Research on the development and planning of renewable energy in Tibet

With the rapid social and economic development of the Tibet Autonomous Region,the situation in regard to energy supply and demand is increasingly tense.Meanwhile,the development of renewable energy in Tibet has been given considerable practical significance by its peculiar ecological environment.Given the complementarity of renewable energies in Tibet,using the method of factor analysis,we derived four major factors:level of economic development,social development,industrial development,and energy endowment,which help to evaluate development conditions in different regions of Tibet.Treating these four factors equally,we used the hierarchical clustering method to determine the order of regional development.Thus we acquire a three-stage planning project for renewable energy.In the first stage,Lhasa plays a leading role in promoting the development of renewable energy,particularly that based on solar and wind energy.There are two phases in the second stage,the first being to simultaneously develop solar and wind energy in Xigaze and Nyingchi.The second is to develop solar and wind energy in accordance with the time of year in Qamdo,Nagqu,and Ali,with 1.145billion kWh electricity to be generated.The third stage is to develop energy production in Lhoka Prefecture,with 1.369billion kWh electricity to be generated.At the end of the three-stage project,consumption of available electricity will have reached 4.045 billion kwh,with major social and economic benefits.

Design and impact estimation of a reform program of China's tax and fee policies for low-grade oil and gas resources

With China＇s rapid economic development,it is important to formulate reasonable and feasible tax and fee policies to promote the development and utilization of low-grade oil and gas resources to guarantee China＇s energy supply security.In this paper,by analyzing major problems of China＇s current tax and fee policies for oil and gas resources,a reform program for low-grade oil and gas resources is designed from the aspects of tax/fee items and tax/fee rates.The impacts of this reform program on China and China＇s oil companies during the ＂Twelfth Five-Year Plan＂ are investigated according to the related data in 2008.The results show that the proposed tax and fee reform program will lower the tax burden of oil companies,promote the development of low-grade oil and gas resources,and increase China＇s GDP and national fiscal revenue.Besides that,it will bring positive social effects by increasing employment opportunities.

Factors affecting the pilot trading market of carbon emissions in China

Climate change and carbon emissions are major problems which are attracting worldwide attention. China has had its pilot carbon emission trading markets in seven regions for more than 3 years. What affects carbon emission trading market in China is a big question. More attention is paid to how China promotes the carbon emission trading schemes in the whole country. This paper addresses concerns about the functioning of carbon emission trading schemes in seven pilot regions and takes the weekly data from November 25, 2013, to March 19, 2017. We employ a vector autoregressive model to study how coal price, oil price and stock index have affected the carbon price in China. The results indicate that carbon price is mainly affected by its own historical price; coal price and stock index have negative effects on carbon price, while oil price has a negative effect on carbon price during the first 3 weeks and then has a positive effect on carbon price. More regulatory attention and economic measures are needed to improve market efficiency, and the mechanisms of carbon emission trading schemes should be improved.

Migration Experience of Village Leaders and Local Economic Development:Evidence from Rural China

This paper examines the impact of migration experience of vzTlage leaders on local economic development, based on the village-level data of the 2005 China General Social Survey. Our results show that the human capital of village leaders accumulated during the migration period has had a positive effect on per capita net income and per capita non-agricultural income in rural China. The migration experience of village leaders also plays a positive role in entrepreneurial activities in rural regions. From a policy perspective, these findings call attention to the importance of harnessing potential benefits of return migration to local economic development in rural China.

Environment and economic feasibility of municipal solid waste central sorting strategy： a case study in Beijing

Although Beijing has carried out municipal solid waste （MSW） source separation since 1996, it has largely been ineffective. In 2012, a ＂Green House＂ program was established as a new attempt for central sorting. In this study, the authors used material flow analysis （MFA） and cost benefit analysis （CBA） methods to investigate Green House＇s environment and economic feasibility. Results showed that the program did have significant environmental benefits on waste reduction, which reduced the amount of waste by 34%. If the Green House program is implemented in a residential community with wet waste ratio of 66%, the proportion of waste reduction can reach 37%. However, the Green House is now running with a monthly loss of 1982 CNY. This is mainly because most of its benefits come from waste reduction （i.e., 5878 CNY per month）, which does not turn a monetary benefit, but is instead distributed to the whole of society as positive environmental externalities. Lack of government involvement, small program scale, and technical/managerial deficiency are three main barriers of the Green House. We, thus, make three recommendations： involve government authority and financial support, expand the program scale to separate 91.4 tons of waste every month, and use more professional equipment/technologies. If the Green House program can successfully adopt these suggestions, 33.8 tons of waste can be reduced monthly, and it would be able to flip the loss into a profit worth 35034 CNY.

A new approach for crude oil price prediction based on stream learning

Crude oil is the world＇s leading fuel, and its prices have a big impact on the global environment, economy as well as oil exploration and exploitation activities. Oil price forecasts are very useful to industries, governments and individuals. Although many methods have been developed for predicting oil prices, it remains one of the most challenging forecasting problems due to the high volatility of oil prices. In this paper, we propose a novel approach for crude oil price prediction based on a new machine learning paradigm called stream learning. The main advantage of our stream learning approach is that the pre- diction model can capture the changing pattern of oil prices since the model is continuously updated whenever new oil price data are available, with very small constant overhead. To evaluate the forecasting ability of our stream learning model, we compare it with three other popular oil price prediction models. The experiment results show that our stream learning model achieves the highest accuracy in terms of both mean squared prediction error and directional accuracy ratio over a variety of forecast time horizons.