Coal power generation is the second largest water use industry in China; its fast expansion puts pressures on water resources; water use quota management is supposed to be a vital means in saving water for coalpower generation industry. This paper, based on benchmark energy efficiency level of nationwide coal power plants, uses multiple regression model to evaluate water use intensity and factors of unit power generation in coal power plants, and estimates the expected water saving quantity in accordance with the latest edition of Coal Power Water Use Quota. The suggested general water use quota has little push on motive of saving water upgrading for coal power plants. Total saving water may be 122 millions cubic meters in 2020 given all plants comply with the suggested quota, but could be up to 823 millions cubic meters if three northern China regions satisfy the quota where water resources are rare, while other regions reach a premium quota. Viewing from technical perspective, water saving quantity proportions of circular cooling, direct cooling and air cooling are 58.6%, 18.7% and 22.8% under differentiated scenarios. Water saving quantity in eastern and northern China is over 200 millions cubic meters, around one forth nationwide, 108 million cubic meters in northwestern China, and 53 million cubic meters in northeastern China, the least. 

This paper applies eco-efficiency model and entropy weight TOPSIS to quantitatively analyze Shanghai’s resource, environmental and ecological efficiency during 2005-2014, with the result used to judge its economic mode, and employs obstacle mode to diagnose its obstacle factors. Ecological efficiency level had undergone a low-medium-high change during 2005 to 2014, showing a rising trend. Economic mode along an ABD path had undergone a traditional linear mode, end treatment mode and recycling mode. The top three key obstacle factors against eco-efficiency are overall emission of industrial gas waste (8.56%), industrial fumes emission (8.53%) and living electricity (8.30%).

Study on the coordination between population urbanization and land urbanization is of significance to optimizing human land relation during urbanization and promoting new urbanization. This paper selects population urbanization and land urbanization factors, establishes an index system and coordination model to study the coordination between Suzhou’s population urbanization and land urbanization from 2005-2014. The result shows a rising population urbanization index and land urbanization index with urban development turning into population lagging from land lagging. The coordination transitions into relatively coordinated from not coordinated with lagging population urbanization and falsely leveled land urbanization, due to the urban expansion model and development policy. Suzhou shall select a rational urban expansion model and progressively develop the urban and rural integration, boost intensive use of urban land and diversify the urbanization capital.

This paper, based onnine factors relatedto energy supply stability and Shaanxi'sdata 1990—2011, concludes that the major factors of Shaanxi's energy supply stability are energy investment, carbon emission intensity, GDPper capita, industrial structure, population with their elasticity 0.8293, -0.2373, -0.2876, -2.1336and -2.4144, respectively. According to Shaanxi'senergy objectives and economicsocial planning, thispaper sets up scenarios for economy,popular growth, carbon emissionintensity andenergyinvestment, and forecasts the stability under ninescenarios. Shaanxi's stability rises upto 5.567 1 in 2020 under a low growth of populationand GDP per capita, a high growth in energy investment, andan intensified industrial structureadjustment and reducing carbon emission, but can't last long. Scenarios A, Band C are assumed under different energy investment growth to study the influence ofenergy investment over energy supply stability,which need tolimit growth in energy investment to avoid over mining and to maintain a rational energy production.