Study on Development of the West of Shandong Province Based on Overall Regional Development Planning Pattern

The overall regional development planning pattern has been considered to be a new and effective pattern as for development of provincial economy. The article analyzed the current conditions of the west of Shandong Province and tried to find the generation mechanisms of current non-balanced economic devel- opment of Shandong Province. And then approaches to regional development were put forward according to the theory of regional development pattern as a whole.     

碳税对区域能源消费、经济增长和收入分配影响实证研究

碳税对区域能源消费、经济增长和收入分配影响的研究尚属空白,分别采用面板数据模型的方法和面板分位数回归模型结合对应分析的方法,对这些效应进行实证研究,发现后者能够明显的揭示出我国碳税政策效应的差异性。研究表明：除大西北地区外,碳税对区域能源消费和经济增长都具有显著的抑制效应,且效应由西至东逐渐增强;碳税在各区域都导致资本要素在总收入中的分配比例增加,劳动要素的分配份额降低,但该效应在大西北地区较弱。因此,制定我国碳税政策除了借鉴以碳税效应产业差异为导向的“欧洲经验”以外,还应该注意区域差异,对中西部地区相对倾斜的区域差异性碳税政策可以在控制碳排放的同时促进区域间经济协调发展     

Impact of Regional Economy on Internal Migration in Yangtze Delta： Based on Panel Data

Metropolitan Shanghai, in Yangtze River Delta （YRD）, plays undoubtedly the leading role in the economic development in China, and becomes one of the most important population congregation areas. It is also widely regarded as the sixth uprising urban agglomeration in the world. Based on the quantitative studies on basic socioeconomic and demographic profile on the number and transition of population, this paper concluded that the migration is the key factor for population dynamics in YRD. Then, what are the regional economic factors affecting the migration of different cities in YRD？ The panel data show that the different wage level is the most important factor that affects the immigration in YRD. Moreover, the ratio of industry sector and service sector has an impact on attracting immigration. However, per-capital GDP and the share of foreign direct investment （FDI） to GDP have dual-side impact： not high per-capital GDP and FDI bring the high immigration.     

A fuzzy expert system for soil characterization

As soil is a natural resource not always renewable, the risk characterization of contaminated soils is an issue of great interest. Artificial Intelligence (AI), based on Decision Support Systems (DSSs), has been developed for a wide range of applications in contaminated soil management. Decision trees have already shown to be easy to interpret and able to treat large scale applications. Fuzzy logic gives an improvement in the perturbations and the variance of the training data, due to the elasticity of fuzzy set formalism. In this study, we have developed a classificatory tool applied to characterize contaminated soil in function of human and environmental risks. Knowledge engineering for constructing the Soil Risk Characterization Decision Support System (SRC-DSS) involves three stages: knowledge acquisition, conceptual design and system implementation. A total of 26 parameters were divided into three groups to facilitate the configuration of the expert system: source attributes, transfer vector attributes, and local properties. Sixteen case studies were evaluated with the SRC-DSS. In comparison with other techniques, the results of the current study have shown that SRC-DDS is an excellent tool to classify and characterize soils according to the associated risk.     

Review on Quantitative Research Methods of Regional Sustainable Development in China

Since the 1990s, with the in-depth study and understanding of sustainable development, quantitative study of regional sustainable development (RSD) was increasingly hot in China. Based on quantitative study of RSD from Core Periodical in China National Knowledge Infrastructure (1992–2008), statistical analysis on the annual distribution, periodicals distribution and changes of the distribution were made. And from perspectives of social–economic, ecological, systematic and emerging methods, the course, probl...     

三峡水库对区域气候影响的数值模拟分析

利用中尺度数值模式MM5V3模拟了三峡水库建成后,由于下垫面变化对区域气候的影响,并探讨了三峡水库的建成是否为引发社会广泛关注的高温干旱和低温雨雪冰冻灾害等极端天气的主要因素。研究表明:三峡水库的建成对当地气温具有海洋性效应,库区附近春季温度变低,夏季在水库下游气温升高、上游则气温降低,而冬季则以升温为主;春季降水变化主要位于库区沿线的南部山区,增雨带和减雨带相间分布,夏季降水量在三峡库区中上游地区和附近的山区呈增加趋势,在库区下游及附近地区降水呈减少趋势,冬季降水量减少,主要集中在大坝附近地区到三峡(巫山)段;春季库区的相对湿度增加,幅度多在0.5%～1.0%,夏季相对湿度的影响也存在正负两种效应,大坝上游库区附近相对湿度增加,大坝下游地区相对湿度降低,冬季变幅不大;三峡水利工程不是干旱、低温雨雪冰冻等极端天气出现的主因,它对极端天气事件的影响并不明显。     

Natural product biomarkers as indicators of sources and transport of sedimentary organic matter in a subtropical river

The sources and transformations of sedimentary organic matter along the Harney River, a representative subtropical river of the Florida Everglades, were assessed using a natural product biomarker approach. Sediment samples were collected from the headwaters to the Continental Shelf, with characteristic vegetation dominated by freshwater marsh species, mangrove (middle to lower estuary), and seagrass as the marine end-member. A peat sample was collected inland. All sample extracts were analyzed by GC–MS as underivatized and as silylated compounds. With these total extract analyses, major compound classes can be defined: n-alkanols, n-alkanoic acids, methyl alkanoates, methyl - and ω-hydroxyalkanoates, triterpenoids, phytosterols and saccharides, with traces of hydrocarbons. In general, the peat sample extract has a different overall composition compared to the sediment extracts. The major differences include distinct carbon number maxima for the lipid series (e.g., C_max = 28 for n-alkanols) probably from sawgrass and periphyton biomass, and predominance of phytosterols (sitosterol and stigmasterol) from higher plant detritus. In contrast, river sediment extracts contain biomarkers predominantly from mangrove-derived organic matter, such as the triterpenoids taraxerol and myricadiol. Significant amounts of saccharides and ω-hydroxyalkanoates are also found. Generally, compound concentrations decrease downstream due to dilution, and alteration of organic compounds from plant waxes and coastal vegetation is obvious in both peat and sediment samples. This is confirmed by the significant low abundance of n-alkanes and n-alkenoic acids due to biodegradation, oxidation of -tocopherol to homophytanic acid γ-lactone, and presence of traces of dihydrolacunosic acid, a photochemical alteration product of taraxerol.     

REGIONAL SEWERING AND GROUNDWATER QUALITY IN THE SOUTHERN SAN JOAQUIN VALLEY1

ABSTRACT: Sewage effluent is commonly disposed of on land in arid regions, and the majority usually recharges the groundwater. Few evaluations have been made of the effect of effluent disposal on groundwater quality in the west. Groundwater hydrologists are rarely involved with treatment plant design and operation or effluent disposal in the San Joaquin Valley, California. The author's purpose is to evaluate the effect of regional sewering programs on groundwater quality in this valley. Research was conducted on past studies of sewage effluent disposal. An extensive water sampling program was undertaken near the Fresno Sewage Treatment Plant. Chloride contents were used to trace recharged effluent. The extent of recharged effluent was delineated and traced for about ten miles. Sampling between the plant and the urban Fresno area indicated a high probability of large-scale leakage of raw sewage into the groundwater.     

巢湖区域地质旅游资源评价与开发对策

通过专家咨询和问卷调查分析方法，对巢湖区域地质旅游资源进行了综合评价和等级划分，明确了地质旅游资源在巢湖区域旅游开发中的地位与潜力，提出了对该区地质旅游资源规划和开发的途径与措施，探讨了地质旅游资源的保护对策。     

REGION OF INFLUENCE REGRESSION FOR ESTIMATING THE 50-YEAR FLOOD AT UNGAGED SITES1

ABSTRACT: Five methods of developing regional regression models to estimate flood characteristics at ungaged sites in Arkansas are examined. The methods differ in the manner in which the State is divided into subregions. Each successive method (A to E) is computationally more complex than the previous method. Method A makes no subdivision. Methods B and C define two and four geographic subregions, respectively. Method D uses cluster/discriminant analysis to define subregions on the basis of similarities in watershed characteristics. Method E, the new region of influence method, defines a unique subregion for each ungaged site. Split-sample results indicate that, in terms of root-mean-square error, method E (38 percent error) is best. Methods C and D (42 and 41 percent error) were in a virtual tie for second, and methods B (44 percent error) and A (49 percent error) were fourth and fifth best.