不同发展模式下资源环境承载力评价——以海南省为例

文章关注于产业、人口与资源环境要素的作用关系,建构了资源环境承载力综合评价框架,并以海南省为案例区开展应用研究。该框架首先对区域产业重要性进行评价并分级,为产业结构调整提供依据;其次解析了区域产业、人口资源消耗与污染排放强度,最后,基于产业评价结果设定不同的产业结构调整情景,结合产业和人口的资源消耗与污染排放强度评价不同产业结构下的资源环境承载力,即产业和人口的规模上限。结果表明：2016年海南省的经济规模并未超载,产业有进一步发展空间。其中土地资源成为海南省发展的首要限制因素,其次是水环境;海南经济效益较高的支柱产业和基础性产业多为高耗水、高污染的产业,亟需加强水资源的集约利用,并降低污染排放强度。为提升经济发展规模上限,需要培育低能耗、低排放的产业。文章建构的资源环境承载力评价方法将产业、人口与资源环境相联系,其评价结果政策意义更为明确,可为优化产业结构调整、控制产业及人口发展规模提供决策参考。     

地方政府土地出让干预对区域工业碳排放影响的对比分析——以中国8大经济区为例

探讨不同区域地方政府干预对碳排放的影响差异,对于中国推进碳减排战略、协调区域经济社会发展具有重要意义。鉴于此,论文基于地方政府土地出让的视阈,以中国8大经济区为研究对象,有机耦合STIRPAT模型与CKC模型,构建形成STIRPAT拓展模型,并使用2007—2016年中国28个省(市、自治区)的工业面板数据,对比考察8大经济区政府土地出让干预对区域碳排放的影响差异。结果表明:不同经济区的地方政府土地出让干预对区域碳排放的影响存在显著差异。其中,同为CKC“倒N”型的北部沿海、南部沿海、长江中游经济区,其政府土地出让干预对区域碳排放的影响呈现出北部沿海经济区为负、南部沿海经济区为正、长江中游经济区无显著影响的差异效果;同为CKC“倒U”型的东北、西南和西北经济区,其政府土地出让干预对区域碳排放的影响,东北和西南经济区都显著为负,西北经济区未表现出显著影响;同为CKC“U”型的东部沿海和黄河中游经济区,其政府土地出让干预对碳排放也呈现出前者为负、后者为正的相反影响。研究结果可为制定碳减排差别化政策、协调区域可持续发展提供参考。     

Characterisation and preliminary quantification of the methane reservoir in a coastal sedimentary source: San Simón Bay,Ría de Vigo,NW Spain

Ría de Vigo is a river valley flooded by the sea, with a bay (San Simón Bay) at its innermost part. The accumulation of Holocene sediment in San Simón Bay has been studied by the integration of 1) large scale high resolution seismic data, and 2) detailed geochemical analysis of a gravity core. In San Simón Bay the majority of the seismic records are obscured by acoustic turbidity which represents gassy sediments, but on records from Rande Strait it is possible to distinguish two Quaternary seismic sequences; an Upper Pleistocene sequence (SQ1) and a Holocene sequence (SQ2). Only SQ2 is recognized in San Simón Bay where it is comprised of two seismic units; the upper unit represents the HST sediment, i.e. the period of highest sea level. A gravity core taken within the gassy zone at 10 m water depth provided 3.55 m of fine-grained sediments (muds) from the youngest seismic unit (4 m thick). Geochemical analysis show high values (4 to 10%) of TOC. Sediment and porewater analyses indicate a distinct sulphate–methane transition zone (SMTZ) between 60 and 80 cm where sulphate is depleted (to <1.7 mM) and methane increases (to >0.4 mM). The top of the acoustic turbidity (the gas front) at 80 cm corresponds to the lower limit of the SMTZ. The methane cannot have been derived from the underlying metamorphic and granitic rocks, but was probably derived by microbial degradation of the organic matter in the Holocene sediments. We estimate that the sediments of the Bay contain approximately 1.8 × 10⁶ m³ of organic carbon and 275 ton of methane.     

空间同位模式支持下城市服务业关联发现及特征分析

空间同位模式分析是数据挖掘中一种常见的方法,可有效挖掘城市设施在空间位置上的关联特征,进而发现城市设施的分布规律.本文基于POI数据同位模式挖掘用来获取城市服务业空间关联结构:首先,通过邻近实例获取、同位候选模式存储与筛选,得到城市服务业二阶同位模式;然后,据此构造产业空间关联图,得到产业间的关联结构;最后,分别构造了...     

产业空间集聚及其效应的研究进展

产业的空间集聚是经济活动最突出的地理特征, 也是一个世界性的经济现象。产业集聚 一直是经济地理学、区域经济学、管理学等相关学科研究的主要问题之一, 特别是20 世纪90 年 代以来, 产业集聚成为经济学和地理学的热点课题。本文重点回顾了产业区位论、新产业区理论 以及新经济地理理论等对产业集聚的理论阐述。并从产业集聚的影响因素和产业集聚效应两个 方面综述了近年来国内外有关产业集聚的实证研究, 突出了要素禀赋、外部性、规模经济等在产 业集聚形成过程中的重要作用, 并指出了产业集聚形成后对产业区位、产业增长以及区域经济增 长产生的影响。最后对国内产业集聚研究现状进行了总结。     

中国地区制造业竞争力的时间变化和空间分异解析

地区制造业竞争力是地区制造业在区域之间的市场竞争中表现出来的综合实力、所提供的有效产品或服务的能力及其未来的发展潜力大小。利用构建的地区制造业竞争力评价模型,以省区为基本单元,分析了近20年来中国地区制造业竞争力的时间变化特征和空间分布格局,并对这种变化和差异的动因给与解析。研究表明,从1985年到2003年的近20年来,中国地区制造业竞争力呈现出一定的时空演化规律:①随着改革开放进程的加速和地区经济实力的提高,地区制造业的综合竞争能力普遍抬升;②中国地区制造业竞争力的地域差异明显,由东部沿海向中、西部内陆逐渐递减,且差距随时间的推移呈扩大趋势;③地区制造业竞争力与其驱动因素关系密切。驱动因素的时空分布格局决定了地区制造业竞争力的时间过程与空间格局演变趋向。     

Appropriate Spatial Sampling of Rainfall or Flow Simulation/Echantillonnage Spatial de la Pluie Approprié pour la Simulation D'écoulements

Abstract

The objective of this study is to find the appropriate number and location of raingauges for a river basin for flow simulation by using statistical analyses and hydrological modelling. First, a statistical method is used to identify the appropriate number of raingauges. Herein the effect of the number of raingauges on the cross-correlation coefficient between areally averaged rainfall and discharge is investigated. Second, a lumped HBV model is used to investigate the effect of the number of raingauges on hydrological modelling performance. The Qingjiang River basin with 26 raingauges in China is used for a case study. The results show that both cross-correlation coefficient and modelling performance increase hyperbolically, and level off after five raingauges (therefore identified to be the appropriate number of rain-gauges) for this basin. The geographical locations of raingauges which give the best and worst hydrological modelling performance are identified, which shows that there is a strong dependence on the local geographical and climatic patterns.     

Fuzzy Optimization Neural Network Approach for Ice Forecast in the Inner Mongolia Reach of the Yellow River/Approche d'Optimisation Floue de Réseau de Neurones pour la Prévision de la Glace Dans le Tronçon de Mongolie Intérieure du Fleuve Jaune

Abstract

In ice forecasting, a key problem is the forecast of freeze-up and break-up dates. Ice-water mechanics and the principle of heat-exchange were mainly adopted in previous research. However, the mathematical models in these studies are complex and many parameters are required in relation to upstream and/or downstream gauging stations. Moreover, too many assumptions or simplifications for these parameters and constraints directly lead to low accuracy of the models and limitations as to their practical applications. This paper develops a fuzzy optimization neural network approach for the forecast of freeze-up date and break-up date. The Inner Mongolia reach lies in the top north of the Yellow River, China. Almost every year ice floods occur because of its special geographical location, hydrometeorological conditions and river course characteristics. Therefore, it is of particular importance for ice flood prevention to forecast freeze-up date and break-up date accurately. A case study in this region shows that the proposed methodology may allow obtaining useful results.     

Are artificial neural network techniques relevant for the estimation of longitudinal dispersion coefficient in rivers? / Les techniques de réseaux de neurones artificiels sont-elles pertinentes pour estimer le coefficient de dispersion longitudinale en rivières?

Abstract

Abstract Accurate application of the longitudinal dispersion model requires that specially designed experimental studies are performed in the river reach under consideration. Such studies are usually very expensive, so in order to quantify the longitudinal dispersion coefficient, as an alternative approach, various researchers have proposed numerous empirical formulae based on hydraulic and morphometric characteristics. The results are presented of the application of artificial neural networks as a parameter estimation technique. Five different cases were considered with the network trained for different arrangements of input nodes, such as channel depth, channel width, cross-sectionally averaged water velocity, shear velocity and sinuosity index. In the case where the sinuosity index is included as an input node, the results turned out to be better than those presented by other authors.     

Relations indices de Végétation–Pluie au Burkina Faso: Cas du Bassin Versant du Nakambé/Relationship between Rainfall and Vegetation Indexes in Burkina Faso: A Case Study of the Nakambé Basin

Abstract

This work deals with the problem of the use of remote sensing data derived from NOAA/AVHRR observations for monitoring the West African Sahel climatic variability. NDVI is widely used in hydrological and climatological research, and in the study of global climatic changes. The relationships between NDVI and climatic parameters are not well established yet and are the focus of many studies. The relationships between NDVI and rainfall were studied at a 10-day time step in the Nakambe River basin in Burkina Faso in the Sahelo-Sudanian area over the years 1982–1999. Good correlations were found in the annual evolution of these two variables. The statistical analysis shows a significant relationship between NDVI and the sum of the annual rainfall with determination coefficients greater than 0.80. At the spatial scale of 0.5° × 0.5°, the determination coefficient ranges from 0.91 to 0.96. It was also found that the NDVI is a good indicator of the determination of the beginning and the end of the rainy season. It gives reasonably good results in comparison with the other methods commonly used in the study region.