海洋石油污染及其生物修复

文章根据海洋油污染的现状,介绍了海洋石油污染的来源、危害、转归以及对污染的生物修复等内容。指出了限制微生物降解的因素以及如何提高降解效率的措施。生物修复对环境和人类影响小,修复速度快且费用较低,在海洋油污染治理中该方法具有广阔应用前景。     

石油污染海滩的生物修复实践及营养施加策略

介绍了施加营养修复石油污染海滩的3个典型实例。Exxon Valdez溢油生物修复的研究中发现,以藿烷为内标,施加营养的生物降解速率比石油的自然清除速率快将近5倍。美国特拉华州的现场研究结果表明,孔隙水中维持初始N浓度为1~2 mg/L可以使降解率接近最大值;海滩上N的背景浓度很高时,即使不添加任何肥料,石油烃的生物降解也可接近最大值。英国对细颗粒沉积物的生物修复试验结果显示:在被石油污染的区块上施加营养物质使石油降解菌的数量增加了10倍,石油烃相对于藿烷的比值在施加肥料组和控制组中有显著的不同。此外,还对海滩石油污染生物修复过程中孔隙水中的最佳营养浓度、营养的施加频率及方法进行了综述。     

基于生物标志物的海洋溢油污染评价方法研究

生物标志物是指能够指示或表征暴露于环境化学污染物而引起生物机体发生响应变化的标志物或指标。采用生物标志物指示海洋环境的水质变化及其生态预警作用的研究是当今海洋环境科学研究的热点和前沿,在海洋污染评价领域中应用广泛。本文介绍了生物标志物的定义及分类,综述了国内外基于不同种类的生物标志物的评价方法在海洋溢油污染监测与评价中的应用特点和研究现状,以及多种生物标志物综合应用的典型方法及重要意义,例如生物标志物响应指数(biomarker response index,BRI)和综合生物标志物响应指数法(Integrated biomarker responses index,IBR)。最后,本文总结并指出了今后开展相关溢油污染评价的研究方向,包括针对海洋溢油污染特点筛选特异性强、敏感性高的生物标志物以及建立基于生物标志物的海洋溢油污染预警系统等,从而提供更加精准有效的技术方法和科学保障。     

生物标志物在海洋溢油污染评价中的应用

生物标志物是指能够描述或表征生物机体所产生的各种变化的标志物或指标,在海洋污染评价领域具有较好的应用前景。文章详细综述了国内外应用于海洋溢油污染评价的生物标志物类型、特点和研究现状。同时结合海洋开发与管理,提出了目前研究的不足之处,指出了今后开展相关研究的方向,包括针对海洋溢油污染特点筛选特异性强、稳定性好的生物标志物以及基于生物标志物的海上平台石油污染预警系统的建立等。     

生物表面活性剂在海洋溢油生物修复中的应用

生物表面活性剂具有乳化和分散油污且不污染环境等特点,常被用于原油的生物降解过程中.本文概述了生物表面活性剂在海洋溢油生物修复中的应用现状,包括对微生物降解原油的促进作用,与化学表面活性剂促进效果的对比及处理油污染现场时的投加方式,并指出了应用中存在的问题与今后的发展方向.     

海洋石油污染生物修复技术

石油泄漏是海洋环境的重要污染物之一,生物修复技术已逐渐得到广泛应用.本文从海洋石油污染物的来源、转化过程、降解机理和影响生物降解因素等方面,论述了生物技术对泄漏入海的石油类污染物的处理技术经验,以及国内外对于生物修复海洋石油污染取得的成果和存在的问题.     

固定化微生物技术在海洋溢油生物修复中的应用

海洋石油的勘探开发,石油加工产品的生产、使用及排放,海上溢油事故等,使石油成为海洋环境的主要污染物之一。据估计,全世界每年约有1．0×10^10kg的石油进人海洋环境中,中国每年排人海洋的石油达1．15×10^8kg,并且呈逐年增长的趋势[卜列。2010年4月和7月先后发生的墨西哥湾钻井平台漏油事故和大连新港储油码头输...     

海岸线的溢油环境敏感性评价研究进展

海域溢油环境敏感性评价工作是溢油应急规划的基础,有利于溢油事故的应急处理。本文对海岸线的溢油环境敏感型的主要评价方法和选取的评价指标进行了总结;在溢油环境敏感性评价中采用的方法主要包含指数法、层次分析法、德尔菲法、模糊综合评价法等;在研究中,各类方法具有不同特点,多为各种方法同时使用。目前,国内外研究中选取的各类指标可总结归为物理指标、生物指标、社会-经济指标三大类,并且针对部分指标选取的理论依据进行了论述。探讨了较为系统化的评价指标体系的构建。综述了海岸线溢油环境敏感性评价的国内外的主要研究进展。最后指出当前溢油环境敏感性评价中存在的不足,如评价体系系统性差、评价指标科学性低及评价过程主观性强等,而加强学科交叉的同时对目前研究中不足深入研究将是后续的研究重点。     

广东省海岸线整治修复的成效、问题与对策

作为全国大陆海岸线最长的省份,广东高度重视海岸线的整治修复.自2010年以来,全省沿海市县积极申请各类中央、省级财政资金,不断加大海岸线整治修复力度,维护并持续提高了海岸的减灾、生态和旅游功能,促进了海洋自然资源资产的保值增值.然而,项目进行过程中也出现了思想认识不足、统筹规划不足、标准衔接不足、重视投入不足和考核督查...     

表面活性剂在生物修复海洋油污染中的应用及发展

生物修复法是治理海洋油污染的主要途径。它通常采用投加表面活性剂,投加外源微生物以及投加氮磷营养源三种方式,其中投加表面活性剂在应用中存在较大分歧。本文从结构及其作用机理的角度重点探讨了表面活性剂尤其是生物表面活性剂在生物修复海洋油污染中的应用,指出生物表面活性剂的应用是未来主要发展方向,提出其应用方面存在的问题。     

Hindcast of short-term shoreline evolution

A mathematical procedure is described with the aim of estimating short-term shoreline variations. The approach is fully deductive; the procedure being composed of different models that, starting from the atmospheric pressure distribution, evaluate in sequence the wind, current, wave fields, the breaking conditions, the coastal currents and finally the littoral transport. A comparison is made between visual observations of the shoreline evolution and, at one location, the variation of the bottom profile.     

Defining and interpreting shoreline change

Successfully managing the coastal zone requires careful consideration of all the components of shoreline motion. Shoreline movement is a complex phenomenon that is the result of both natural processes and man-made effects. Some of these processes occur over millennia, while others are recent and may be cyclic. Understanding changes to the shore requires both a complete understanding of the underlying processes and an ability to accurately measure the changes. Many uncertainties exist, and predictions must be approached with an understanding of potential errors. Agencies using predictions must exercise caution and be prudent in the application of predictions for management decisions.     

Variability of shore and shoreline evolution

Shore and shoreline evolution both due to natural and human-induced causes or factors can be variable over a wide range of different temporal and/or spatial scales. Our capability to understand and especially predict this variability is still limited. This can lead to misinterpretation of coastal change information, which hampers informed decision making and the subsequent design and implementation of (soft) engineering interventions. Collecting and describing example observations of shore and shoreline variability is one way to support and improve such human intervention. This paper describes causes and factors for the variability and the resulting possible evolutions of wave-dominated shores and shorelines, which are illustrated by a number of case studies. The new element of this work is that the variability is described in terms of a range of different time and space scales, which helps to structure such analysis. However, it is difficult to generalise the results for arbitrary situations, especially on decadal time scales. Scientific and engineering improvements require more quantitative insight into the physical mechanisms behind the free and forced shore behaviour responsible for the variability.     

Forecasting seasonal to multi-year shoreline change

This contribution details a simple empirical model for forecasting shoreline positions at seasonal to interannual time-scales. The one-dimensional (1-D) model is a simplification of a 2-D behavioural-template model proposed by Davidson and Turner (2009). The new model is calibrated and tested using five-years of weekly video-derived shoreline data from the Gold Coast, Australia. The modelling approach first utilises a least-squares methodology to calibrate the empirical model coefficients using the first half of the dataset of observed shoreline movement in response to known forcing by waves. The model is then verified by comparison of hindcast shoreline positions to the second half of the observed shoreline dataset. One thousand synthetic time-series of wave height and period are generated that encapsulate the statistical characteristics of the modelled wave field, retaining the observed seasonal variability and sequencing characteristics. The calibrated model is used in conjunction with the simulated wave time-series to perform Monte Carlo forecasting of the resulting shoreline positions. The ensemble-mean of the 1000 individual five-year shoreline simulations is compared to the unseen shoreline time-series. A simple linear trend forecast of the shoreline position was used as a baseline for assessing the performance of the model. The model performance relative to this baseline prediction was quantified by several objective methods, including cross-correlation (r), root mean square (RMS) error analysis and Brier Skill tests. Importantly, these tests involved no prior knowledge of either the wave forcing or shoreline response. The new forecast model was found to significantly improve shoreline predictions relative to the simple linear trend model, capturing well both the trend and seasonal shoreline variabilities observed at this site. Brier Skill Scores (BSS) indicate that the model forecasts based on unseen data were rated as ‘excellent’ (BSS = 0.83), and root mean square errors were less than 7 m (≈ 14% of the observed variability). The standard deviations of the 1000 individual simulations from ensemble-averaged ‘mean’ forecast were found to provide a useful means of predicting the higher-frequency (individual storm) shoreline variability, with 98% of the observed shoreline data falling within two standard deviations of the forecast position.     

Model study of a shoreline wave-power system

A wave-power system which combines the concept of a breakwater and a harbor resonance chamber was developed in this study. In the caisson chamber, a multi-resonant oscillating water column (MOWC) was formed to push or suck air through the air turbine and thus continuously generated the power. The proposed wave-power system has two aims in mind: one is shore protection and the other is to extract energy from the ocean. To achieve an optimal effect of harbor resonance when excited by incident waves of various periods, a 60° opening of the cylindrical chamber with an entrance section and an arc-shaped curve board in front of the caisson was designed. In order to assess the energy-conversion efficiency and the hydraulic performance, a 1/20 model of this system was constructed and tested in the wave tank under various wave conditions. Our experimental data for the amplification factor of the MOWC agree well with previous theoretical results [Lee, J.J., 1971. Journal of Fluid Mechanics 45, 375–394]. The curve board proves to be useful: it not only broadens the resonant period but also increases the energy-extraction rate. The reflection coefficient was found to be generally low and to decrease with increasing wave height. However, due to the relatively high energy loss of the MOWC, only 28.5% of the incident-wave energy was converted into air energy, indicating that there are still areas for further improvement. In any event, the experimental results provided a clear picture of the energy-transformation process, and demonstrated the preliminary feasibility of this wave-energy device.     

A simple new shoreline change model

A simple new shoreline change model has been developed and calibrated/evaluated with several sets of high quality field data. The model is based upon the general observation that the shoreline tends to approach an equilibrium position exponentially with time when subjected to constant forcing. The model represents the shoreline response to cross-shore processes only and is extremely efficient, requiring only readily obtainable wave and water-level data as input. Shoreline changes are forced by changes in the local water surface elevation due to a combination of local tide, storm surge and wave-induced setup. The model contains three adjustable parameters, representing a baseline condition from which equilibrium shoreline displacements are calculated, and two rate constants, all of which are evaluated by minimizing the error between model hindcasts and several historical shoreline data sets. Several possible forms for the rate parameters, incorporating local wave and sediment properties, were considered and evaluated. At most sites, the model has proven successful in predicting large-scale shoreline response to local water level and wave forcing. The combination of model accuracy and efficiency, along with the minimal data required to drive the model, make it a potentially useful tool in many coastal engineering applications. As more high-quality shoreline, wave and water-level data sets become available, significant improvements can be made in the determination of the rate parameter governing the time scale of the beach response.     

Sub-weekly to interannual variability of a high-energy shoreline

Sixty-one Global Positioning System (GPS), sub-aerial beach surveys were completed at 7 km long Ocean Beach, San Francisco, CA (USA), between April 2004 and March 2009. The five-year time series contains over 1 million beach elevation measurements and documents detailed changes in beach morphology over a variety of spatial, temporal, and physical forcing scales. Results show that seasonal processes dominate at Ocean Beach, with the seasonal increase and decrease in wave height being the primary driver of shoreline change. Storm events, while capable of causing large short-term changes in the shoreline, did not singularly account for a large percentage of the overall observed change. Empirical orthogonal function (EOF) analysis shows that the first two modes account for approximately three-quarters of the variance in the data set and are represented by the seasonal onshore/offshore movement of sediment (60%) and the multi-year trend of shoreline rotation (14%). The longer-term trend of shoreline rotation appears to be related to larger-scale bathymetric change. An EOF-based decomposition technique is developed that is capable of estimating the shoreline position to within one standard deviation of the range of shoreline positions observed at most locations along the beach. The foundation of the model is the observed relationship between the temporal amplitudes of the first EOF mode and seasonally-averaged offshore wave height as well as the linear trend of shoreline rotation. This technique, while not truly predictive because of the requirement of real-time wave data, is useful because it can predict shoreline position to within reasonable confidence given the absence of field data once the model is developed at a particular site.     

江苏辐射沙洲水边线自动提取方法研究

针对不同遥感数据源(TM多光谱、SPOT多光谱及全色波段),对江苏辐射沙洲水边线的自动提取方法进行了研究,形成基于密度分割(TC2分量密度分割、饱和度分量图像密度分割)及基于边缘检测(Canny边缘检测)等2类3种沙洲水边线提取方法。实验表明：(1)上述3种沙洲水边线提取方法在实践中是可行的;(2)通过上述沙洲水边线提取方法,沙洲水边线提取时间大大缩短;(3)由于不受研究者主观影响,水边线提取结果更为准确、客观。     

国际海岸线变化研究进展综述——基于文献计量学方法

以SCIE数据库为基础,基于1024篇文献和VOSviewer(Visualization of Similarities Viewer)文献网络分析软件,运用文献计量学方法分析1970年以来国际海岸线变化研究的发展特征,并结合文献综述方法,归纳海岸线变化研究主要涉及的科学问题及研究热点。研究表明:近50年来,国际上海岸线变化研究文献发文量整体呈上升趋势,主要涉及地球科学、环境科学和自然地理等学科,《Journal of Coastal Research》是此主题最主要的发文期刊;美国及其国内的地质调查局、杜克大学和佛罗里达大学一直引领该领域的研究及其发展,并形成以其为核心的主要合作集群;岸线侵蚀一直是该领域研究的重点问题,遥感和GIS逐渐发展为岸线变化研究的主要手段,海岸线变化的驱动力分析及模拟预测、岸线变化的自然与社会效应以及海岸带综合管理研究成为近年来的研究热点;中国在该领域的研究起步较晚,但发展迅速。本研究对促进我国海岸线变化研究的发展及海岸带综合管理实践有较好的参考和借鉴作用。     

Separation of shoreline change signal from random noise

Investigation of shoreline change signals in the presence of possible non-stationarity is attempted via Karhunen–Loeve filtering to separate the actual shoreline signal change from that of random noise. Interpretation is made of the signal and noise normalized covariance and spectra to help in delineating natural change versus man-made change patterns for a section of shoreline where a navigation channel existed over a portion of the shoreline history.