An Interval-Parameter Fuzzy-Stochastic Programming Approach for Municipal Solid Waste Management and Planning

In this study, an integrated fuzzy-stochastic linear programming model is developed and applied to municipal solid waste management. Methods of chance-constrained programming and fuzzy linear programming are incorporated within a general interval-parameter mixed-integer linear programming framework. It improves upon the existing optimization methods with advantages in uncertainty reflection, data availability, and computational requirement. The model can be used for answering questions related to types, times and sites of solid waste management practices, with the objective of minimizing system costs over the planning horizon. The model can effectively reflect dynamic, interactive, and uncertain characteristics of municipal waste management systems. In its solution process, the model is transformed into two deterministic submodels, corresponding to upper and lower bounds of the desired objective function values under a given significance level, based on an interactive algorithm. Results of the method's application to a hypothetical case indicate that reasonable outputs have been obtained. It demonstrates the practical applicability of the proposed methodology.     

Deterministic and Stochastic Simulations for Solid Waste Collection Systems – A SWIM Approach

The SWIM model is the first systems model in Australia that deals with integrated waste management systems. The main modelling approach adopted is simulation, which is based on both deterministic and stochastic models for collection systems.These models are described in this paper, after a number of modelling approaches are reviewed. An example of the application of the SWIM model is given, and planned extensions to the SWIM model are briefly outlined.     

A systematic approach for the comparative assessment of stormwater pollutant removal potentials

This paper describes the development of a methodology to theoretically assess the stormwater pollutant removal performances of structural best management practices (BMPs). The method combines the categorisation of the relative importance of the primary removal processes within 15 different BMPs with an evaluation of the ability of each process to remove a pollutant in order to generate a value representing the pollutant removal potential for each BMP. The methodology is demonstrated by applying it separately to a set of general water quality indicators (total suspended solids, biochemical and chemical oxygen demand, nitrates, phosphates and faecal coliforms) to produce a ranked list of BMP pollutant removal efficiencies. Given the limited amount of available monitoring data relating to the differential pollutant removal capabilities of BMPs, the resulting prioritization will support stakeholders in making urban drainage decisions from the perspective of pollutant removal. It can also provide inputs to existing urban hydrology models, which aim to predict the treatment performances of BMPs. The level of resilience of the proposed approach is tested using a sensitivity analysis and the limitations in terms of BMP design and application are discussed.     

Fundamental insights on when social network data are most critical for conservation planning

As declines in biodiversity accelerate, there is an urgent imperative to ensure that every dollar spent on conservation counts toward species protection. Systematic conservation planning is a widely used approach to achieve this, but there is growing concern that it must better integrate the human social dimensions of conservation to be effective. Yet, fundamental insights about when social data are most critical to inform conservation planning decisions are lacking. To address this problem, we derived novel principles to guide strategic investment in social network information for systematic conservation planning. We considered the common conservation problem of identifying which social actors, in a social network, to engage with to incentivize conservation behavior that maximizes the number of species protected. We used simulations of social networks and species distributed across network nodes to identify the optimal state-dependent strategies and the value of social network information. We did this for a range of motif network structures and species distributions and applied the approach to a small-scale fishery in Kenya. The value of social network information depended strongly on both the distribution of species and social network structure. When species distributions were highly nested (i.e., when species-poor sites are subsets of species-rich sites), the value of social network information was almost always low. This suggests that information on how species are distributed across a network is critical for determining whether to invest in collecting social network data. In contrast, the value of social network information was greatest when social networks were highly centralized. Results for the small-scale fishery were consistent with the simulations. Our results suggest that strategic collection of social network data should be prioritized when species distributions are un-nested and when social networks are likely to be centralized.     

Integrating Large Wood Jams into Hydraulic Models: Evaluating a Porous Plate Modeling Method

Large wood (LW) jams are key riverine habitat features that affect hydraulic processes and aquatic habitat. The hydraulic influence of LW jams is poorly understood due to the complexity of fluid dynamics around irregular, porous structures. Here we validated a method for two‐dimensional hydraulic modeling of porous LW jams using the open‐source modeling software Delft3D‐FLOW. We sampled 19 LW jams at three reaches across the Columbia River Basin in the United States. We used computer‐generated porous plates to represent LW jams in the modeling software and calibrated our modeling method by comparing model outputs to measured depths and velocities at validation points. We found that modeling outputs are error‐prone when LW jams are not represented. By representing LW jams as porous plates we reduced average velocity root mean square error (RMSE) values (i.e., improved model accuracy) by 42.8% and reduced average depth RMSE values by 5.2%. These differences impacted habitat suitability index modeling. We found a 15.1% increase in weighted useable area for juvenile steelhead at one test site when LW jams were simulated vs. when they were ignored. We investigated patterns in average RMSE improvements with varying jam size, bankfull obstruction, porosity, and structure type, and river complexity. We also identified research gaps related to field estimation of LW jam porosity and porous structure modeling methods.     

Utilization of UV‐A and UV‐C radiation in advanced oxidation processes with the intention of removing color and organic matter from the gross leachate of a stabilized sanitary landfill

The present work investigated color and biochemical oxygen demand (COD) removal from treated landfill leachate via advanced oxidative processes (AOPs) artificially emitted. The AOP H₂O₂/UV, TiO₂/UV, and photolysis were tested in two bench‐scale photoreactors: The first one with UV‐C lamp and the other with UV‐A lamp associated or not with coagulation / flocculation pretreatment. Crude leachate samples with pH ranging from 8 to 3 were used, and time varied in 30, 45, and 60 minutes. Experiments were performed in two stages: step 1 with a 20 mL volume from each sample and step 2 with repetition of the best results from the previous step, adopting the 150 mL volume. In step 1, the AOP applied in the crude leachate sample showed the best results, standing out H₂O₂/UV‐C with 30 minutes and TiO₂/UV‐A with 60 minutes. In step 2, H₂O₂/UV‐C had a 60% color removal and 25% COD reduction, while TiO₂/UV‐A had a 10% color removal and 20% COD reduction. Therefore, the H₂O₂/UV‐C process was the most efficient, because the complex characteristics of the effluent interfered in the TiO₂/UV‐A efficiency, but it is necessary to eliminate the process interferences. The use of artificial radiation is a viable alternative; however, it can be costly, being relevant in the associations between processes with artificial UV and solar UV, as the natural radiation becomes more attractive and allows the process operating costs reduction.     

Modelling radioactivity in the Irish Sea: From discharge to dose

In order to support authorised discharges of low level radioactive liquid effluent into coastal regions, mathematical models are required to robustly predict radiological impacts on critical groups of current and proposed changes to liquid discharges. The grid model presented here simulates the long term dispersion and transport of radioactivity discharged from the Sellafield site in Cumbria, UK, and the subsequent exposure of critical groups in Cumbria and across the Irish Sea in Northern Ireland. The fine grid of the model allows a good resolution of the seabed sediment distribution. This benefits the predictions for the last decades of low discharge level, when bed sediment can become a source of contamination by bringing back the legacy of past high discharges. This is highlighted by the dose comparison, where the predicted dose to Cumbria critical group follows well the dose estimated from environmental data during the low discharge level period.     

Effect of sorbed and desorbed Zn(Ⅱ) on the growth of a green alga (Chlorella pyrenoidosa)

Toxic effect of Zn(Ⅱ) on a green alga (Chlorella pyrenoidasa) in the presence of sepiolite and kaolinite was investigated.The Zn-free clays were found to have a negative impact on the growth of C.pyrenoidosa in comparison with control samples (without adding any clay or Zn(Ⅱ)).When Zn(Ⅱ) was added,the algae in the presence of clays could be better survived than the control samples,which was actually caused by a decrease in Zn(Ⅱ) concentration in the solution owing to the adsorption of Zn(Ⅱ) on the clays.When the solution system was diluted,the growth of algae could be further inhibited as compared to that in a system which had the same initial Zn(Ⅱ) concentration as in the diluted system.This in fact resulted from desorption of Zn(Ⅱ) from the zinc-contaminated clays,although the effect varied according to the different desorption capabilities of sepiolite and kaolinite.Therefore the adsorption and desorption processes of Zn(Ⅱ) played an important part in its toxicity,and adsorption and desorption of pollutants on soils/sediments should be well considered in natural eco-environmental systems before their risk of toxicity to aquatic organisms was assessed objectively.     

染料废水物理化学脱色技术的现状与进展

本文按吸附,混凝,化学氧化,离子交换,超滤膜等几个方面分别论述了染料废水物理化学脱化技术的现状与发展情况。     

Anaerobic degradation of xenobiotic organic contaminants (XOCs): The role of electron flow and potential enhancing strategies

In groundwater, deep soil layer, sediment, the widespread of xenobiotic organic contaminants (XOCs) have been leading to the concern of human health and eco-environment safety, which calls for a better understanding on the fate and remediation of XOCs in anoxic matrices. In the absence of oxygen, bacteria utilize various oxidized substances, e.g. nitrate, sulphate, metallic (hydr)oxides, humic substance, as terminal electron acceptors (TEAs) to fuel anaerobic XOCs degradation. Although there have been increasing anaerobic biodegradation studies focusing on species identification, degrading pathways, community dynamics, systematic reviews on the underlying mechanism of anaerobic contaminants removal from the perspective of electron flow are limited. In this review, we provide the insight on anaerobic biodegradation from electrons aspect — electron production, transport, and consumption. The mechanism of the coupling between TEAs reduction and pollutants degradation is deconstructed in the level of community, pure culture, and cellular biochemistry. Hereby, relevant strategies to promote anaerobic biodegradation are proposed for guiding to an efficient XOCs bioremediation.