State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361005, China; College of Earth, Ocean and Environment, University of Delaware, Newark, DE 19716, USA.
State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361005, China.
Mar Pollut Bull. 2013 Oct 15;75(1-2):21-27. doi: 10.1016/j.marpolbul.2013.08.023. Epub 2013 Sep 12.
Three optimization methods are employed to allocate Marine Environmental Carrying Capacity (MECC) in the Xiamen Bay. The hydrodynamic and pollutant fields are first simulated by the Princeton Ocean Model. Taking phosphorus as an index of the water quality, the response fields are then calculated. These response fields represent the relationship between the concentration of the sea zone and the pollution sources. Finally, MECC is optimized and distributed in the Xiamen Bay by three optimization methods. The results show classical linear optimization can only maximize the satisfaction level for one of the stake holders', e.g., dischargers or environmental protection bureau, satisfaction level. However, the fuzzy and grey fuzzy optimizations can provide a compromise, and therefore a fairer result, by incorporating the conflicting goals of all of the different stakeholders. Compared with fuzzy optimization, the grey fuzzy optimization provides a more flexible choice for the decision-makers.
三种优化方法被应用于厦门湾海洋环境容量的分配。首先通过普林斯顿海洋模型模拟水动力和污染物场，然后计算响应场。这些响应场代表了海域浓度与污染源之间的关系。最后，通过三种优化方法在厦门湾优化和分配海洋环境容量。结果表明，经典线性优化只能使利益相关者（如排放者或环境保护局）之一的满意度最大化。然而，模糊和灰色模糊优化可以通过纳入所有不同利益相关者的冲突目标，提供一个妥协，从而得到一个更公平的结果。与模糊优化相比，灰色模糊优化为决策者提供了更灵活的选择。
