Eutrophication Assessment Based on the Cloud Matter Element Model

An innovative method based on Gaussian cloud distribution and sample information richness for eutrophication assessment of Yangtze's lakes and reservoirs under uncertainty

The precise assessment of a water body's eutrophication status is essential for making informed decisions in water environment management. However, conventional approaches frequently fail to consider the randomness, fuzziness, and inherent hidden information of water quality indicators. These would result in an unreliable assessment. An enhanced method was proposed for the eutrophication assessment under uncertainty in this study. The multi-dimension gaussian cloud distribution was introduced to capture the randomness and fuzziness. The Shannon entropy based on various sample size and trophic levels was proposed to maximize valuable information hidden in the datasets. Twenty-seven significant lakes and reservoirs located in the Yangtze River Basin were selected to demonstrate the proposed method. The sensitivity and consistency were used to evaluate the accuracy of the proposed method. Results indicate that the proposed method has the capability to effectively assess the eutrophication status of lakes and reservoirs under uncertainty and that it has a better sensitivity since it can identify more than 33-50% trophic levels compared to the traditional methods. Further scenario experiments analysis revealed that the sample information richness, i.e., sample size and the number of trophic levels is of great significance to the accuracy/robustness of the method. Moreover, a sample size of 60 can offer the most favorable balance between accuracy/robustness and the monitoring expenses. These findings are crucial to optimizing the eutrophication assessment.

Variability of the trophic state in a coastal reef system associated with submarine groundwater discharge in the Mexican Caribbean

Submarine groundwater discharges (SGD) have been associated with important sources of nutrients between the land and oceans that can generate eutrophication conditions. This study aims to analyze the behavior of nitrogen and phosphorus using the mixing curve method, to examine the variation of the trophic state using the Karydis Index, and to evaluate the δ15N in benthic organisms to trace the origin of nitrogen in neap tide (November) and spring tide (January) in the Manatí Cenote, and Nohoch-Teek reef lagoon in the Mexican Caribbean. Nitrogen and phosphate enrichment was in the Manatí Cenote during neap and spring tides. This enrichment was particularly noticeable in the reef lagoon during low tides in the areas influenced by SGD. In the Cenote, differences in the nitrate trophic state were observed, indicating an eu-mesotrophic condition during neap tide and a mesotrophic condition during spring tide. However, no significant differences were observed for ammonium (oligo-mesotrophic), nitrites, or phosphate compounds (oligotrophic). The trophic state reef lagoon exhibited a similar pattern but with different spatial variations. In both systems, phosphorus was a limiting nutrient, while δ15N suggested anthropogenic nitrogen uptake by several benthic organisms.

Safety Risk Assessment of Air Traffic Control System Based on the Game Theory and the Cloud Matter Element Analysis

With the ever-increasing demand for air traffic over the years, safety risk assessment has become significant in maintaining the operational safety of the air transport system for long-term development towards sustainability. This paper conducts a safety risk assessment of the air traffic control (ATC) system based on game theory and cloud matter element analysis. The safety risk of the ATC system is evaluated from four aspects, including human, machine, environment, and management. The Nash equilibrium is introduced from game theory to weigh the indicators. The cloud matter element assessment adopts the cloud model from fuzzy sets and probability theory to replace the certain value in conventional matter element theory, which takes the randomness, ambiguity, and incompatibility of the indicators into consideration. In this sense, the safety risk level of the ATC system can be evaluated by calculating the correlation degree of the standard cloud matter element between the indicators and the risks. This paper expands the research scope by introducing and combing game theory and cloud matter element analysis. Furthermore, the applicability and the robustness of the method are examined with a case study of the ATC system, which enriches the existing literature and points out the direction for future work.

BIM-Based Green Hospital Building Performance Pre-Evaluation: A Case Study

With ecological problems and energy crises intensifying today, greening is essential to sustainable development. Compared with other types of buildings, hospital buildings account for a relatively larger proportion of building energy consumption. In order to realize the rapid cycle optimization of a green hospital project in the design stage and improve the green grade of the building, a pre-evaluation Building Information Model (BIM) of green hospital building performance was established in this study. Firstly, the literature review and expert consultation established the building performance pre-evaluation index system for green hospitals. Then, BIM technology is taken to extract data needed for building a performance pre-evaluation system, and the Cloud Model and the Matter–Element Extension Theory are used to build models. The final green grade calculation is realized in MATLAB. Finally, the Maluan Bay Hospital is taken as an example to test the applicability and effectiveness of the proposed model. The results show that the green hospital building performance pre-evaluation model has advantages of simulation, cyclic optimization and fuzzy quantification, which can effectively guide the design and construction of a green hospital.

A Critical Review of Methods for Analyzing Freshwater Eutrophication

Water eutrophication is a global environmental problem that poses serious threats to aquatic ecosystems and human health. The evaluation of eutrophication provides a theoretical basis and technical guidance for the management and rehabilitation of water ecosystems. In the last four decades, dozens of evaluation methods have been applied to freshwater eutrophication, but there is a clear need to optimize and standardize the most suitable methods. We have addressed this gap by presenting a systematic review of methodologies. Due to the diversity and complexity of water bodies, no single evaluation method was identified that would adequately represent eutrophication under all scenarios. We demonstrate that lakes can best be assessed using the trophic level index (TLI) method, reservoirs and wetlands the trophic state index (TSI) and fuzzy comprehensive evaluation (FCE) method, respectively, and rivers the FCE method or back propagation (BP) neural network methods. More recently applied methodologies including spectral imaging and 3-D mapping of water quality using underwater gliders allow greater resolution and can be effective in managing waterbodies to avoid future eutrophication. The aim of this review is to guide future studies on the most appropriate methods available for assessing and reporting water eutrophication.