A Study of Risk Analysis and Effluent Trading for Total Mass Control of Water Pollution

• Main Authors: Jen-Huei Li, 李貞憓
• Other Authors: 童慶斌
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/01645977463325134998

碩士 === 國立臺灣大學 === 生物環境系統工程學研究所 === 99 === Sustainable water quality management requires total mass control in pollutant discharge, which aims to meet the needs of economic and social development while considering the principles of not exceeding carrying capacity and equity among generations. The goal of total mass control is to allocate the pollutant load and to control pollutant discharge to satisfy water quality standards based on the water vision and an affordable risk. When some polluters are unable to reduce the pollution to meet the allowable emission or intend to expand economical benefits which will produce more pollutants, they can trade with others according to the effluent trading system. Water quality simulation model is an important tool for the development of total mass control. However, the simulation results are uncertain due to the uncertainty of parameters and data. This study use a method based on the reliability method to assess the risk of violating the water quality standard by representing parameters and data as random variables. And it also estimates the allowable pollutant discharges for a target risk through the inverse reliability method. The mechanism of effluent trading is also discussed in this study, including point-point source trading and point-nonpoint source trading. In the point-point source trading, this study integrates a water quality simulation model with an optimization model to assess river water quality and allowable pollutant discharges. The constraints of the water quality standard and individual polluter would be considered in the optimization model, which is solved via the large-scale system optimization theory. The trading ratio and transaction price of point-point source trading are also evaluated. In point-nonpoint source trading, stochastic programming is used to establish point-nonpoint source trading model because the nonpoint source emission are stochastic and difficult to control. Trading ratio, optimal abatement allocation under trading equilibrium, and total cost saving of point-nonpoint source trading are evaluated. Cases would be designed to explain the above methodologies and model.