"\"Emissions of unpleasant odours are associated to many different types of industrial . activities (e.g. paper mills, tanneries, refineries, slaughterhouses, distilleries, . pharmaceutical industries, etc.), civil and industrial wastewater treatment plants, landfills . and composting plants. Their production is generally related to microbial degradation . processes of putrescible organic substances. . In recent decades, the increasing number of landfills located in residential areas has . attracted the attention of the scientific and technical community, placing greater emphasis . on how odour emissions from landfills can be measured and how they can be diminished. . This paper proposes a Fuzzy Early Warning System (FEWS) for the mitigation of the risk . of exposure to odorous substances emitted from a waste landfill in a highly urbanised . area. A fuzzy logic approach was chosen to tackle the complex task of modelling an . automatic decision support system considering several risk variables, such as the wind . speed, the time derivative of the velocity, the wind direction, the time derivative of the . wind direction and the temperature. Indeed the fuzzy logic approach proved to be very . effective both for its “native” capability to deal with nonlinear models and for the possibility . to take into account heuristic and political rules. . The FEWS takes into account both hazard variables (e.g. the contaminant source . emission rate) and vulnerability and exposure variables (e.g. the distance of the landfill . and the typology of human activities). The case study of a solid waste landfill near Naples . (Italy), located in a densely populated area was considered. . The analysis of odour transport was carried out by using ISCST3-BREEZE developed by . EPA. This allows odour dispersion in air to be assessed as a function of weather . conditions (data provided by Capodichino Airport weather station) and contaminant . emissions (estimated using scientific literature). The FEWS is part of a MATLAB . framework in which the fuzzy input variables considered were modelled with a . “membership function” and the risk mitigation actions (e.g., covering of waste, spraying of . fragrant substances, extraction wells to maintain the landfill body at a pressure below . atmospheric, pressure, etc.) were inferred using a set of SUGENO fuzzy output rules. . The simulation results show that FEWS is very effective as compared to simulations . without any mitigation actions. Indeed the use of FEWS allowed for a considerable . reduction in the number of exceedances in all the sensitive centers analyzed, although in . some cases the FEWS operates also when it does not need. The next steps will consist . in improving the optimization of fuzzy rules and membership functions with other . techniques. \""
A Fuzzy Early Warning System To Mitigate The Odorous Substances Emitted From A Waste Landfill
DI NARDO, Armando;Santonastaso G. F.;DI NATALE, Michele;MUSMARRA, Dino
2013
Abstract
"\"Emissions of unpleasant odours are associated to many different types of industrial . activities (e.g. paper mills, tanneries, refineries, slaughterhouses, distilleries, . pharmaceutical industries, etc.), civil and industrial wastewater treatment plants, landfills . and composting plants. Their production is generally related to microbial degradation . processes of putrescible organic substances. . In recent decades, the increasing number of landfills located in residential areas has . attracted the attention of the scientific and technical community, placing greater emphasis . on how odour emissions from landfills can be measured and how they can be diminished. . This paper proposes a Fuzzy Early Warning System (FEWS) for the mitigation of the risk . of exposure to odorous substances emitted from a waste landfill in a highly urbanised . area. A fuzzy logic approach was chosen to tackle the complex task of modelling an . automatic decision support system considering several risk variables, such as the wind . speed, the time derivative of the velocity, the wind direction, the time derivative of the . wind direction and the temperature. Indeed the fuzzy logic approach proved to be very . effective both for its “native” capability to deal with nonlinear models and for the possibility . to take into account heuristic and political rules. . The FEWS takes into account both hazard variables (e.g. the contaminant source . emission rate) and vulnerability and exposure variables (e.g. the distance of the landfill . and the typology of human activities). The case study of a solid waste landfill near Naples . (Italy), located in a densely populated area was considered. . The analysis of odour transport was carried out by using ISCST3-BREEZE developed by . EPA. This allows odour dispersion in air to be assessed as a function of weather . conditions (data provided by Capodichino Airport weather station) and contaminant . emissions (estimated using scientific literature). The FEWS is part of a MATLAB . framework in which the fuzzy input variables considered were modelled with a . “membership function” and the risk mitigation actions (e.g., covering of waste, spraying of . fragrant substances, extraction wells to maintain the landfill body at a pressure below . atmospheric, pressure, etc.) were inferred using a set of SUGENO fuzzy output rules. . The simulation results show that FEWS is very effective as compared to simulations . without any mitigation actions. Indeed the use of FEWS allowed for a considerable . reduction in the number of exceedances in all the sensitive centers analyzed, although in . some cases the FEWS operates also when it does not need. The next steps will consist . in improving the optimization of fuzzy rules and membership functions with other . techniques. \""I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
