烟台港倾倒区表层沉积物重金属的富集特征及风险评价

分析了2001~2011年烟台港倾倒区表层沉积物中6种重金属的含量及时空分布特征,采用地累积指数(Igeo)和潜在生态风险指数(ERI)对重金属富集现状及潜在生态风险进行评价。结果显示：历次调查重金属含量均较低且空间分布差异小,与黄海背景值相比, Cd和Cu出现一定程度的富集。ERI评价表明2011年倾倒区潜在生态风险性较低,年际变化顺序为：2008年＞2006年＞2009年＞2011年＞2001年, Cd和Hg是近年来的主要风险因子。     

Assessment and management of Cape horse mackerel Trachurus capensis off Namibia based on a fleet-disaggregated age-structured production model

The Cape horse mackerel stock off Namibia is assessed using a fleet-disaggregated age-structured production model including historical International Commission for the Southeast Atlantic Fisheries (ICSEAF) and current data. Data from acoustic biomass surveys, on commercial catch per unit effort and on commercial catch-at-age, were used to estimate current stock status over a range of model specifications. A management tool, the so-called management monitor graph, was introduced in order to track past management relative to stock status. Target, limit and precautionary reference points, decision rules and harvesting strategies, according to which the stock should be managed, are described and tested. The target reference point was set at maximum sustainable yield (MSY), the precautionary reference point at 80% of MSY and the limit reference point at 30% of MSY. Owing to some inconsistencies in the dataseries, evaluation of the current state of the resource is challenging, but estimates are that the resource is around the MSY level, somewhere between 250 000 and 300 000 t.     

Environment and Deep-Sea Mining: A Perspective

Abstract

As the quest for deep-sea mineral resources is gaining momentum, environment and ocean mining have become important aspects of study. Because many of these deposits occur in international waters, the concern for environmental conservation in view of the effects of deep-sea mining is resulting in these effects being studied in different oceans, and efforts to develop regulations governing this exploitation are also underway at national and international levels. The impact assessment of deep-sea mining needs to encompass a variety of subjects, including environmental, socioeconomic, technological, and legal aspects. At the same time, effects of in situ environmental conditions on mining activities also need to be considered for effecient performance by the mining system. Differences in the degree of impact have been noticed during the mining simulation experiments by different investigating agencies. Therefore, interparameter comparisons, standardization of methods, and improvement in mining design are important considerations for proper utilization of resources, conservation of environment, and cost efficiency of the mining operations.     

Environmental Issues Pertaining to the Kwale Mineral Sands Project,Kenya's South Coast—Reply

Tiomin Resources Inc. (“Tiomin”), the proponent of the Kwale Mineral Sands Project in Kenya, presents a response to the article authored by J. O. Z. Abuodha and P. O. Hayombe, entitled “Protracted Environmental Issues on a Proposed Titanium Minerals Development in Kenya's South Coast”, published in Volume 24, Number 2, April–June 2006. This article contains a series of inaccuracies, some grossly misleading and many statements relate to outdated information. Tiomin is greatly concerned at the publication of such a misleading report and is obliged to state the facts correctly. This response seeks to identify the misrepresentation of statements and/or facts in the article and present a correct and accurate perspective on the environmental issues of the project.     

On the use of Atterberg limits on marine soils

Abstract

On the basis of the Atterberg indexes of various sediments collected in the Mediterranean Sea, we select two major parameters indicative of the mechanical behavior of marine soils: the sedimentary facies (i.e., mechanism of deposition expressed by silt content) and the clay mineral association characterized by smectite content in the fraction finer than 2 μm. Activity and real thixotropic ability appear to be particularly important parameters in marine engineering; better values are obtained by a double test operation in distilled and marine water.     

灾害学定义之下的土壤盐碱化风险评价

为改善灌区中低产地的产量、提高其田间管理及粮食综合生产能力、防止土壤盐碱化灾害的扩展,在土壤盐碱化灾害学研究的基础上,建立了土壤盐碱化灾害风险评价指标体系。选用基于熵权的灰色关联评价方法来构建土壤盐碱化灾害风险评价模型,根据标准自然灾害风险原理,建立土壤盐碱化灾害风险指数计算模型。在松原灌区土壤盐碱化灾害风险评价中的应用表明,灌区各灌片盐碱灾害风险值为0.10～0.36,属于中度风险和重度风险区,风险值由小到大排序为：前郭片、安字片、有字片、龙海片、水字片、大布苏片、潜字片、套浩太片、戎字片、红星片、洪字片。该模型与灌区实情符合较好,客观性较强,表明所建模型可用于土壤盐碱化灾害风险评价。     

黔东南天锦黎地区矿田级金矿定位预测——兼论勘查及研究程度较低地区的矿产预测方法

黔东南天柱-锦屏-黎平地区金矿勘查及研究程度较低,在进行矿产预测时必须有针对性地进行成矿地质背景、成矿规律、物化遥信息、找矿标志、预测要素等专题研究,更多关注成矿地质背景、成矿规律对矿产预测的主导作用,找准影响矿产预测的主要因素,客观适度地赋予物化遥信息对矿产预测的权重。同时,在条件不成熟时可将预测精度降至矿田-矿床级的定位预测,从整体上评价每个金矿田的找矿远景,并对某些部位找到矿床的可能性作进一步评述。采用了多种预测要素权重的简单相加法进行定位预测,而未具体开展基于GIS的定量预测,意在强调地质勘查及研究程度较低地区开展各项专题研究的重要性,并探讨简化矿产预测程序的可行性。经尝试,适宜于该类地区矿田级定位预测的简化流程为：a.相关专题研究;b.预测要素研究及赋值;c.各矿田成矿概率的计算及找矿远景分类;d.各矿田资源潜力评价。通过该方法尝试,该区获得找矿远景区A类4个、B类3个、C类3个。     

气候变化和人类活动对永定河流域径流变化影响定量研究

以永定河流域为研究对象,在对永定河流域1957-2010年降水、实际蒸发和气温实测资料进行趋势分析的基础上,建立SWAT模型,验证了还原径流的必要性,对气候变化和人类活动对永定河流域径流的影响进行了定量研究。结果表明：20世纪60、70年代为永定河流域的丰水期,80年代至今为枯水期。永定河流域80年代后的实测径流资料受气候变化和人类活动影响显著,需进行径流还原后才能保证径流资料的一致性。气候变化是80年代后期径流减少的主要原因,其贡献量约占总减少量的65.4%,人类活动的贡献量占34.6%,也是不容忽视的因素。     

基于ICESat/GLAS数据的中国典型区域SRTM与ASTER GDEM高程精度评价

航天飞机雷达地形测绘(shuttle radar topography mission, SRTM)和先进星载热发射和反射辐射成像仪全球数字高程模型(advanced spaceborne thermal emission and reflection radiometer global digital elevation model, ASTER GDEM)提供了全球覆盖面积最广的数字高程模型(digital elevation model, DEM)数据, 但其高程精度还未得到充分验证, 传统地面测量方法很难适用于验证大面积范围的DEM精度.以冰、云和陆地高程卫星/地学激光测高系统(ICESat/GLAS)高程数据为参考, 综合利用地理信息系统(geographic information system, GIS)空间分析、三维可视化与统计分析方法, 对中国典型低海拔沿海平原地区和高海拔山地的两种DEM数据高程精度进行了对比分析.结果表明, 高程值小于20m的低海拔地区, SRTM高程精度达到2.39m, ASTER GDEM的精度达到4.83m, 均远远高于这两种数据的标称精度; 而在西南山地, 这两种DEM的精度大约为20m, 与标称精度相当.最后, 建立了ICESat/GLAS与SRTM和ASTER GDEM的一元线性回归模型, 该模型具有较高的拟合度和显著线性关系, 可用于改善这两种DEM的高程精度.      

厦门城市空间拓展的生态敏感性评价

在综合分析海湾型城市自然生态与社会生态属性的基础上,选取了高程、坡度、河流水库、植被覆盖、土地覆盖和生态保护区等6个因子,作为生态敏感性评价的指标。另外,借助GIS空间分析单因子评价与多因子加权综合评价方法,研究了生态敏感性程度及其空间分布特征,将厦门的生态敏感性划分为4级:不敏感、较敏感、中敏感和高敏感。综合评价结果表明,厦门市生态敏感性在空间分布上差异显著:高度敏感区占研究区总面积的28.1%,低敏感区和不敏感区分别占研究区总面积的27.9%和33.6%。中度敏感区占的比例较小,仅为10.4%。