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Chris Aldrich - One of the best experts on this subject based on the ideXlab platform.
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New methodology for hazardous Waste classification using fuzzy set theory Part I. Knowledge acquisition.
Journal of Hazardous Materials, 2008Co-Authors: Ndeke Musee, Leon Lorenzen, Chris AldrichAbstract:In the literature on hazardous Waste classification, the criteria used are mostly based on physical properties, such as Quantity (weight), form (solids, liquid, aqueous or gaseous), the type of processes generating them, or a set of predefined lists. Such classification criteria are inherently inadequate to account for the influence of toxic and hazard characteristics of the constituent chemicals in the Wastes, as well as their exposure potency in multimedia environments, terrestrial mammals and other biota. Second, none of these algorithms in the literature has explicitly presented Waste classification by examining the contribution of individual constituent components of the composite Wastes. In this two-part paper, we propose a new automated algorithm for Waste classification that takes into account physicochemical and toxicity effects of the constituent chemicals to humans and ecosystems, in addition, to the exposure potency and Waste Quantity. In part I, available data on the physicochemical and toxicity properties of individual chemicals in humans and ecosystems, their exposure potency in environmental systems and the effect of Waste Quantity are described, because they fundamentally contribute to the final Waste ranking. Knowledge acquisition in this study was accomplished through the extensive review of published and specialized literature to establish facts necessary for the development of fuzzy rule-bases. Owing to the uncertainty and imprecision of various forms of data (both quantitative and qualitative) essential for Waste classification, and the complexity resulting from knowledge incompleteness, the use of fuzzy set theory for the aggregation and computation of Waste classification ranking index is proposed. A computer-aided intelligent decision tool is described in part II of this paper and the functionality of the fuzzy Waste classification algorithm is illustrated through nine worked examples.
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New methodology for hazardous Waste classification using fuzzy set theory
Journal of Hazardous Materials, 2007Co-Authors: Ndeke Musee, Chris Aldrich, Leon LorenzenAbstract:In the literature on hazardous Waste classification, the criteria used are mostly based on physical properties, such as Quantity (weight), form (solids, liquid, aqueous or gaseous), the type of processes generating them, or a set of predefined lists. Such classification criteria are inherently inadequate to account for the influence of toxic and hazard characteristics of the constituent chemicals in the Wastes, as well as their exposure potency in multimedia environments, terrestrial mammals and other biota. Second, none of these algorithms in the literature has explicitly presented Waste classification by examining the contribution of individual constituent components of the composite Wastes. In this two-part paper, we propose a new automated algorithm for Waste classification that takes into account physicochemical and toxicity effects of the constituent chemicals to humans and ecosystems, in addition, to the exposure potency and Waste Quantity. In part I, available data on the physicochemical and toxicity properties of individual chemicals in humans and ecosystems, their exposure potency in environmental systems and the effect of Waste Quantity are described, because they fundamentally contribute to the final Waste ranking. Knowledge acquisition in this study was accomplished through the extensive review of published and specialized literature to establish facts necessary for the development of fuzzy rule-bases. Owing to the uncertainty and imprecision of various forms of data (both quantitative and qualitative) essential for Waste classification, and the complexity resulting from knowledge incompleteness, the use of fuzzy set theory for the aggregation and computation of Waste classification ranking index is proposed. A computer-aided intelligent decision tool is described in part II of this paper and the functionality of the fuzzy Waste classification algorithm is illustrated through nine worked examples.
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New methodology for Waste classification using fuzzy set theory Part 1. Knowledge Acquisition
Journal of hazardous materials, 2007Co-Authors: Ndeke Musee, Leon Lorenzen, Chris AldrichAbstract:In the literature on hazardous Waste classification, the criteria used are mostly based on physical properties, such as Quantity (weight), form (solids, liquid, aqueous or gaseous), the type of processes generating them, or a set of predefined lists. Such classification criteria are inherently inadequate to account for the influence of toxic and hazard characteristics of the constituent chemicals in the Wastes, as well as their exposure potency in multimedia environments, terrestrial mammals and other biota. Second, none of these algorithms in the literature has explicitly presented Waste classification by examining the contribution of individual constituent components of the composite Wastes. In this two-part paper, we propose a new automated algorithm for Waste classification that takes into account physicochemical and toxicity effects of the constituent chemicals to humans and ecosystems, in addition, to the exposure potency and Waste Quantity. In part I, available data on the physicochemical and toxicity properties of individual chemicals in humans and ecosystems, their exposure potency in environmental systems and the effect of Waste Quantity are described, because they fundamentally contribute to the final Waste ranking. Knowledge acquisition in this study was accomplished through the extensive review of published and specialized literature to establish facts necessary for the development of fuzzy rule-bases. Owing to the uncertainty and imprecision of various forms of data (both quantitative and qualitative) essential for Waste classification, and the complexity resulting from knowledge incompleteness, the use of fuzzy set theory for the aggregation and computation of Waste classification ranking index is proposed. A computer-aided intelligent decision tool is described in part II of this paper and the functionality of the fuzzy Waste classification algorithm is illustrated through nine worked examples.
Ndeke Musee - One of the best experts on this subject based on the ideXlab platform.
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New methodology for hazardous Waste classification using fuzzy set theory Part I. Knowledge acquisition.
Journal of Hazardous Materials, 2008Co-Authors: Ndeke Musee, Leon Lorenzen, Chris AldrichAbstract:In the literature on hazardous Waste classification, the criteria used are mostly based on physical properties, such as Quantity (weight), form (solids, liquid, aqueous or gaseous), the type of processes generating them, or a set of predefined lists. Such classification criteria are inherently inadequate to account for the influence of toxic and hazard characteristics of the constituent chemicals in the Wastes, as well as their exposure potency in multimedia environments, terrestrial mammals and other biota. Second, none of these algorithms in the literature has explicitly presented Waste classification by examining the contribution of individual constituent components of the composite Wastes. In this two-part paper, we propose a new automated algorithm for Waste classification that takes into account physicochemical and toxicity effects of the constituent chemicals to humans and ecosystems, in addition, to the exposure potency and Waste Quantity. In part I, available data on the physicochemical and toxicity properties of individual chemicals in humans and ecosystems, their exposure potency in environmental systems and the effect of Waste Quantity are described, because they fundamentally contribute to the final Waste ranking. Knowledge acquisition in this study was accomplished through the extensive review of published and specialized literature to establish facts necessary for the development of fuzzy rule-bases. Owing to the uncertainty and imprecision of various forms of data (both quantitative and qualitative) essential for Waste classification, and the complexity resulting from knowledge incompleteness, the use of fuzzy set theory for the aggregation and computation of Waste classification ranking index is proposed. A computer-aided intelligent decision tool is described in part II of this paper and the functionality of the fuzzy Waste classification algorithm is illustrated through nine worked examples.
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New methodology for hazardous Waste classification using fuzzy set theory
Journal of Hazardous Materials, 2007Co-Authors: Ndeke Musee, Chris Aldrich, Leon LorenzenAbstract:In the literature on hazardous Waste classification, the criteria used are mostly based on physical properties, such as Quantity (weight), form (solids, liquid, aqueous or gaseous), the type of processes generating them, or a set of predefined lists. Such classification criteria are inherently inadequate to account for the influence of toxic and hazard characteristics of the constituent chemicals in the Wastes, as well as their exposure potency in multimedia environments, terrestrial mammals and other biota. Second, none of these algorithms in the literature has explicitly presented Waste classification by examining the contribution of individual constituent components of the composite Wastes. In this two-part paper, we propose a new automated algorithm for Waste classification that takes into account physicochemical and toxicity effects of the constituent chemicals to humans and ecosystems, in addition, to the exposure potency and Waste Quantity. In part I, available data on the physicochemical and toxicity properties of individual chemicals in humans and ecosystems, their exposure potency in environmental systems and the effect of Waste Quantity are described, because they fundamentally contribute to the final Waste ranking. Knowledge acquisition in this study was accomplished through the extensive review of published and specialized literature to establish facts necessary for the development of fuzzy rule-bases. Owing to the uncertainty and imprecision of various forms of data (both quantitative and qualitative) essential for Waste classification, and the complexity resulting from knowledge incompleteness, the use of fuzzy set theory for the aggregation and computation of Waste classification ranking index is proposed. A computer-aided intelligent decision tool is described in part II of this paper and the functionality of the fuzzy Waste classification algorithm is illustrated through nine worked examples.
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New methodology for Waste classification using fuzzy set theory Part 1. Knowledge Acquisition
Journal of hazardous materials, 2007Co-Authors: Ndeke Musee, Leon Lorenzen, Chris AldrichAbstract:In the literature on hazardous Waste classification, the criteria used are mostly based on physical properties, such as Quantity (weight), form (solids, liquid, aqueous or gaseous), the type of processes generating them, or a set of predefined lists. Such classification criteria are inherently inadequate to account for the influence of toxic and hazard characteristics of the constituent chemicals in the Wastes, as well as their exposure potency in multimedia environments, terrestrial mammals and other biota. Second, none of these algorithms in the literature has explicitly presented Waste classification by examining the contribution of individual constituent components of the composite Wastes. In this two-part paper, we propose a new automated algorithm for Waste classification that takes into account physicochemical and toxicity effects of the constituent chemicals to humans and ecosystems, in addition, to the exposure potency and Waste Quantity. In part I, available data on the physicochemical and toxicity properties of individual chemicals in humans and ecosystems, their exposure potency in environmental systems and the effect of Waste Quantity are described, because they fundamentally contribute to the final Waste ranking. Knowledge acquisition in this study was accomplished through the extensive review of published and specialized literature to establish facts necessary for the development of fuzzy rule-bases. Owing to the uncertainty and imprecision of various forms of data (both quantitative and qualitative) essential for Waste classification, and the complexity resulting from knowledge incompleteness, the use of fuzzy set theory for the aggregation and computation of Waste classification ranking index is proposed. A computer-aided intelligent decision tool is described in part II of this paper and the functionality of the fuzzy Waste classification algorithm is illustrated through nine worked examples.
Leon Lorenzen - One of the best experts on this subject based on the ideXlab platform.
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New methodology for hazardous Waste classification using fuzzy set theory Part I. Knowledge acquisition.
Journal of Hazardous Materials, 2008Co-Authors: Ndeke Musee, Leon Lorenzen, Chris AldrichAbstract:In the literature on hazardous Waste classification, the criteria used are mostly based on physical properties, such as Quantity (weight), form (solids, liquid, aqueous or gaseous), the type of processes generating them, or a set of predefined lists. Such classification criteria are inherently inadequate to account for the influence of toxic and hazard characteristics of the constituent chemicals in the Wastes, as well as their exposure potency in multimedia environments, terrestrial mammals and other biota. Second, none of these algorithms in the literature has explicitly presented Waste classification by examining the contribution of individual constituent components of the composite Wastes. In this two-part paper, we propose a new automated algorithm for Waste classification that takes into account physicochemical and toxicity effects of the constituent chemicals to humans and ecosystems, in addition, to the exposure potency and Waste Quantity. In part I, available data on the physicochemical and toxicity properties of individual chemicals in humans and ecosystems, their exposure potency in environmental systems and the effect of Waste Quantity are described, because they fundamentally contribute to the final Waste ranking. Knowledge acquisition in this study was accomplished through the extensive review of published and specialized literature to establish facts necessary for the development of fuzzy rule-bases. Owing to the uncertainty and imprecision of various forms of data (both quantitative and qualitative) essential for Waste classification, and the complexity resulting from knowledge incompleteness, the use of fuzzy set theory for the aggregation and computation of Waste classification ranking index is proposed. A computer-aided intelligent decision tool is described in part II of this paper and the functionality of the fuzzy Waste classification algorithm is illustrated through nine worked examples.
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New methodology for hazardous Waste classification using fuzzy set theory
Journal of Hazardous Materials, 2007Co-Authors: Ndeke Musee, Chris Aldrich, Leon LorenzenAbstract:In the literature on hazardous Waste classification, the criteria used are mostly based on physical properties, such as Quantity (weight), form (solids, liquid, aqueous or gaseous), the type of processes generating them, or a set of predefined lists. Such classification criteria are inherently inadequate to account for the influence of toxic and hazard characteristics of the constituent chemicals in the Wastes, as well as their exposure potency in multimedia environments, terrestrial mammals and other biota. Second, none of these algorithms in the literature has explicitly presented Waste classification by examining the contribution of individual constituent components of the composite Wastes. In this two-part paper, we propose a new automated algorithm for Waste classification that takes into account physicochemical and toxicity effects of the constituent chemicals to humans and ecosystems, in addition, to the exposure potency and Waste Quantity. In part I, available data on the physicochemical and toxicity properties of individual chemicals in humans and ecosystems, their exposure potency in environmental systems and the effect of Waste Quantity are described, because they fundamentally contribute to the final Waste ranking. Knowledge acquisition in this study was accomplished through the extensive review of published and specialized literature to establish facts necessary for the development of fuzzy rule-bases. Owing to the uncertainty and imprecision of various forms of data (both quantitative and qualitative) essential for Waste classification, and the complexity resulting from knowledge incompleteness, the use of fuzzy set theory for the aggregation and computation of Waste classification ranking index is proposed. A computer-aided intelligent decision tool is described in part II of this paper and the functionality of the fuzzy Waste classification algorithm is illustrated through nine worked examples.
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New methodology for Waste classification using fuzzy set theory Part 1. Knowledge Acquisition
Journal of hazardous materials, 2007Co-Authors: Ndeke Musee, Leon Lorenzen, Chris AldrichAbstract:In the literature on hazardous Waste classification, the criteria used are mostly based on physical properties, such as Quantity (weight), form (solids, liquid, aqueous or gaseous), the type of processes generating them, or a set of predefined lists. Such classification criteria are inherently inadequate to account for the influence of toxic and hazard characteristics of the constituent chemicals in the Wastes, as well as their exposure potency in multimedia environments, terrestrial mammals and other biota. Second, none of these algorithms in the literature has explicitly presented Waste classification by examining the contribution of individual constituent components of the composite Wastes. In this two-part paper, we propose a new automated algorithm for Waste classification that takes into account physicochemical and toxicity effects of the constituent chemicals to humans and ecosystems, in addition, to the exposure potency and Waste Quantity. In part I, available data on the physicochemical and toxicity properties of individual chemicals in humans and ecosystems, their exposure potency in environmental systems and the effect of Waste Quantity are described, because they fundamentally contribute to the final Waste ranking. Knowledge acquisition in this study was accomplished through the extensive review of published and specialized literature to establish facts necessary for the development of fuzzy rule-bases. Owing to the uncertainty and imprecision of various forms of data (both quantitative and qualitative) essential for Waste classification, and the complexity resulting from knowledge incompleteness, the use of fuzzy set theory for the aggregation and computation of Waste classification ranking index is proposed. A computer-aided intelligent decision tool is described in part II of this paper and the functionality of the fuzzy Waste classification algorithm is illustrated through nine worked examples.
Delia Teresa Sponza - One of the best experts on this subject based on the ideXlab platform.
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co digestion of mixed industrial sludge with municipal solid Wastes in anaerobic simulated landfilling bioreactors
Journal of Hazardous Materials, 2007Co-Authors: Osman Nuri Agdag, Delia Teresa SponzaAbstract:In this study, the feasibility of the anaerobic co-digestion of a mixed industrial sludge with municipal solid Wastes (MSW) was investigated in three simulated anaerobic landfilling bioreactors during a 150-day period. All of the reactors were operated with leachate recirculation. One of them was loaded only with MSW (control reactor); the second reactor was loaded with mixed industrial sludge and MSW, the weight ratio of the MSW to mixed industrial sludge was 1:1 (based on dry solid) (Run 1); the third reactor was loaded with mixed industrial sludge and MSW, the weight ratio of the MSW to mixed industrial sludge was 1:2 (based on dry solid) (Run 2). The VFA concentrations decreased significantly in Run 1 and Run 2 reactors at the end of 150 days. The pH values were higher in Run 1 and Run 2 reactors compared to control reactor. The differences between leachate characteristics, the biodegradation and the bioefficiency of the reactors were compared. The NH4–N concentrations released to leachate from mixed sludge in Run 1 and Run 2 reactors were lower than that of control reactor. The BOD5/COD ratios in Run 1 and Run 2 reactors were lower than that of control reactor at the end of 150 days. Cumulative methane gas productions and methane percentages were higher in Run 1 and Run 2 reactors. Reductions in Waste Quantity, carbon percentage and settlement of the Waste were better in Run 1 and Run 2 reactors compared to control reactor at the end of 150 days. Furthermore, TN and TP removals in Waste were higher in reactors containing industrial sludge compared to control. The toxicity test results showed that toxicity was observed in reactors containing industrial mixed sludge.
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effect of alkalinity on the performance of a simulated landfill bioreactor digesting organic solid Wastes
Chemosphere, 2005Co-Authors: Osman Nuri Agdag, Delia Teresa SponzaAbstract:This study investigated the effects of alkalinity on the anaerobic treatment of the organic solid Wastes collected from the kitchen of Engineering Faculty in Dokuz Eylul University, Izmir, Turkey and the leachate characteristics treated in three simulated landfill anaerobic bioreactors. All of the reactors were operated with leachate recirculation. One reactor was operated without alkalinity addition. The second reactor was operated by the addition of 3 g l-1 d-1 of NaHCO3 alkalinity to the leachate and the third reactor was operated by the addition of 6 g l-1 d-1 NaHCO3 alkalinity to the leachate. After 65 d of anaerobic incubation, it was observed that the chemical oxygen demand (COD), volatile fatty acids (VFA) concentrations, and biochemical oxygen demand to chemical oxygen demand (BOD5/COD) ratios in the leachate samples produced from the alkalinity added reactors were lower than the control reactor while the pH values were higher than the control reactor. The COD values were measured as 18900, 3800 and 2900 mg l-1 while the VFA concentrations were 6900, 1400 and 1290 mg l-1, respectively, in the leachate samples of the control, and reactors containing 3 g l-1 NaHCO3 and 6 g l-1 NaHCO3 after 65 d of anaerobic incubation. The total nitrogen (TN), total phosphorus (TP) and ammonium nitrogen (NH4-N) concentrations in organic solid Waste (OSW) significantly reduced in the reactor containing 6 g l-1 NaHCO3 by d 65. The values of pH were 6.54, 7.19 and 7.31, after 65 d of anaerobic incubation, respectively, in the aforementioned reactors results in neutral environmental conditions in alkalinity added reactors. Methane percentage of the control, reactors containing 3 g l-1 NaHCO3 and 6 g l-1 NaHCO3 were 37%, 64% and 65%, respectively, after 65 d of incubation. BOD5/COD ratios of 0.27 and 0.25 were achieved in the 3 and 6 g l-1 NaHCO3 containing reactors, indicating a better OSW stabilization. Alkalinity addition reduced the Waste Quantity, the organic content of the solid Waste and the biodegradation time.
Osman Nuri Agdag - One of the best experts on this subject based on the ideXlab platform.
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co digestion of mixed industrial sludge with municipal solid Wastes in anaerobic simulated landfilling bioreactors
Journal of Hazardous Materials, 2007Co-Authors: Osman Nuri Agdag, Delia Teresa SponzaAbstract:In this study, the feasibility of the anaerobic co-digestion of a mixed industrial sludge with municipal solid Wastes (MSW) was investigated in three simulated anaerobic landfilling bioreactors during a 150-day period. All of the reactors were operated with leachate recirculation. One of them was loaded only with MSW (control reactor); the second reactor was loaded with mixed industrial sludge and MSW, the weight ratio of the MSW to mixed industrial sludge was 1:1 (based on dry solid) (Run 1); the third reactor was loaded with mixed industrial sludge and MSW, the weight ratio of the MSW to mixed industrial sludge was 1:2 (based on dry solid) (Run 2). The VFA concentrations decreased significantly in Run 1 and Run 2 reactors at the end of 150 days. The pH values were higher in Run 1 and Run 2 reactors compared to control reactor. The differences between leachate characteristics, the biodegradation and the bioefficiency of the reactors were compared. The NH4–N concentrations released to leachate from mixed sludge in Run 1 and Run 2 reactors were lower than that of control reactor. The BOD5/COD ratios in Run 1 and Run 2 reactors were lower than that of control reactor at the end of 150 days. Cumulative methane gas productions and methane percentages were higher in Run 1 and Run 2 reactors. Reductions in Waste Quantity, carbon percentage and settlement of the Waste were better in Run 1 and Run 2 reactors compared to control reactor at the end of 150 days. Furthermore, TN and TP removals in Waste were higher in reactors containing industrial sludge compared to control. The toxicity test results showed that toxicity was observed in reactors containing industrial mixed sludge.
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effect of alkalinity on the performance of a simulated landfill bioreactor digesting organic solid Wastes
Chemosphere, 2005Co-Authors: Osman Nuri Agdag, Delia Teresa SponzaAbstract:This study investigated the effects of alkalinity on the anaerobic treatment of the organic solid Wastes collected from the kitchen of Engineering Faculty in Dokuz Eylul University, Izmir, Turkey and the leachate characteristics treated in three simulated landfill anaerobic bioreactors. All of the reactors were operated with leachate recirculation. One reactor was operated without alkalinity addition. The second reactor was operated by the addition of 3 g l-1 d-1 of NaHCO3 alkalinity to the leachate and the third reactor was operated by the addition of 6 g l-1 d-1 NaHCO3 alkalinity to the leachate. After 65 d of anaerobic incubation, it was observed that the chemical oxygen demand (COD), volatile fatty acids (VFA) concentrations, and biochemical oxygen demand to chemical oxygen demand (BOD5/COD) ratios in the leachate samples produced from the alkalinity added reactors were lower than the control reactor while the pH values were higher than the control reactor. The COD values were measured as 18900, 3800 and 2900 mg l-1 while the VFA concentrations were 6900, 1400 and 1290 mg l-1, respectively, in the leachate samples of the control, and reactors containing 3 g l-1 NaHCO3 and 6 g l-1 NaHCO3 after 65 d of anaerobic incubation. The total nitrogen (TN), total phosphorus (TP) and ammonium nitrogen (NH4-N) concentrations in organic solid Waste (OSW) significantly reduced in the reactor containing 6 g l-1 NaHCO3 by d 65. The values of pH were 6.54, 7.19 and 7.31, after 65 d of anaerobic incubation, respectively, in the aforementioned reactors results in neutral environmental conditions in alkalinity added reactors. Methane percentage of the control, reactors containing 3 g l-1 NaHCO3 and 6 g l-1 NaHCO3 were 37%, 64% and 65%, respectively, after 65 d of incubation. BOD5/COD ratios of 0.27 and 0.25 were achieved in the 3 and 6 g l-1 NaHCO3 containing reactors, indicating a better OSW stabilization. Alkalinity addition reduced the Waste Quantity, the organic content of the solid Waste and the biodegradation time.
