Full-scale blending treatment of fresh MSWI leachate with municipal wastewater in a wastewater treatment plant

Fresh leachate, generated in municipal solid waste incineration (MSWI) plants, contains various pollutants with extremely high strength organics, which usually requires expensive and complex treatment processes. This study investigated the feasibility of blending treatment of MSWI leachate with municipal wastewater. Fresh MSWI leachate was pretreated by coagulation–flocculation with FeCl₃ 2 g/L and CaO 25 g/L, plate-and-frame filter press, followed by ammonia stripping at pH above 12. After that, blending treatment was carried out in a full-scale municipal wastewater treatment plant (WWTP) for approximately 3 months. Different operational modes consisting of different pretreated leachate and methanol addition levels were tested, and their performances were evaluated. Results showed that throughout the experimental period, monitored parameters in the WWTP effluent, including COD (<60 mg/L), BOD₅ (<20 mg/L), ammonium (<8 mg/L), phosphorus (<1.5 mg/L) and heavy metals, generally complied with the Chinese sewage discharged standard. Under the experimental conditions, a certain amount of methanol was needed to fulfill TN removal. An estimation of the operation cost revealed that the expenditure of blending treatment was much lower than the total costs of respective treatment of MSWI leachate and municipal wastewater. The outcomes indicated that blending treatment could not only improve the treatability of the MSWI leachate, but also reduce the treatment cost of the two different wastewaters.     

Inexact fuzzy-stochastic mixed-integer programming approach for long-term planning of waste management – Part A: Methodology

In this study, an inexact fuzzy chance-constrained two-stage mixed-integer linear programming (IFCTIP) approach is proposed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing inexact two-stage programming and mixed-integer linear programming techniques by incorporating uncertainties expressed as multiple uncertainties of intervals and dual probability distributions within a general optimization framework. The developed method can provide an effective linkage between the predefined environmental policies and the associated economic implications. Four special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties. Firstly, it provides a linkage to predefined policies that have to be respected when a modeling effort is undertaken; secondly, it is useful for tackling uncertainties presented as intervals, probabilities, fuzzy sets and their incorporation; thirdly, it facilitates dynamic analysis for decisions of facility-expansion planning and waste-flow allocation within a multi-facility, multi-period, multi-level, and multi-option context; fourthly, the penalties are exercised with recourse against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised solid waste-generation rates are violated. In a companion paper, the developed method is applied to a real case for the long-term planning of waste management in the City of Regina, Canada.     

Inexact fuzzy-stochastic mixed integer programming approach for long-term planning of waste management–––Part B: Case study

In this study, a solid waste decision-support system was developed for the long-term planning of waste management in the City of Regina, Canada. Interactions among various system components, objectives, and constraints will be analyzed. Issues concerning planning for cost-effective diversion and prolongation of the landfill will be addressed. Decisions of system-capacity expansion and waste allocation within a multi-facility, multi-option, and multi-period context will be obtained. The obtained results would provide useful information and decision-support for the City's solid waste management and planning. In the application, four scenarios are considered. Through the above scenario analyses under different waste-management policies, useful decision support for the City's solid waste managers and decision makers was generated. Analyses for the effects of varied policies (for allowable waste flows to different facilities) under 35 and 50% diversion goals were also undertaken. Tradeoffs among system cost and constraint-violation risk were analyzed.Generally, a policy with lower allowable waste-flow levels corresponded to a lower system cost under advantageous conditions but, at the same time, a higher penalty when such allowances were violated. A policy with higher allowable flow levels corresponded to a higher cost under disadvantageous conditions. The modeling results were useful for (i) scheduling adequate time and capacity for long-term planning of the facility development and/or expansion in the city's waste management system, (ii) adjusting of the existing waste flow allocation patterns to satisfy the city's diversion goal, and (iii) generating of desired policies for managing the city's waste generation, collection and disposal.     

Inexact fuzzy-stochastic constraint-softened programming – A case study for waste management

In this study, an inexact fuzzy-stochastic constraint-softened programming method is developed for municipal solid waste (MSW) management under uncertainty. The developed method can deal with multiple uncertainties presented in terms of fuzzy sets, interval values and random variables. Moreover, a number of violation levels for the system constraints are allowed. This is realized through introduction of violation variables to soften system constraints, such that the model’s decision space can be expanded under demanding conditions. This can help generate a range of decision alternatives under various conditions, allowing in-depth analyses of tradeoffs among economic objective, satisfaction degree, and constraint-violation risk. The developed method is applied to a case study of planning a MSW management system. The uncertain and dynamic information can be incorporated within a multi-layer scenario tree; revised decisions are permitted in each time period based on the realized values of uncertain events. Solutions associated with different satisfaction degree levels have been generated, corresponding to different constraint-violation risks. They are useful for supporting decisions of waste flow allocation and system-capacity expansion within a multistage context.     

The influence of low-dose cadmium on the laryngeal microstructure and ultrastructure of Pelophylax nigromaculata

Environmental Science and Pollution Research - Cadmium (Cd) is one of the common heavy metals dispersed throughout the modern environment that disrupts the development of aquatic organisms....     

广州市环境监测管理信息化建设中若干问题探讨

以广州市环境监测中心站推进信息化的实践为例，重点对环境监测管理信息化规划、开发和应用3个环节所涉及的信息化进程路线、应用系统开发的需求分析和推广应用等问题进行了一些探讨，提出切合自身的解决思路或办法。     

Nitrogen removal performance and bacterial communities in zeolite trickling filter under different influent C/N ratios

Environmental Science and Pollution Research - In this study, the degradation performance of nutrients in zeolite trickling filter (ZTF) with different influent C/N ratios and aeration conditions...     

Revealing the impact of water conservancy projects and urbanization on hydrological cycle based on the distribution of hydrogen and oxygen isotopes in water

Environmental Science and Pollution Research - In recent years, the development and utilization of water resources have imposed great impacts on hydrological characteristics and ecological...