Wei Sun

Risk assessment of hydropower stations through an integrated fuzzy entropy-weight multiple criteria decision making method

An integrated fuzzy entropy-weight MCDA method is proposed.It is firstly applied to risk assessment of hydraulic projects in the Xiangxi River.It avoids subjective effects on the weights.The comprehensive risk levels of hydropower stations are ranked. An integrated fuzzy entropy-weight multiple criteria decision making (IFEMCDM) method was proposed and applied to risk assessment of hydropower stations in the Xiangxi River. The IFEMCDM integrates the fuzzy set theory, the entropy weight method and the multiple criteria decision making method within a risk assessment framework. It can quantify uncertainties presented in fuzzy sets and assess multi-criteria decision problems in a more objective manner through avoiding subjective effects on the weights. The detailed computational procedures were provided to illustrate the integration process of the above methods. The performance of IFEMCDM was analyzed in terms of relative closeness and α-cut levels. The comprehensive assessment results demonstrated that, all of the ten hydropower stations can be divided into four degree ranges in accordance with the relative closeness. Most of the hydropower stations along the Gaolan River and the Gufu River would have lower risk. Decision makers can conduct flexible and variable response programs for the ten hydropower stations under different α-cut levels. The application of the IFEMCDM revealed its superiority in solving complicated multi-criteria assessment problems more objectively under fuzzy uncertainty. This study was the first application of the IFEMCDM model to risk assessment of hydropower stations, which indicated that it can also be applied to other environmental problems under uncertainties.

Performance of in-vessel composting of food waste in the presence of coal ash and uric acid.

Massive quantities of food waste often coexist with other agroindustrial and industrial waste, which might contain coal ash (CA) and uric acid (UA). This study investigated the influence of CA and UA on the composting of food waste in the in-vessel system. The patterns of food waste composting were compared among various combinations. The results showed that the temperature level was enhanced in the presence of CA and UA during the first 8 days. The significant drop in pH was observed in the treatment without any amendment. But the presence of CA could alleviate the drop of pH. More intensive organic mass reduction took place in the treatments with amended CA and UA in the first half of process. The O(2) uptake rate in the reactor with CA and UA was higher than that with only CA in the early stage. Both thermophilic and mesophilic microorganisms were present throughout the composting period. The populations of both thermophilic and mesophilic microorganisms were influenced when amended with CA and UA. The decreasing trend in C/N ratio was shown in all the reactors, while a relatively lower C/N ratio was obtained in the series with both CA and UA.

Simulation-based inexact chance-constrained nonlinear programming for eutrophication management in the Xiangxi Bay of Three Gorges Reservoir

Although integrated simulation and optimization approaches under stochastic uncertainty have been applied to eutrophication management problems, few studies are reported in eutrophication control planning where multiple formats of uncertainties and nonlinearities are addressed in forms of intervals and probabilistic distributions within an integrated framework. Since the impounding of Three Gorges Reservoir (TGR), China in 2003, the hydraulic conditions and aquatic environment of the Xiangxi Bay (XXB) have changed significantly. The resulting emergence of eutrophication and algal blooms leads to its deteriorated water quality. The XXB becomes an ideal case study area. Thus, a simulation-based inexact chance-constrained nonlinear programming (SICNP) model is developed and applied to eutrophication control planning in the XXB of the TGR under uncertainties. In the SICNP, the wastewater treatment costs for removing total phosphorus (TP) are set as the objective function; effluent discharge standards, stream water quality standards and eutrophication control standards are considered in the constraints; a steady-state simulation model for phosphorus transport and fate is embedded in the environmental standards constraints; the interval programming and chance-constrained approaches are integrated to provide interval decision variables but also the associated risk levels in violating the system constraints. The model results indicate that changes in the violating level (q) will result in different strategy distributions at spatial and temporal scales; the optimal value of cost objective is from [2.74, 13.41] million RMB to [2.25, 13.08] million RMB when q equals from 0.01 to 0.25; the required TP treatment efficiency for the Baisha plant is the most stringent, which is followed by the Xiakou Town and the Zhaojun Town, while the requirement for the Pingyikou cement plant is the least stringent. The model results are useful for making optimal policies on eutrophication control planning and water quality improvement in the XXB.

Inexact joint-probabilistic chance-constrained programming with left-hand-side randomness: An application to solid waste management

In practical waste management systems, amounts of waste transported and treated are not always equal on a daily basis. To distinguish between these two kinds of amounts and reflect their random relationships effectively, an inexact joint-probabilistic left-hand-side chance-constrained programming (IJLCP) method was developed and applied to a municipal solid waste management problem under dual uncertainties. Dual uncertainties are defined as two kinds of uncertainties existing in the same programming model. Improving upon conventional right-hand-side chance-constrained programming, the IJLCP can not only reflect uncertainties presented in terms of interval parameters (unit transportation/treatment costs, capacities of waste treatment facilities, waste generation rates, waste transportation/treatment amounts and so on) and left-hand-side random variables (the relationship between waste transportation and treatment amounts), but also examine the reliability of satisfying (or risk of violating) the entire system constraints. A non-equivalent but sufficient linearization form of IJLCP for solving this type of problem was proposed and proved in a straightforward manner. The performance of IJLCP was analyzed under scenarios at joint and individual probabilities and compared with the corresponding internal-parameter programming model. The results indicated that the net system costs would both decrease with increasing joint probability levels and decrease slightly at different individual probabilities with the same joint probabilities. The two types of dual uncertainties were discussed as well.

Quantitative effects of composting state variables on C/N ratio through GA-aided multivariate analysis

It is widely known that variation of the C/N ratio is dependent on many state variables during composting processes. This study attempted to develop a genetic algorithm aided stepwise cluster analysis (GASCA) method to describe the nonlinear relationships between the selected state variables and the C/N ratio in food waste composting. The experimental data from six bench-scale composting reactors were used to demonstrate the applicability of GASCA. Within the GASCA framework, GA searched optimal sets of both specified state variables and SCAs internal parameters; SCA established statistical nonlinear relationships between state variables and the C/N ratio; to avoid unnecessary and time-consuming calculation, a proxy table was introduced to save around 70% computational efforts. The obtained GASCA cluster trees had smaller sizes and higher prediction accuracy than the conventional SCA trees. Based on the optimal GASCA tree, the effects of the GA-selected state variables on the C/N ratio were ranged in a descending order as: NH₄+-N concentration>Moisture content>Ash Content>Mean Temperature>Mesophilic bacteria biomass. Such a rank implied that the variation of ammonium nitrogen concentration, the associated temperature and the moisture conditions, the total loss of both organic matters and available mineral constituents, and the mesophilic bacteria activity, were critical factors affecting the C/N ratio during the investigated food waste composting. This first application of GASCA to composting modelling indicated that more direct search algorithms could be coupled with SCA or other multivariate analysis methods to analyze complicated relationships during composting and many other environmental processes.

Multi-objective ecological reservoir operation based on water quality response models and improved genetic algorithm

This study proposes a self-adaptive GA-aided multi-objective ecological reservoir operation model (SMEROM) and applies it to water quality management in the Xiangxi River near to the Three Gorges Reservoir, China. The SMEROM integrates statistical water quality models, multi-objective reservoir operations, and a self-adaptive GA within a general framework. Among them, the statistical water quality models of the Xiangxi River are formulated to deal with the relationships between reservoir operation and water quality, which are embedded in constraints of the SMEROM. The multiple objective functions, including maximizing hydropower generation, minimizing loss of flood control, minimizing rate of flood risk, maximizing the average remaining capacity of flood control and maximizing the benefit of shipping, are considered simultaneously to obtain comprehensive benefit among the environment, society and economy. The weighting method is employed to convert the multiple objectives to a single objective. To solve the complex SMEROM, an improved self-adaptive GA is employed through incorporating simulated binary crossover and self-adaptive mutation. To demonstrate the advantage of the developed SMEROM model, the solutions through ecological reservoir operation are compared with those through the traditional reservoir operation and the practical operation in 2011, in terms of water quality, reservoir operation and objective function values. The results show that most of benefit in the ecological operation is better than that in the traditional or practical operations except for the hydropower benefit and loss benefit of flood control. This is because flood control and environmental protection are reasonably considered in the ecological operation.

Waste management under multiple complexities: inexact piecewise-linearization-based fuzzy flexible programming.

To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerance intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFPs advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFPs solutions demonstrate its effectiveness for providing more satisfactory interval solutions than IPFP3. Following its first application to waste management, the IPFP can be potentially applied to other environmental problems under multiple complexities.

A scenario-based modeling approach for emergency evacuation management and risk analysis under multiple uncertainties

Nuclear emergency evacuation is important to prevent radioactive harms by hazardous materials and to limit the accidents consequences; however, uncertainties are involved in the components and processes of such a management system. In the study, an interval-parameter joint-probabilistic integer programming (IJIP) method is developed for emergency evacuation management under uncertainties. Optimization techniques of interval-parameter programming (IPP) and joint-probabilistic constrained (JPC) programming are incorporated into an integer linear programming framework, so that the approach can deal with uncertainties expressed as joint probability and interval values. The IJIP method can schedule the optimal routes to guarantee the maximum population evacuated away from the effected zone during a finite time. Furthermore, it can also facilitate post optimization analysis to enhance robustness in controlling system violation risk imposed on the joint-probabilistic constraints. The developed method has been applied to a case study of nuclear emergency management; meanwhile, a number of scenarios under different system conditions have been analyzed. It is indicated that the solutions are useful for evacuation management practices. The result of the IJIP method can not only help to raise the capability of disaster responses in a systematic manner, but also provide an insight into complex relationships among evacuation planning, resources utilizations, policy requirements and system risks.

Detection of phenylhydrazine based on lectin-glycoenzyme multilayer-film modified biosensor

A novel inhibition-based amperometric biosensor of horseradish peroxidase (HRP) for phenylhydrazine detection is described. The multilayer-film modified sensor is prepared by a layer-by-layer deposition of concanavalin A (Con A) and HRP on glassy carbon electrode (GCE), which is forced by the bioaffinity between Con A and mannose residues on the surface of HRP molecule. Hydroquinone is chosen as electron mediator in the system. The performance of the sensor and the optimum experimental conditions are studied. The lower detection limit of the inhibition-based sensor for phenylhydrazine is 1.7u2009×u200910−6u2009M, and the linear response range is divided into two parts, one of which is 1.7u2009×u200910−6 to 1.07u2009×u200910−5u2009M, and the other 1.07u2009×u200910−5 to 6.98u2009×u200910−5u2009M. The HRP sensor can be reactivated after inhibition and remains more than 91% activity after half a month of frequent running. Interference from phenol, aniline, hydroxylamine, Hg(II), Cd(II) and Bi(III) is found to be minimal, while a high concentration of hydrazine anhydrous, methylhydrazine and 1,1-dimethylhydrazine may interfere with the determination of trace phenylhydrazine. The sensor has been used in phenylhydrazine determination in water of Xiangjiang River.

Inexact quadratic joint-probabilistic programming for water quality management under uncertainty in the Xiangxi River, China

An inexact quadratic joint-probabilistic programming model for water quality management (IQJWQ) is developed and applied to supporting multiple-point-source waste reduction in the Xiangxi River, China. The IQJWQ is a hybrid of interval quadratic programming, joint probabilistic programming and multi-segment water quality simulation. It has advantages in reflecting uncertainties expressed as joint probabilities of system risk, probability distributions of water quality standards, interval parameters and nonlinearities in the objective function. An interactive and derivative algorithm is employed for solving the IQJWQ model. The results indicate that the Pingyikou chemical plant and Liucaopo chemical plant contribute more to pollution of the main stream in the Xiangxi River, which should be the prior plants to reduce the wastewater discharge and enhance the wastewater treatment efficiencies. Meanwhile, the environmental agencies should choose the joint probability carefully to balance the tradeoff between production development and pollution control. Compared with the conventional chance-constrained programming method, the IQJWQ exhibits an increased robustness in handling the overall system risk in the optimization process. Although this study is the first application of the IQJWQ to water quality management, the proposed methods in the IQJWQ can also be applicable to many other environmental management problems under uncertainty.