Adaptation and application of the fuzzy synthetic evaluation (FSE) method for characterizing the trophic state of tropical semiarid reservoirs.

Eutrophication is a recurrent problem in water bodies, especially in tropical semiarid reservoirs. The trophic state index (TSI) is an important tool for the environmental management of aquatic systems. However, determining the TSI involves uncertainties that can affect decision-making. This study aimed to adapt and apply the fuzzy synthetic evaluation (FSE) to characterize the TSI considering the uncertainties of the reference eutrophication classification system. The Castanhão reservoir, the largest in the State of Ceará, Brazil, was taken as a case study. The results showed that (i) the uncertainty of the trophic classification system can be characterized by the triangular and trapezoidal membership functions; (ii) the result matrix associates the global trophic level with a degree of certainty, providing greater confidence to the decision maker; (iii) the eutrophication index (EI) is not an adequate tool for hierarchizing the trophic degree; and (iv) the membership level of the global trophic state generated by the FSE method is a suitable alternative to the EI. It is concluded that the proposed FSE model can be a useful tool for improving water resources management, especially in drylands.

Integrated probabilistic-fuzzy synthetic evaluation of drinking water quality in rural and remote communities.

An integrated probabilistic-fuzzy synthetic evaluation (PFSE) approach was developed for assessing drinking water quality in rural and remote communities (RRCs) through the lens of health risks and aesthetic impacts. The probabilistic health risk assessment can handle aleatory uncertainty raised by the variation of contaminant concentrations, and fuzzy synthetic evaluation (FSE) can address vagueness and ambiguity in human perception of risks and aesthetic impacts. The PFSE approach was applied to five RRCs in British Columbia, Canada where different drinking water quality issues, including high metal(loids) concentrations, the presence of coliforms, and poor aesthetics were reported. Cancer, non-cancer, and microbial risks assessed, as well as both quantitative and qualitative aesthetic impact assessment outcomes, were aggregated into synthetic water quality indices for water quality ranking. The probabilistic health risk assessment results revealed significant health risks for a community with relatively high arsenic concentrations (mean value = 7.0 µg/L) in the water supply. The microbial risks were also found significant (disability-adjusted life years >1 × 10-6) for all communities because of the presence of coliforms in the water. The FSE results indicated that the drinking water quality of five RRCs was associated with high aggregated impacts, which concurred with the "poor" water quality ratings according to the Canadian Water Quality Index. The water quality of the five RRCs was ranked based on the synthetic water quality evaluation indices. The PFSE approach can help decision-makers prioritize RRCs in effective resource allocation for addressing drinking water quality issues.

Contamination characteristics, source analysis and health risk assessment of heavy metals in the soil in Shi River Basin in China based on high density sampling.

To explore the contamination of heavy metals in the Shi River Basin soil in China, a high density sampling of surface soil was conducted. In this study, an absolute principal component scores multiple linear regression model (APCS-MLR) was used to identify the sources of heavy metals in the soil and quantify their amounts. The methods to assess the heavy metals included a fuzzy synthetic evaluation, index and health risk assessment. The results show that heavy metals are relatively rich southwest of the study area. Their levels may be affected by natural sources, such as parent materials. The pollution caused by human factors cannot be ignored, and it is primarily influenced by traffic emissions and processing sources, which contribute 62.6%, followed by agricultural sources, such as pesticides and fertilizers, that contribute 21.1%. The risk assessment indicated that the study area was slightly to moderately polluted. All heavy metals pose higher carcinogenic and other health risks to children than adults, and ingestion is the main way that these pollutants enter the body. The carcinogenic risk of children owing to Cr from natural sources merits further study, while the carcinogenic risk to adults and the non-carcinogenic risk to both adults and children are at acceptable levels. Transportation and industrial processing sources are the main cause of the non-carcinogenic risk. The results could provide reference for reducing heavy metal pollution in the soil.

Fast eutrophication assessment for stormwater wet detention ponds via fuzzy probit regression analysis under uncertainty.

Stormwater wet detention ponds have been a commonly employed best management practice for stormwater management throughout the world for many years. In the past, the trophic state index values have been used to evaluate seasonal changes in water quality and rank lakes within a region or between several regions; yet, to date, there is no similar index for stormwater wet detention ponds. This study aimed to develop a new multivariate trophic state index (MTSI) suitable for conducting a rapid eutrophication assessment of stormwater wet detention ponds under uncertainty with respect to three typical physical and chemical properties. Six stormwater wet detention ponds in Florida were selected for demonstration of the new MTSI with respect to total phosphorus (TP), total nitrogen (TN), and Secchi disk depth (SDD) as cognitive assessment metrics to sense eutrophication potential collectively and inform the environmental impact holistically. Due to the involvement of multiple endogenous variables (i.e., TN, TP, and SDD) for the eutrophication assessment simultaneously under uncertainty, fuzzy synthetic evaluation was applied to first standardize and synchronize the sources of uncertainty in the decision analysis. The ordered probit regression model was then formulated for assessment based on the concept of MTSI with the inputs from the fuzzy synthetic evaluation. It is indicative that the severe eutrophication condition is present during fall, which might be due to frequent heavy summer storm events contributing to high-nutrient inputs in these six ponds.

Evaluation of the optimal quantity of in-vehicle information icons using a fuzzy synthetic evaluation model in a driving simulator.

In-Vehicle Information (IVI) features such as navigation assistance play an important role in the travel of drivers around the world. Frequent use of IVI, however, can easily increase the cognitive load of drivers. The interface design, especially the quantity of icons presented to the driver such as those for navigation, music, and phone calls, has not been fully researched. To determine the optimal number of icons, a systematic evaluation of the IVI Human Machine Interface (HMI) was examined using single-factor and multivariate analytical methods in a driving simulator. When one-way ANOVA was performed, the results showed that the 3-icon design scored best in subjective driver assessment, and the 4-icon design was best in the steering wheel angle. However, when a new method of analyzing the data that enabled a simultaneous accounting of changes observed in the dependent measures, 3 icons had the highest score (that is, revealed the overall best performance). This method is referred to as the fuzzy synthetic evaluation model (FSE). It represents the first use of it in an assessment of the HMI design of IVI. The findings also suggest that FSE will be applicable to various other HMI design problems.

Selection of green remediation alternatives for chemical industrial sites: An integrated life cycle assessment and fuzzy synthetic evaluation approach.

The concept of green site remediation calls for a model that can consider environmental impacts in the selection of site remediation alternatives. In this study, an integrated life cycle assessment (LCA)-fuzzy synthetic evaluation (FSE) model is developed to help practitioners select the optimal site remediation plan by incorporating life cycle impacts into the comprehensive suitability evaluation. The LCA module quantifies environmental and economic impacts using ReCiPe and Input-Output LCA methods, respectively. The impacts are evaluated along with other suitability considerations, presented in 32 indicators under ten criteria, by practitioners through a questionnaire survey. FSE is used to process the collected subjective judgments and generate a suitability index for informed selection. The integrated model is applied to a case study of an abandoned chemical industrial site contaminated by various organic chemicals and mercury. Four remediation alternatives, designed as the combined uses of ex-situ thermal desorption, in-situ thermal desorption, and in-situ containment, are evaluated. The LCA results show that the alternative with extensive use (treating 93.8 % of the contaminated soil) of in-situ thermal desorption is associated with the highest environmental and economic impacts, followed by the alternative with less extensive use (6.2 %) of in-situ thermal desorption. The FSE results show that the economic, technical, and environmental impact considerations are the top three important criteria. The integrated LCA-FSE results indicate that the alternative with mixed use of ex-situ thermal desorption and in-situ containment could be the optimal plan. Excluding LCA results could alter the suitability ranks of the alternatives.

Fuzzy synthetic evaluation of the impact of plant growth regulators on the root phenotype traits of rice seedlings under thiocyanate stress.

Application of plant growth regulators (PGRs) is a novel strategy for allay of the adverse effects caused by biotic/abiotic stresses. However, no studies have vividly executed mathematic evaluation for the assessment of various PGRs on root phenotype traits (RPTs) against pollutants. In the present study, a microcosm hydroponic experiment was conducted to examine responses of RPTs under SCN- (0, 24, 96, and 300 mg SCN/L) stress in the presence of PGRs such as jasmonic acid (JA), indole-3-acetic acid (IAA), and sodium hydrosulfide (NaHS) in rice plants. Fuzzy synthetic evaluation was applied to determine the outcome of the effects of various PGRs on the RPTs under SCN- exposure. Root scanning results indicated that exogenous IAA and NaHS has the greater potential for improving the RPTs of rice seedlings under SCN- stress, while JA failed to uplift the RPTs in response to SCN- stress. Fuzzy synthetic evaluation indicated that in control plants (without SCN-), the effect of three PGRs applied on the RPTs is as follows: NaHS > IAA > JA. At 24 mg SCN/L, NaHS and IAA had consistent actuate in regulating RPTs of rice seedlings, while all PGRs amended have an affirmative impact on RPTs at 96 and 300 mg SCN/L. The present research highlights the utilization of contemporary mathematic method to screen the superior species of PGRs through the RPTs test of plants under pollutant belt.

Fuzzy synthetic evaluation and health risk assessment quantification of heavy metals in Zhangye agricultural soil from the perspective of sources.

Heavy metals in agricultural soil receive much attention because they are easily absorbed by crop into the ecosystem. Managing the discharge of heavy metals from the source is an effective way to prevent and control heavy metals pollution. Grouped principal component analysis (GPCA) and Positive Matrix Factorization (PMF) receptor models were utilized in this study to conduct source apportionment, and the former was optimal because of the accuracy of predicting. Based on the source contribution by GPCA/APCS, heavy metals were evaluated by fuzzy synthetic evaluation model and health risk assessment model. The results of source apportionment showed that heavy metals in Zhangye agricultural soil were mainly affected by steel industry, traffic, agrochemicals, manures, mining activities, leather industry and metal processing industry source. Fuzzy synthetic evaluation showed that the pollution levels of Chromium (Cr) derived by leather industry and metal processing industry and Nickel (Ni) derived by steel industry and traffic source were higher. Health risk assessment revealed that the non-carcinogenic and carcinogenic risks of Cr derived by leather industry and metal processing industry and Lead (Pb) derived by steel industry and traffic source were higher.

Risk assessment based on fuzzy synthetic evaluation method.

The IPCC fifth assessment report envisions risk of climate-related impacts as an outcome of the interaction of climate-related hazards with the vulnerability and the exposure of human and natural systems. This approach relies heavily on human perception, via expert opinions. As experts decide appropriate placement of an indicator in any of the exposure, sensitivity or adaptive capacity domains, several risk maps can potentially be created for the same study area. There is thus some degree of uncertainty in selecting the most appropriate and representative risk map from the several alternatives created by IPCC methods. On the other hand, Fuzzy Synthetic Evaluation (FSE) method, when used to assess risk, can handle this uncertainty much better, as there is no need to distribute indicators among different domains. In FSE, a specific indicator can either increase (positive sign) or decrease (negative sign) a risk, following a simple binary logic. This does not require any expert opinion and thus is free from subjective perception. In this study, risk maps are generated and compared by applying FSE method and two IPCC methods, as outlined in the third and fifth assessments (TAR and AR5). A variant of AR5 risk map is created by interchanging one indicator from the exposure domain to the sensitivity domain. It is found that risk zones are created with statistically significant difference when different IPCC methods are applied. This makes it uncertain to judge a specific risk map by a specific IPCC method as a true risk map. This uncertainty does not exist in FSE method as there is only one risk map where indicators are placed with certainty by following a simple binary logic for a known hazard domain. Hence, this risk map may be considered as the true risk map for the given set of indicators.

Research and application of a hybrid model based on dynamic fuzzy synthetic evaluation for establishing air quality forecasting and early warning system: A case study in China.

As the atmospheric environment pollution has been becoming more and more serious in China, it is highly desirable to develop a scientific and effective early warning system that plays a great significant role in analyzing and monitoring air quality. However, establishing a robust early warning system for warning the public in advance and ameliorating air quality is not only an extremely challenging task but also a public concerned problem for human health. Most previous studies are focused on improving the prediction accuracy, which usually ignore the significance of uncertainty information and comprehensive evaluation concerning air pollutants. Therefore, in this paper a novel robust early warning system was successfully developed, which consists of three modules: evaluation module, forecasting module and characteristics estimating module. In this system, a new dynamic fuzzy synthetic evaluation is proposed and applied to determine air quality levels and primary pollutants, which can be regarded as the research objectives; Moreover, to further mine and analyze the characteristics of air pollutants, four different distribution functions and interval forecasting method are also employed that can not only provide predictive range, confidence level and the other uncertain information of the pollutants future values, but also assist decision-makers in reducing and controlling the emissions of atmospheric pollutants. Case studies utilizing hourly PM2.5, PM10 and SO2 data collected from Tianjin and Shanghai in China are applied as illustrative examples to estimate the effectiveness and efficiency of the proposed system. Experimental results obviously indicated that the developed novel early warning system is much suitable for analyzing and monitoring air pollution, which can also add a novel viable option for decision-makers.