Next Article in Journal
Human Papillomavirus Infection and Vaccination: Knowledge and Attitudes among Nursing Students in Italy
Next Article in Special Issue
Spatial and Seasonal Variations in the Abundance of Nitrogen-Transforming Genes and the Microbial Community Structure in Freshwater Lakes with Different Trophic Statuses
Previous Article in Journal
Parent’s Cardiorespiratory Fitness, Body Mass, and Chronic Disease Status Is Associated with Metabolic Syndrome in Young Adults: A Preliminary Study
Open AccessArticle

Comprehensive Eutrophication Assessment Based on Fuzzy Matter Element Model and Monte Carlo-Triangular Fuzzy Numbers Approach

1
Department of Energy and Environment, Southeast University, Nanjing 210096, China
2
School of Glasgow, University of Electronic Science and Technology, Chengdu 610054, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(10), 1769; https://doi.org/10.3390/ijerph16101769
Received: 15 April 2019 / Revised: 16 May 2019 / Accepted: 16 May 2019 / Published: 19 May 2019
(This article belongs to the Special Issue Mechanism and Control Technology of Lake Eutrophication)
Evaluating the eutrophication level of lakes with a single method alone is challenging since uncertain, fuzzy, and complex processes exist in eutrophication evaluations. The parameters selected for assessing eutrophication include chlorophyII-a, chemical oxygen demand, total phosphorus, total nitrogen, and clarity. Firstly, to deal with the uncertainties and fuzziness of data, triangular fuzzy numbers (TFN) were applied to describe the fuzziness of parameters. Secondly, to assess the eutrophication grade of lakes comprehensively, an improved fuzzy matter element (FME) approach was incorporated with TFNs with weights determined by combination of entropy method and analytic hierarchy process (AHP). In addition, the Monte Carlo (MC) approach was applied to easily simulate the arithmetic operations of eutrophication evaluation. The hybrid model of TFN, FME, and MC method is termed as the TFN–MC–FME model, which can provide more valuable information for decision makers. The developed model was applied to assess the eutrophication levels of 24 typical lakes in China. The evaluation indicators were expressed by TFNs input into the FME model to evaluate eutrophication grade. The results of MC simulation supplied quantitative information of possible intervals, the corresponding probabilities, as well as the comprehensive eutrophication levels. The eutrophication grades obtained for most lakes were identical to the results of the other three methods, which proved the correctness of the model. The presented methodology can be employed to process the data uncertainties and fuzziness by stochastically simulating their distribution characteristics, and obtain a better understanding of eutrophication levels. Moreover, the proposed model can also describe the trend of eutrophication development in lakes, and provide more valuable information for lake management authorities. View Full-Text
Keywords: triangle fuzzy number; Monte Carlo approach; fuzzy matter element model; eutrophication evaluation triangle fuzzy number; Monte Carlo approach; fuzzy matter element model; eutrophication evaluation
Show Figures

Figure 1

MDPI and ACS Style

Wang, Y.; Ran, W. Comprehensive Eutrophication Assessment Based on Fuzzy Matter Element Model and Monte Carlo-Triangular Fuzzy Numbers Approach. Int. J. Environ. Res. Public Health 2019, 16, 1769.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop