Nowadays, more and more cars have begun to enter into innumerable families; the family car has become a necessity for Chinese households who have certain purchasing power. However, the ups and downs of oil prices have brought some impact on people's automobile consumption activities. Therefore, after collecting the information of the oil price and family car consumer, carried on through in-depth analysis of the relevant data with reasonable relationship, and then developed a suitable for China's national conditions and finished oil pricing model, thereby the National Development and Reform Commission have proposed the suggestion for China's refined oil pricing mechanisms and promoting the healthy development of new energy vehicles with specific measures. For question 1, through the problem analysis and information access, combined with the past and current situation of the domestic refined oil prices, we analyze the following seven factors: international crude oil prices, China's annual crude oil imports, China's annual crude oil exports, crude oil output in China, China's annual GDP per capita, China's annual consumption of crude oil, the total annual energy consumption in China, all have influence on China's refined oil prices. By monadic linear regression analysis, annual average prices of domestic refined oil products have a certain correlation with the various influencing factors, and then by multiple linear regression way eventually concluded the final relationship between oil prices and the influence factors, which compared with the current price, and make reasonable evaluation model. Through the establishment of various influencing factors and function of time, and using the evaluation model for refined oil product price to make reasonable forecast. According to this model, in order to predict refined oil product price as $122.15 per barrel in 2016. For question two, we basically sums up three key factor which influence the quantity of family vehicle: China's oil product prices, the annual GDP per capita, total road mileage. Through Excel to make the relationship curves of different quantity of family cars against influencing factors, and use Grey Forecasting method to forecast the quantity of family cars. And carries on the residual error test, it is used to conclude that the rationality of the model is highly. The number of private cars of the city of xi 'an is predicts that to 8.302 million vehicles by 2020. For question three, we discussed the relationship between international crude oil prices and domestic exports of crude oil export with domestic refined oil prices, through its multiple linear regressions to get the final pricing model. For question four, according to three previous established models, we proposed China's refined oil pricing mechanism proposal to the national development and Reform Commission: perfect price controls, deeper product market, and integration of resources consideration and environmental protection class tax types, adjust the consumption tax collection and Administration links, and improve the production cost accounting.

Fe3+-doped nano-TiO2 powders were prepared by sol-gel method. The photocatalytic activity of Fe3+-doped TiO2 nanoparticles was studied by using UV lamp as light source and methylene blue as degradation target. The photocatalytic activity of Fe3+-doped TiO2 was studied by degradation of 4L methylene blue solution with initial concentration of 10mg · L - 1. The results show that the photocatalytic activity of TiO2 can be improved by the addition of Fe3+. When the molar ratio of Fe3+ is 0.5-1%, the calcination temperature is 500 ℃. The photocatalytic degradation of methylene blue is the best.

Lianghuai Mining Area is one of the 13 large coal bases in China. It is an important coal and coal production base in China. Mine water inrush accidents occur frequently, resulting in economic and human resource losses, reflecting the importance of the study of hydrogeology in mining areas. In this paper, the hydrogeological conditions of Bozhou and Huainan Panxie mine are analyzed, and the similarities and differences between the hydrogeological conditions of the two mines are summarized. The shallow pore water group in the Bozhou area is composed of the Quaternary system of the Quaternary system (Q4d) and the upper part of the upper part of the Mao Tong group (Q3m). The lithology of the aquifer is silt, silt and fine sand. The shallow pore water group of the Panxian Pancho Formation in Huainan is composed of the Upper Pleistocene of the Quaternary system and the Holocene strata. The lithology is mainly composed of fine sand. The main sources of shallow pore water supply in the two areas are precipitation infiltration, mainly for evaporation, lateral runoff, artificial mining and deep flow and discharge to the river.

In this paper, all the forests, woodlands and trees in the administrative area of Zhaoling Township in Chuzhou City of Huai'an City were collected and analyzed. The total area of the administrative area is 4852 hectares, the forest coverage rate is 22.07%, and the forest greening rate is 26.13%. This index has exceeded 20% of the forest coverage rate of the well - off society. Tree species is particularly serious. In the forest system (pure forest), the area of pure forest of poplar is accounted for 99.9% of the whole forest area. In the four tree systems, the number of poplar trees accounted for 80% of the total number of trees in the whole tree, and the total amount of poplar trees accounted for 98%. The poplar pure forest age group structure disorders, the unit area is low. The ratio of total area of poplar pure forest in Zhongling and young forests was 92.9%, and the ratio of total area of poplar pure forest and mature forest was 7.1%. The ratio of mature forest and the ratio of mature forest was 0.7%, and the proportion of each group was obviously abnormal.

Using a newly developed data set, we analyze the effects of infrastructure investment on economic performance in Portugal. A vector-autoregressive approach estimates the elasticity and marginal products of twelve types of infrastructure investment on private investment, employment, and output. We find that the largest long-term accumulated effects come from investments in railroads, ports, airports, health, education, and telecommunications. For these infrastructures, the output multipliers suggest that these investments pay for themselves through additional tax revenues. For investments in ports, airports and education infrastructures, the bulk of the effects are short-term demand-side effects, while for railroads, health, and telecommunications, the impact is mostly of a long-term and supply-side nature. Finally, investments in health and airports exhibit decreasing marginal returns, with railroads, ports, and telecommunications being relatively stable. In terms of the other infrastructure assets, the economic effects of investments in municipal roads, electricity and gas, and refineries are insignificant, while investments in national roads, highways, and waste and waste water have positive economic effects but too small to improve the public budget. Clearly, from a policy perspective, not all infrastructure investments in Portugal are created equal.