Spatial energy efficiency patterns and the coupling relationship with industrial structure:A study on Liaoning Province,China

Using a sample of 14 prefecture-level cities in Liaoning Province, this study first explored the spatial hierarchy and structural characteristics of energy efficiency from the following three viewpoints: energy technical efficiency based on data envelopment analysis, energy consumption per unit of GDP, and energy utilization efficiency combining the previous two indexes. After measuring and analyzing the advancement, rationality, and concentration of the industrial structure in each city, we made some generalizations about the coupling features of the energy efficiency and industrial structure in Liaoning, using the coupling degree rating model. Some of our conclusions are as follows: (1) The 14 cities differ significantly in their energy efficiency, with Shenyang, Dalian, Anshan, and Jinzhou enjoying the highest energy efficiency. Northwestern Liaoning and other heavy-industrial cities such as Fushun and Benxi belong to low-efficiency and high-consumption areas. (2) In areas with higher efficiency, the spatial patterns of the energy technical efficiency, energy consumption per unit of GDP, and energy utilization efficiency are, respectively, "π"-,"Ⅱ"- and "H"- shaped. Geographically, the energy utilization efficiency shows different trends from east to west and from north to south. Factors such as the binuclear structure of economic development have a major effect on this spatial pattern of energy efficiency. (3) Southeastern Liaoning enjoys a highly advanced industrial structure. Areas with a highly rational industrial structure form an “H” shape, with Shenyang and Dalian at the two poles. The urban agglomerations in middle and southern Liaoning have a highly concentrated industrial structure. (4) Overall, the coupling between energy efficiency and industrial structure is low in Liaoning, except for Shenyang and Dalian at both ends, where the coupling between an advanced industrial structure and energy efficiency is higher than in other cities.     

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胶州湾水体重金属Hg的质量浓度和分布

根据1982-04、06、07和10月胶州湾水域调查资料,探讨和研究胶州湾重金属Hg的水质、平面分布、垂直分布、季节变化以及来源.结果表明：Hg在胶州湾水体中的质量浓度范围为：0.006～0.049 μg/L,在胶州湾整个水域,没有受到Hg的污染.在胶州湾西南沿岸水域,地表径流直接输送Hg入海,其质量浓度都非常低;在胶州湾东部沿岸水域,河流输送Hg入海,其质量浓度相对较高.Hg的表、底层水平分布证实了Hg的水域迁移过程和水域迁移机制.Hg质量浓度的垂直分布展示了胶州湾表层水质受到陆地地表径流输送Hg的影响,而胶州湾底层水质受到累计沉降的效应.通过胶州湾Hg的时空分布,发现控制Hg的排放得到实施,输入胶州湾水域的Hg大为减少.     

GIS支持下的澜沧江流域云南段土壤侵蚀空间分析

利用ArcView3.2和ARC/INF08.1软件,通过图层叠加、统计分析和缓冲区分析等,提取西南纵向岭谷区澜沧江流域云南段的不同类型和强度的土壤侵蚀与地形坡度、土地利用/土地覆盖现状、土壤类型和分布、大雨日数以及河流、道路两侧的缓冲区等的相应数据,计算出土壤侵蚀综合度。结果表明,研究区不同坡度等级中,15°²5°坡度上的土壤侵蚀最强,其次为8°¹5°坡地和4°⁸°坡地;>25°坡地上则较小;不同用地类型的土壤侵蚀程度不同,总体上,旱耕坡地的土壤侵蚀较草地严重,而草地又较林地严重;在各种土壤类型中,黄壤和石灰土的土壤侵蚀最为突出,其次为红壤、黄棕壤和南方水稻土等;河流两侧和道路两侧的土壤侵蚀都较整个流域要严重,而河流两侧又略重于道路两侧;当多年平均大雨日数小于20日时,土壤侵蚀程度基本上随大雨日数的增加而增加;当大雨日数大于20日时,土壤侵蚀程度反而较小,原因在于前期大雨冲刷侵蚀,带走了地表的疏松物质。研究结果可为有针对性地防治水土流失、减少河流泥沙和水库淤积提供依据。     

洛阳地区太阳能资源分析与评估

根据1981—2010年郑州辐射站太阳辐射和日照资料、洛阳地区9个气象观测站日照资料,采用气候学计算、线性趋势分析等方法和资源丰富程度、利用价值、稳定程度等指标,对洛阳地区太阳能资源进行了计算、分析和评估。结果表明:洛阳地区多年平均总辐射为4842.4MJ·m-2·a-1,总体呈显著减少趋势,减少速率为每年1.4MJ·m-2。夏季辐射丰富,冬季偏少,夏季总辐射量是冬季的2倍;月平均总辐射5月最多(569.7MJ·m-2),12月最少(241.9MJ·m-2);年总辐射孟津最高,为4922.8MJ·m-2·a-1,宜阳最少,为4681.1MJ·m-2·a-1。多年平均日照时数为2064.7h,总体呈显著减少趋势。春季日照时数多,冬季少,春季日照时数比冬季多33.37%;月平均日照时数5月最多(217.3h),2月最少(138.2h);年日照时数孟津最多(2144.9h),宜阳最少(1909.2h)。洛阳各地属太阳能资源丰富区,利用价值较高,各月日照时数6h的天数为9.8~18.1天,全年为162.7~185.3天;太阳能资源也比较稳定,月最大日照时数12月6h的天数为16.9天,是月最小日照时数7月的1.48倍,12月至次年1月不利于太阳能利用。     

基于节水视角的中国水资源压力时空演变及影响因素分析

基于水资源节约视角,采用区域水资源规划消耗量占该地区水资源可利用量的比重来测算水资源压力指数,运用趋势分析、探索性数据分析(ESDA)方法对2005-2017年中国31个省市水资源压力指数空间格局演化特征与空间相关性进行分析,并选取8个相关变量,采用地理探测器探究影响水资源压力指数空间分异的因素,结论如下:①研究期内,...     

Spatial distribution and behavior of dissolved selenium speciation in the South China Sea and Malacca Straits during spring inter-monsoon period

Selenium(Se) has been recognized as a key trace element that is associated with growth of primary producers in oceans. During March and May 2018, surface water(67 samples) was collected and measured by HG-ICP-MS to investigate the distribution and behavior of selenite [Se(IV)], selenate [Se(VI)] and dissolved organic selenides(DOSe) concentrations in the Zhujiang River Estuary(ZRE), South China Sea(SCS) and Malacca Straits(MS). It showed that Se(IV)(0.14–3.44 nmol/L) was the dominant chemical species in the ZRE, related to intensive manufacture in the watershed; while the major species shifted to DOSe(0.05–0.79 nmol/L) in the MS, associated with the wide coverage of peatland and intensive agriculture activities in the Malaysian Peninsula. The SCS was identified as the northern and southern sections(NSCS and SSCS) based on the variations of surface circulation.The insignificant variation of Se(IV) in the NSCS and SSCS was obtained in March, potentially resulting from the high chemical activity and related preferential assimilation by phytoplankton communities. Contrastively, the lower DOSe concentrations in the SSCS likely resulted from higher primary production and utilization during March. During May, the concentration of Se(IV) remained low in the NSCS and SSCS, while DOSe concentrations increased notably in the SSCS, likely due to the impact of terrestrial inputs from surface current reversal and subsequent accumulation. On a global scale, DOSe is the dominant Se species in tropical oceans, while Se(IV) and Se(VI) are major fractions in high-latitude oceans, resulting from changes in predominated phytoplankton and related biological assimilation.     

一种基于最佳指数模型的 TM 遥感影像最佳波段组合计算方法

如何通过定量计算选择最佳波段组合一直是TM等多波段遥感影像信息提取的研究热点。本文综合利用Erdas提供的可视化空间建模工具（ Spatial Modeler ）和面向对象的编程技术,提出了一种基于最佳指数（ Opti-mum Index Factor ,OIF）的定量计算与定性分析相结合的TM遥感影像最佳波段组合方法。实验证明,该方法快速有效,极大提升了TM等多波段遥感影像最佳波段组合的计算过程。     

Research on spatial calculating analysis model of landuse change

The spatial calculating analysis model is based on GIS overlay. It will compartmentalize the land in research district into three spatial types: unchanged parts, converted parts and increased parts. By this method we can evaluate the numerical model and dynamic degree model for calculating land-use change rates. Furthermore, the paper raises the possibility of revising the calculating analysis model of spatial information in order to predicate more precisely the dynamic changing level of all types of land uses. In the most concrete terms, the model is used mainly to understand changed area and changed rates (increasing or decreasing) of different land types from microcosmic angle and establish spatial distribution and spatio-temporal principles of the changing urban lands. And we will try to find out why the situation can take place by combining social and economic situations. The result indicates the calculating analysis model of spatial information can derive more accurate procedure of spatial transference and increase of all kinds of land from microcosmic angle. By this model and technology we can conduct the research of land-use spatio-temporal structure evolution more systematically and more deeply, and can obtain a satisfactory result. The result will benefit the rational planning and management of urban land use of developed coastal areas in China in the future.     

STATISTICAL ANALYSIS ON THE INFLUENCE OF THE LANDFALLING STRONG TROPICAL CYCLONES IN THE CATASTROPHIC MIGRATIONS OF NILAPARVATA LUGENS(STL) IN CHINA

In order to clarify the statistical pattern by which landfalling strong tropical cyclones(LSTCs)influenced the catastrophic migrations of rice brown planthopper(BPH),Nilaparvata lugens(stl)in China,the data of the LSTCs in China and the lighting catches of BPH that covered the main Chinese rice-growing regions from 1979 to 2008 were collected and analyzed in this work with the assistance of ArcGIS9.3,a software of geographic information system.The results were as follows:(1)In China,there were 220 strong tropical cyclones that passed the main rice-growing regions and 466 great events of BPH’s immigration in the 30 years from 1979 to 2008.73 of them resulted in the occurrence of BPH’s catastrphic migration(CM)events directly and 147 of them produced indirect effect on the migrations.(2)The number of the LSTCs was variable in different years during 1979 to 2008 and their influence was not the same in the BPH’s northward and southward migrations in the years.In the 30 years,the LSTCs brought more obvious influence on the migrations in 1980,1981,2005,2006 and 2007.The influence was the most obvious in2007 and all of the 7 LSTCs produced remarkable impact on the CMs of BPH’s populations.The effect of the LSTCs on the northward immigration of BPH’s populations was the most serious in 2006 and the influence on the southward immigration was the most remarkable in 2005.(3)In these years,the most of LSTCs occurred in July,August and September and great events of BPH's immigration occurred most frequently in the same months.The LSTCs played a more important role on the CM of BPH’s populations in the three months than in other months.(4)The analysis on the spatial distribution of the LSTCs and BPH’s immigration events for the different provinces showed that the BPH’s migrations in the main rice-growing regions of the Southeastern China were influenced by the LSTCs and the impact was different with the change of their spatial probability distribution during their passages.The most serious influence of the LSTCs on the BPH’s migrations occurred in Guangdong and Fujian provinces.(5)The statistical results indicated that a suitable insect source is an indispensable condition of the CMs of BPH when a LSTC influenced a rice-growing region.