生态渔业效益综合指标体系的研究

通过对湖北省现行生态渔业系统环境生态结构与功能效益的调查和评价，建立了生态渔业效益综合评价指标体系，为合理培植利用资源，保护生态环境，推进生态渔业经济发展，并对其类型结构不断优化与调控提供了决策参考。     

Violation analysis for solid waste management systems: an interval fuzzy programming approach

This paper introduces a violation analysis approach for the planning of regional solid waste management systems under uncertainty, based on an interval-parameter fuzzy integer programming (IPFIP) model. In this approach, several given levels of tolerable violation for system constraints are permitted. This is realized through a relaxation of the critical constraints using violation variables, such that the model's decision space can be expanded. Thus, solutions from the violation analysis will not necessarily satisfy all of the model's original constraints. Application of the developed methodology to the planning of a waste management system indicates that reasonable solutions can be generated through this approach. Considerable information regarding decisions of facility expansion and waste flow allocation within the waste management system were generated. The modeling results help to generate a number of decision alternatives under various system conditions, allowing for more in-depth analyses of tradeoffs between environmental and economic objectives as well as those between system optimality and reliability.     

COMPUTER-OPTIMIZED STORMWATER TREATMENT (COST) PROGRAM: PHILADELPHIA CASE STUDY1

ABSTRACT: Two computer models, the Continuous Stormwater Pollution Simulation System (CSPSS) and the Computer Optimized Storm-water Treatment Program (COST), were developed to aid in performing water quality planning. This paper describes COST and its site specific applications to the Philadelphia urban area, using the results from an updated CSPSS receiving water simulation. COST provides a planning and conceptual design tool to identify the economically optimum combination of wet weather and dry weather pollution abatement alternatives. Economic analysis procedures incorporated are based on production theory and marginal cost analysis. This study demonstrates that by transforming BOD removal to reduction in low DO events, using CSPSS results, the benefits associated with pollutant removal can be accounted for explicitly by COST simulations. This is important because a pound of BOD removed from combined sewer overflow may be of more benefit to the receiving water than a pound of BOD removed from urban stormwater runoff. The selection of a pollution control strategy is often a difficult decision which should consider social, political, financial, and regulatory factors. It is suggested that such a selection can be based on evaluating the tradeoffs between total annual costs and receiving water improvements, as determined using the COST and CSPSS programs.     

THE EFFECTS OF RISK AND RELIABILITY ON OPTIMAL RESERVOIR DESIGN1

A chance-constrained linear programming model, which utilizes multiple linear decision rules and is useful for river basin planning, is used to evaluate the effects of risk and reliability on optimal reservoir design. Streamflow forecasts or predictions can be explicitly included in the linear program. The risk associated with the predictions is included in the model through the use of cumulative distribution functions (CDF) of streamflows which are conditioned on the predictions. A multiple-purpose reservoir on the Gunpowder River in Maryland is used to illustrate the effectiveness of the model. In order to provide the decision makers with complete and useful information, trade-off curves relating minimum reservoir capacity (a surrogate for dam costs), water supply and flood control targets, and the reliability of achieving the targets are developed. The trade-off curves may enhance the decision maker's ability to select the best dam capacity, considering technological and financial constraints as well as the trade-offs between targets, risks, and costs.     

Cost effective environmental control technology for utilities

On September 24, 1998, new regulations announced by the US EPA require 22 eastern states plus the District of Columbia to develop state implementation plans to reduce ground-level ozone through the reduction of nitrogen oxide (NOx) emissions (Cooper, 1998). This plan calls for a 28% NOx cut in the summer time (1.2 million tons) by 2007. This calls for utilities to develop new, efficient, and robust post-combustion NOx control technologies. A new environmental control technology called low temperature oxidation (LTO) system, which can reduce NOx emissions below measurable levels (i.e. 2 ppm using process analyzers) at low temperature (125-325 °F), was awarded the best available control technology and the lowest available emission reduction technology by the US EPA in April 1998. Ozone is employed to oxidize nitric oxide (NO) to dinitrogen pentoxide (N₂O₅) at a low temperature in an oxidizer, which is then easily absorbed by water in a scrubber. Bench scale and pilot plant tests have shown that the LTO process can almost completely remove the NOx emissions (i.e. NOx emissions are below levels measurable using process analyzers). This proved that the LTO system is an attractive process to meet the stricter NOx regulations. There are multiple benefits of the LTO system besides removal of NOx emissions, includes reduction of SOx and CO emissions, and no secondary air emissions (NH₃, N₂O). In order to obtain minimum NOx emissions, extra ozone needs to be supplied. The cost of the process also increases nonlinearly as emissions decrease. This poses a challenging multiobjective optimization problem where emissions like NOx and SOx need to be minimized, while minimizing the system cost as well as extra ozone. This problem is addressed using a new and efficient multiobjective optimization framework. This framework will provide designs that are cost effective as well as environmentally friendly.     

基于粗糙集——粒子群神经网络的建设项目安全预测研究

回顾施工项目安全管理和安全管理研究现状,建立建设项目安全管理指标体系。利用人工神经网络非线性函数逼近能力,对项目风险因素程度预测。针对该网络当数据量大时,其结构复杂、收敛慢,易陷入局部最优的缺点,引入粗糙集对影响建设项目安全目标的不确定性因素进行约简,找出最小不确定性风险因素集,大大简化网络输入信息的表达空间维数。并结合粒子群算法收敛速度快、全局最优的寻优能力强的优点,建立基于粗糙集——粒子群神经网络的建设项目安全预测系统。通过实例验证该系统的科学性和有效性。     

正压气力除灰系统的优化设计

从气力除灰系统的经济性考虑，按照系统运行能耗最省的原则，对系统进行优化设计。以山东临沂电厂除灰系统为例，优化出灰气比、管径、系统压损、耗气量等技术指标。实际运行效果证明这种优化设计方法是可行的，为该系统的推广应用提供了优化设计依据。     

MULTIPURPOSE OPERATION STUDIES OF A CANAL-LAKE-RIVER SYSTEM-OSWEGO RIVER SYSTEM,NEW YORK1

Use of systems analysis techniques for setting up flow regulation rules for the Oswego River System, a canal-river system with eight lakes, was examined. Two sets of lake regulation rules were proposed: the rule curve for each lake, and the lake-use priority curves for all the lakes. The former specifies balanced allocation of the storage in lakes to conservation pools and flood control pools and, the latter determines lakes releases depending upon the type of operation, the time of the year, and systems objectives. A generalized mathematical representation of the complex, multipurpose, multilake river systems operation is described. With appropriate measures of effectiveness and details of analysis, the problem was then solved with simulation and optimization. Use of the results in assisting basin plan formulation is also discussed.     

区域大气污染总量控制的渐进方法

对污染物实施总量控制是我国当前和今后污染控制和管理的方向。本文对区域大气污染总量控制的一般方法进行了讨论。考虑到污染控制成本和公平性要求 ,采用浓度控制与总量相结合的循序渐进方法 ,并提出了促进环境与经济协调发展的总量控制负荷优化分配模型 ,以期对各地总量控制的实施提供参考和借鉴     

A CRITICAL APPROACH TO THE CALIBRATION OF A WATERSHED MODEL1

ABSTRACT: A complex watershed-scale water quality simulation model, the Hydrological Simulation Program-FORTRAN (HSPF) model, was calibrated for a 16 km² catchment. The simulation step size was 0.33 hours with predicted and recorded hydrologic flows compared on an annual and monthly basis during a total calibration period of four years. Unguided numerical optimization when applied alone did not yield a model parameter set with acceptable predictive capability; instead, it was necessary to apply a critical process that included sensitivity analysis, numerical optimization, and testing of derived model parameter sets to evaluate their performance for periods other than those for which they were determined. Using this critical calibration process, the model was proven to have significant predictive capability. Numerical optimization is an aid for model calibration, but it must not be used blindly.