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Comparison of Neuro-Fuzzy networks and Fuzzy Logic Models in groundwater pollution risk assessment
No full textHierarchical classification of groundwater pollution risk of contaminated sites using fuzzy logic: A case study in the Basilicata region (Italy)
No full textGroundwater is an important source of water. Since the control and removal of pollution are expensive, it is essential to identify the possible sources of contamination and to correctly classify groundwater on the basis of its intrinsic and integrated vulnerability. In the last years, many fuzzy models have been developed. There is a lack, however, of studies concerning the application of fuzzy logic for the assessment of the susceptibility of groundwater quality to anthropogenic activities and comparing these methods with traditional methods. The fuzzy model described in this paper assesses the aquifer integrated environmental vulnerability connected to the presence of illegal dumpsites and allows us to hierarchically classify them within a hazard scale. The results allowed us to carry out a comparison of the proposed fuzzy method with a traditional method. The fuzzy method proved to be a useful and objective tool for environmental planning
Application of fuzzy logic and sensitivity analysis for soil contamination hazard classification
No full textThe present article is aimed at illustrating a methodology for a rapid and effective assessment of pollution hazard connected with the presence of uncontrolled landfills. In particular, by means of a fuzzy approach,
the criterion adopted allowed a comparison of the results obtained from a cross analysis of some intrinsic characteristics of the single landfills and the territory where they are located. Their identification shows
the most relevant environmental problem. Therefore, we have classified each site within a hazard scale enabling us to understand which one requires to be checked more urgently, to do instrumental surveys
and, if needed, to do restoration and reclamation. Moreover, the sensitivity analysis we carried out allowed us to identify which is the best membership function belonging and which is the best defuzzification method. That is, in particular, the trapezoidal function and the centroid method. The proposed fuzzy approach, supported by the sensitivity analysis, has revealed to be an important tool for supporting decisions, in order to optimise technical and economic resources
Fuzzy logic and sensitivity analysis for the classification of groundwater pollution risk
No full textThe work described in the present article aims at supplying an environmental planning tool able to define a groundwater risk hierarchy index in function of some intrinsic characteristics of uncontrolled landfills and the territory where they are located. The risk assessment was carried out with a conceptual model, which includes the groundwater vulnerability and the intrinsic hazard of landfills. In particular, in order to define the hazard of landfills, the fuzzy logic theory has been applied. The fuzzy approach has been then combined with the sensitivity analysis in order to overcome the problem of uncertainty associated with both the input data and the implemented fuzzy model, and at the same time to reduce the subjectivity. The assessment of groundwater vulnerability has been carried out with the GNDCI-CNR method.
This method, which does not need numerical input parameters, is particularly suitable for a large territory characterized by many geological, hydro-geological and morphological features, in which data and information are often unavailable, generic and territorially inhomogeneous
Fuzzy logic model development for groundwater pollution risk assessment
Full text linkThe following paper presents a methodology for a rapid and effective assessment of groundwater pollution risk connected with the presence of uncontrolled landfills. Moreover, this methodology supplies an environmental planning tool to define a groundwater risk hierarchy index in function of some intrinsic characteristics of landfills and territory, in which they are located. The risk assessment was carried out with a fuzzy model, which includes the groundwater vulnerability and the intrinsic hazard of landfills. In particular, for the assessment of groundwater vulnerability the GNDCI-CNR method was used. This method examines the different geological, hydrogeological and morphological characteristics of the territory. Whereas, the hazard of landfills was evaluated together with the risk of contamination of the aquifers in the fuzzy model, taking into account the different descriptor parameters of the landfills. In addition, the fuzzy model was combined with the sensitivity analysis in order to overcome the problem of subjectivity and uncertainty associated with both input data and fuzzy conceptual model
Characterization of the organic residual fraction form an old landfill for agronomic applications
No full textUncontrolled landfills are one of the causes of lithosphere contamination. The present study addresses the reclamation theme of an old landfill by using landfill mining. Attention is focused on the reuse of the organic residual fraction through the application of remediation technology. We propose a protocol of analysis of the landfill material sieved at 4 mm and 10 mm, that links chemical analyses and environmental bioassays. This protocol will be used to evaluate residual compatibility of the matrix for the landfill capping. Attention is mainly focused on the presence of heavy metals and on the possible interaction with test organisms. Chemical analyses of the residual matrix often showed the presence of heavy metals in concentrations exceeding the legislation limits. The biological tests do not particularly emphasize adverse effects to the growth of the used plant species. The bioassay test with Spartium junceum showed a good adaptation to stress conditions induced by the presence of the residual matrix. In conclusion, the conducted experimental activities demonstrated that the material could be reused in daily and final covering of controlled landfills. The proposed protocol allows us to have the following advantages: site reclamation with landfill mining operations, significant decrease in waste volume which should be added in new landfills, a saving of new inert material to be used in the management of current landfills
Habitat ecological integrity and environmental impact assessment of anthropic activities: A GIS-based fuzzy logic model for sites of high biodiversity conservation interest
No full textIn literature, an effective method enabling the classification, based on a single indicator, of habitats that need a priority protection intervention has not been identified yet. Moreover, the excessive number of landscape metrics, used to quantify integrity of habitats, can cause confusion, often providing redundant and inconsistent results. The aim of this work is to develop a method for evaluating the ecological vulnerability of the habitats in sites of high biodiversity conservation interest. In the first phase, we selected and analyzed, by using principal component analysis (PCA) and fuzzy logic, the landscape metrics, in order to obtain the map of the intrinsic ecological vulnerability index. In the second step, the result of this intrinsic vulnerability was connected, through another fuzzy model, to anthropogenic impacts, obtaining the integrated ecological vulnerability index. We developed specific spatial indicators (landscape metrics), which can examine the mutual position and morphology of the habitats present, along with indicators of human pressure, related to the type and intensity of use of the anthropic territory, with reference to the habitat itself as well as to the areas immediately adjacent. The developed fuzzy models are innovative, compared to the current ecological studies, and examine landscape metrics as well as the impact of human activities. The case study is the "Val Basento-Ferrandina Scalo" Site of Community Importance, Ferrandina-SCI (Basilicata Region, Southern Italy). The results allowed us to build a rank of the habitats based on their intrinsic and integrated ecological vulnerability. Moreover, the results show that, in the Ferrandina-SCI, the most important source of concern is not human activities, but rather the inherent risk of ecological fragility caused by geographical and landscape features of the different patches of habitats themselves. This model aims to be a tool for decision support in sustainable landscape management. It is easy to use and to apply on other regions, although it should always be accompanied by a sensitivity analysis to reduce the subjectivity
Assessment of the possible reuse of MSW coming from landfill mining of old open dumpsites
No full textThe present study addresses the theme of recycling potential of old open dumpsites by using landfill mining.
Attention is focused on the possible reuse of the residual finer fraction (<4 mm), which constitutes more than 60% of the total mined material, sampled in the old open dumpsite of Lavello (Southern Italy).
We propose a protocol of analysis of the landfill material that links chemical analyses and environmental bioassays. This protocol is used to evaluate the compatibility of the residual matrix for the disposal in
temporary storages and the formation of ‘‘bio-soils’’ to be used in geo-environmental applications, such as the construction of barrier layers of landfills, or in environmental remediation activities. Attention is
mainly focused on the presence of heavy metals and on the possible interaction with test organisms.
Chemical analyses of the residual matrix and leaching tests showed that the concentration of heavy metals is always below the legislation limits. Biological acute tests (with Lepidum sativum, Vicia faba and Lactuca sativa) do not emphasize adverse effects to the growth of the plant species, except the bioassay with V. faba, which showed a dose–response effect. The new developed chronic bioassay test with Spartium junceum showed a good adaptation to stress conditions induced by the presence of the mined landfill material. In conclusion, the conducted experimental activities demonstrated the suitability of the material to be used for different purposes
Environmental monitoring and impact mitigation related to landfill management
No full textA landfill can cause significant environmental impacts especially on water, air and soil. The study concentrates on the search for strategies to reduce the pollution risk of landfills. The attention is focused on the problem of a long-term impact of dry-tomb landfills and on the difficulty of controlling and limiting landfill gas emissions to the atmosphere, that concur to increase the greenhouse effect. The first objective is the experimental test of a landfill cover system that can match the acceleration of stabilization processes of organic materials. The scientific literature suggests the possibility of accelerating the process of waste stabilization in landfill, therefore reducing the risk of contamination after the post-management period. The second objective is the optimization of the biogas management, in order to treat the landfill gas with low calorific value, to capture biogas in the first stage of cultivation and in the "tail" phase. From the literature we also learn that the sources of greenhouse gases from human activities, including the production of biogas in landfills, are considered to be the most dangerous
Fuzzy Logic and Neuro-Fuzzy Networks for Environmental Hazard Assessment
Full text linkPollution and management of the environment are serious problems which concern the entire planet; the main responsibility should be attributed to human activities that contribute significantly to damage the environment, leading to an imbalance of natural ecosystems. In recent years, numerous studies focused on the three environmental compartments: soil, water and air. The pollution of groundwater is a widespread problem. The causes of pollution are often linked to human activities, including waste disposal.
Solid waste management has become an important environmental issue in industrialized countries. The most serious problems are related to solid waste disposal. Landfill is still the most used disposal technique but not the safest. In fact, even controlled landfills could easily incur in the breakdown of containment elements. This breakdown could cause contamination of aquifer that is environmental pollution. Such contamination can be mitigated by performing remediation and environmental restoration. The assessment of environmental pollution risk can be performed with different degrees of detail and precision.
Various statistical and mathematical models can be used for a qualitative risk assessment. The planning of a program for environmental remediation and restoration can be supported by expeditious methodologies that allow to obtain a hierarchical classification of contaminated sites. The literature offers some expeditious and qualitative methods including fuzzy logic (Zadeh, 1965), neural networks and neuro-fuzzy networks, which are more objective methods. The three artificial intelligence systems differ among themselves in some respects: fuzzy inference system learns knowledge of data only through the fuzzy rules; neural network is able to learn knowledge of data using the weights of synaptic connections; neuro-fuzzy systems are able to learn knowledge of neural data with neural paradigm and represent it in the form of fuzzy rules.
Fuzzy logic was founded in 1965 by Zadeh. The first applications date back to the nineties. They were mainly used to control industrial processes, household electrical appliances and means of transport. Later, this approach was used in several fields including the environment. In fact it could be used for assessing environmental risk related to contamination of groundwater. The fuzzy approach is advantageous because it allows a quick assessment of the risk, but is disadvantageous because of the increasing complexity in the definition of fuzzy rules along with the increasing of the number of parameters. In many situations, when the number of parameters are considered high in the analysis, application of these techniques is cumbersome and complex and could be used for neuro-fuzzy models. These models reduce the complexity because they use training data. The neuro-fuzzy model were supported by a sensitivity analysis in order to address the problem of subjectivity and uncertainty of model input data
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