关于Ramsey模型及其改进的研究和启示

缺水已经成为我国经济发展和社会进步的重要制约因素之一．而对水价的制定到对水资源的利用效率起科十分关键的作用。本文通过对Ramsey模型及其改进的研究．得出如下启示．即实行阶梯水价既有利于实现杜会福利的优化，也可以起到节约水资源的效果。由于阶梯水价机制的设计可以为制度安排、资本进入和市场运行提供更大的弹性空间．因此．本文的政策含义是：在实施阶梯水价的背景下．政府只需对基量水价按边际成本的定价原则来严格规制．从而有效提升水务市场的运行效率。上述举措的优点在于：由于基量水价被严格规制．消费者的基本用水福利可以得到满足；超过基本用水量的水价和再生水价的相对放松规制会鼓励社会资本进入水务行业．使行业运营效率得到提高；国有资本退出水务行业使得政府财政负担减轻，同时．由于放松规制．政府的规制成本也得以降低。最终城市水务行业可以真正做到可持续的发展。     

The effects of sport fishing growth on behavior of commercial fishermen in Balbina reservoir, Amazon, Brazil

An important alternative for sustainable use of tucunaré stocks and improvement in fishermen welfare in Balbina reservoir, Central Amazon, would be to train commercial fisherman to also become tourist guides for sport fishing. In this study, we modeled fishermen response to this question, in order to evaluate the acceptance of such an idea. Thus, we surveyed 47 fishermen, who currently comprise approximately 75% of the total fishermen population. This survey was implemented during December of 2001 and January of 2002. We used a probity analysis to run two models. The first model includes the variables: family size, school level, fishing time, residence time and boat ownership. On the other hand, the second model includes the number of children under and above eight years old but not the family size. Both models are significant and the most relevant variables are: fishing time (years of participation of fisherman is in the activity) and residence time (length of residency of particular fishermen live at the village nearby the reservoir).     

基于GSPA-IAHP模型的油库火灾风险评价

目的对诱发油库火灾的风险进行分析,保障油库系统的安全。方法将区间层次分析法(Interval Analytic Hierarchy Process,IAHP)和广义集对分析法(Generalized Set Pair Analysis,GSPA)相结合,建立GSPA-IAHP模型,构建三级层次结构体系,从原料及工艺、设备设施、管理措施、火源控制方面分析引发油库火灾的风险因素,并运用Matlab软件计算各项评价指标的权重,对各个风险因素进行重要度排序。结果通过分析得出影响油库发生火灾最大的6个风险因素分别是:明火、防火状况、防静电设备、防雷设备、原料危险性、工作人员素质。结论该评价方法对于油库火灾风险的评价具有适用性和有效性,并为后期的油库安全管理提供科学依据。     

基于直觉模糊AHP和灰色关联法的应急避难所选择

为了做好灾害事前应对,需要构建合理的应急避难所选择评价体系。针对传统的选择评价方法在确立权重时未消除主观因素的影响,并且利用TOPSIS方法不能确定评价对象关于优劣方案连线对称的排序等问题,提出基于改进直觉模糊AHP和灰色关联评价模型,首先利用非隶属度最大限度地减少人为偏差,然后利用各个避难所与最优方案的关联度来确定优劣,使得避难所选择最优化,减少资源闲置。通过实例,验证了该方法的合理性和有效性。     

Losses to the environment from the multilevel cycle of anthropogenic lead

As a component of a multi-level study of the anthropogenic lead cycle for year 2000 (52 countries, 8 regions, and the planet), we have estimated the lead flows in seven emission streams: tailings, slag, fabrication and manufacturing, dissipation from use, hibernation, landfilling, and dispersion following product discard. For every 1 kg of lead put into end use, 0.5 kg is lost to the environment, largely due to landfilling and dissipation from use. From the standpoint of the receiving media, 1/3 of the losses are to uncontained solids on land and 48% of the losses are to containment facilities on land. On a country basis, the largest losses occur in the United States and China, which between them are responsible for about 32% of total global lead losses. On a per capita basis, the highest lead losses occurred in the United Kingdom, Belgium-Luxembourg, and Ireland.     

Effects of local fisheries and ocean productivity on the northeastern Ionian Sea ecosystem

To better understand the effects of fisheries and ocean productivity on the northeastern Ionian Sea we constructed an Ecopath with Ecosim model with 22 functional groups. Data on biomass, production/biomass, consumption/biomass, and diet for each group were estimated or extrapolated from the literature. Fisheries landings and discards were also included. Temporal trajectories were simulated using Ecosim. The model was fitted with time-series data for the most important groups from 1964 to 2006. Simulations highlighted a decline of top predators and of most of the commercial species since the late 1970s. The model shows that the decline of fish resources was mainly caused by an intensive fishing pressure that occurred in the area until the end of the 1990s and also by changes in primary production that impacted the trajectories of the main functional groups. In particular, simulated changes through time in PP impacted the abundance trends of all the commercial species, showing a cascade-up effect through the ecosystem. The application of Ecopath with Ecosim was a useful tool for understanding the trends of the main functional groups of the northeastern Ionian Sea. The model underlined that management actions are needed to restore and protect target species including marine mammals, pelagic and demersal fishes. In particular, measures to reduce overfishing, illegal fishing activities and to respect existing legislations are in need. Moreover, the adoption of marine protected areas could be an effective management measure to guarantee prey survival and to sustain marine predators.     

基于线性变换的水质综合评价方法

对于多个因子的水质综合评价存在很多不同方法,尚未形成公认的权威评价方法。因而,对水质综合评价方法进行探索有利于积累研究经验,丰富方法手段。在把数据向[0 1]区间标准化的基础上,通过线性空间变换,把水质样本数据与《地表水环境质量标准》(GB3838-2002)数据转换到同一线性空间。计算水质样本数据向量与5类水质划分等级标准数据向量的欧式距离,把欧式距离的最小值作为水质类别辨别的依据,最终得到水质的综合评价结果。借由已经公开发表的19个断面水质监测数据,运用大型工程计算软件Matlab 2010b进行计算,并与变权欧式距离模型、灰色聚类法、模糊综合指数法和BP神经网络法的评价结果相比较,符合性较好,验证了线性空间变换法应用于水质综合评价的科学性和合理性。方法可用于水质综合评价。在不对污染因子进行加权的情况下,基于线性变换的水质综合评价方法,获得的评价结果较轻。对于被评价为同一类水质的不同监测断面,可以借助"评价单元与5级水质标准的欧式距离矩阵",对评价单元水质差异进一步辨识。     

Quality standard codes of reference of Jordanian coastal waters of the Gulf of Aqaba,Red Sea

Back in 1992, the Gulf of Aqaba Environmental Action Plan (GAEAP), a collaboration between the Aqaba Region Authority (ARA), Jordan and the World Bank, gave considerable emphasis to the environmental protection of the Gulf of Aqaba [The World Bank. Gulf of Aqaba Environmental Action Plan. Report No. 12244JO (1993).]. The document recommended the establishment of a marine reserve and the long term monitoring of the coastal habitats’ environmental quality. The combination of a dedicated follow up, the collaborative efforts of ARA and the Marine Science Station (MSS), and the founding of the Aqaba Special Economic Zone Authority (ASEZA) have turned the recommendations into reality. A comprehensive monitoring program of the Jordanian coastal habitats commenced in 1999. The first three years of the program were financed by a donation from The Global Environmental Facility (GEF). In return, Jordan has committed itself to the maintenance of the monitoring program as an ongoing tool for sustainable coastal management. The monitoring program includes observations on benthic habitat, fish communities, bottom sediments and seawater quality. This paper focuses on the results of seawater-quality monitoring in the first three years. Records of weather conditions, coastal currents, seawater temperature, transparency, salinity, density, pH, alkalinity, dissolved oxygen, ammonia, nitrate, nitrite, phosphate, silicate, particulate matter, chlorophyll a, zooplankton biomass, total coliform, fecal coliform, hydrocarbons and sedimentation rate have been generated monthly since January 1999 at six coastal stations, and one offshore reference station, in the Jordanian waters of the Gulf of Aqaba. The coastal stations are located at sites with different benthic habitats and are occupied by different human activities. Offshore records of density (thermohaline structure), nutrients and chlorophyll a depicted two well-defined seasons; a nutrient-/chlorophyll a-rich, mixed water winter from December to April and a nutrient-/chlorophyll a-poor, stratified water summer from June to October. Short transition seasons appeared in May and November. The mixing and stratification seasons were also clearly depicted in the coastal waters. Statistical analysis of the three-year data collected at the offshore station revealed no significant inter-annual differences in the upper 125 m of the water column with respect to any of the measured parameters. At coastal stations, the water quality at the two northernmost stations was significantly different in comparison to the upper 125 m at the offshore station and to the other coastal stations, with respect to the two key indicator parameters: inorganic nitrogen and chlorophyll a. The three-year findings of the monitoring program are employed to suggest standard codes of reference for the coastal water quality.     

Optimization of an artificial neural network for identifying fishing set positions from VMS data: An example from the Peruvian anchovy purse seine fishery

The spatial behavior of numerous fishing fleets is nowadays well documented thanks to satellite Vessel Monitoring Systems (VMS). Vessel positions are recorded on a frequent and regular basis which opens promising perspectives for improving fishing effort estimation and management. However, no specific information is provided on whether the vessel is fishing or not. To answer that question, existing works on VMS data usually apply simple criteria (e.g. threshold on speed). Those simple criteria generally focus in detecting true positives (a true fishing set detected as a fishing set); conversely, estimation errors are given no attention. For our case study, the Peruvian anchovy fishery, those criteria overestimate the total number of fishing sets by 182%. To overcome this problem an artificial neural network (ANN) approach is presented here. In order to set both the optimal parameterization and use “rules” for this ANN, we perform an extensive sensitivity analysis on the optimization of (1) the internal structure and training algorithm of the ANN and (2) the “rules” used for choosing both the relative size and the composition of the databases (DBs) used for training and inferring with the ANN. The “optimized” ANN greatly improves the estimates of the number and location of fishing events. For our case study, ANN reduces the total estimation error on the number of fishing sets to 1% (in average) and obtains 76% of true positives. This spatially explicit information on effort, provided with error estimation, should greatly reduce misleading interpretations of catch per unit effort and thus significantly improve the adaptive management of fisheries. While fitted on Peruvian anchovy fishery data, this type of neural network approach has wider potential and could be implemented in any fishery relying on both VMS and at-sea observer data. In order to increase the accuracy of the ANN results, we also suggest some criteria for improving sampling design by at-sea observers and VMS data.     

Interactions between cod, herring and sprat in the changing environment of the Baltic Sea: A dynamic model analysis

The interactions between cod (Gadus morhua), herring (Clupea harengus) and sprat (Sprattus sprattus) in the Central Baltic Sea were examined with a simple dynamic model, an alternative to more complicated and data-demanding multispecies and ecosystem models. The main aims of the study were to compare the effect of alternative structures on the model output and examine the control relationships in the fish assemblage under different environmental conditions. The effect of environmental conditions was modelled using a stock-recruitment equation for cod incorporating an environmental index. The model output was especially sensitive to the functional response in predation by cod on herring and sprat. The type II functional response led to a collapse of the clupeid stocks when cod was abundant, while the type III response produced more realistic stock dynamics. According to the simulations, an abundant cod stock was able to keep the sprat stock at a low level, while the herring stock was less affected and benefited from the decreased density of sprat. Simulation of different fishing scenarios indicated that reducing fishing mortality to the level currently advised by ICES would allow the recovery of the cod stock even in unfavourable environmental conditions.