Modeling the dioxin emission of a municipal solid waste incinerator using neural networks

Bunsan, Sond; Chen, Wei-Yea; Chen, Ho‐Wen; Chuang, Yen Hsun; Grisdanurak, Nurak

doi:10.1016/j.chemosphere.2013.01.083

Cited by 69 publications

(15 citation statements)

References 36 publications

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“…According to our literature review, a data-driven model of WtE plant operation, which is presented in this paper, has not been published yet. Research with a similar focus was, however, presented by Bunsan et al [12] where an ANN (artificial neural network) model was used to predict dioxin emission production in order to plan strategies for reducing pollution.…”

Section: Nomenclaturementioning

confidence: 95%

Combined heat and power production planning in a waste-to-energy plant on a short-term basis

Touš

Pavlas

Putna

et al. 2015

Energy

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Section: Nomenclaturementioning

confidence: 95%

Combined heat and power production planning in a waste-to-energy plant on a short-term basis

Touš

Pavlas

Putna

et al. 2015

Energy

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“…[1,[13][14][15] conducted simulations of the behavior of dioxins using atmospheric dispersion models. [16][17][18][19][20] modeled the behavior of dioxins in the atmosphere. Further, [21,22] used dispersion models to conduct simulations of the behavior of dioxins in bodies of water such as sea waters and canals, and [23] modeled the behavior of dioxins in bodies of water.…”

Section: Related Workmentioning

confidence: 99%

“…Source data is source location (longitude and latitude), annual emissions and emissions elevation; chemical substance parameters are the molecular weight and form of the chemical substance. Concerning the dioxin parameters, referring to the related research previously mentioned [1,4,5,[7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] and the Ministry of the Environment (2004) [3], the molecular weight of a dioxin was assumed to be 388, the molecular weight for PeCDF, which occurs in the greatest percentage at incineration plant exhaust gas dioxin levels, and the form of a dioxin was entered into METI-LIS as a particulate spherical shape.…”

Section: ) Source Data and Chemical Substance Parametersmentioning

confidence: 99%

An Environmental Risk Evaluation Method Employing Atmospheric Dispersion Models and GIS

Ishii¹,

Yamamoto²

2013

JEP

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This study aims to develop a method for evaluating the environmental risk of harmful chemical substances released from specific sources, using two atmospheric dispersion models and GIS (Geographic Information Systems). In the first stage of evaluation, ADMER was used to conduct a wide-area evaluation which covered the entire area of the evaluation target region. In the second stage, METI-LIS was used to conduct a detailed limited-area evaluation which targeted the vicinity of sources. In this study, incinerators were selected as sources and dioxins were selected as harmful chemical substances. The area selected for evaluation was the Tokyo Metropolis in Japan, and the evaluation method proposed in this study was used to evaluate environmental risk. Through the use of atmospheric dispersion models and GIS, the behavior of dioxins emitted into the atmosphere from incinerators was estimated. By superimposing atmospheric levels and population data, the amounts of dioxins that humans exposed to were found. Additionally, by superimposing deposition amounts and land use data, the amounts of dioxins accumulated in each land environment were found. Conducting these steps enabled the impact of dioxins on humans and the environment to be grasped quantitatively and visually, and the risk that dioxins emitted from incinerators pose to the environment to be evaluated.

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“…These chemical groups are generally released from incineration systems. They form by rearrangement of chlorine atoms on CPCs in the postcombustion region of incinerators (Bunsan et al 2013). The United States Environmental Protection Agency has listed PCDDs and PCDFs as priority pollutants because of their extreme toxicity and because of their hazardous classification as human carcinogens and mutagens (US EPA 2000).…”

Section: Introductionmentioning

confidence: 99%

Influence of chlorine substitution on adsorption of gaseous chlorinated phenolics on multi-walled carbon nanotubes embedded in SiO2

Tulaphol

Bunsan²,

Kanchanatip

et al. 2016

Int. J. Environ. Sci. Technol.

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Multi-walled carbon nanotubes (MWCNTs) embedded in SiO 2 particles were prepared through the floating-catalyst chemical vapor deposition method. The parameters reaction time and flow rate of the carbon source (CH 4 ) were studied to obtain optimum conditions for MWCNT synthesis. The obtained MWCNTs were characterized by transmission electron microscopy, scanning electron microscopy, Raman spectroscopy, and Fourier transform infrared spectroscopy to confirm their morphology and crystallinity. The optimum conditions were a CH 4 flow rate of 100 ml/min in a H 2 -Ar mixture at a flow rate of 500 ml/min and a reaction time of 20 min. Under these conditions, MWCNTs with average outer and inner diameters of around 50 and 10 nm, respectively, were obtained. SiO 2 particles with embedded MWCNTs were studied for their adsorption of gaseous chlorinated phenolic compounds (CPCs), with emphasis on the effect of number of chlorine substituents. The CPC compounds of 2-chlorophenol (CP) and 2,4-dichlorophenol (DCP) were compared against phenol (P). Adsorption of P and CPCs on the particles fit well the Langmuir isotherm. The adsorption capacities of P, CP, and DCP on SiO 2 particles with embedded MWCNTs were found to be 3.12, 13.83, and 44.25 mg/g, respectively. Desorption activation energy was determined by thermogravimetric analysis. Chlorine substitution on P changed the adsorption process from physical to chemical adsorption. The particles showed high potential for use as a pre-concentration unit for solid-phase microextraction.

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Modeling the dioxin emission of a municipal solid waste incinerator using neural networks

Cited by 69 publications

References 36 publications

Combined heat and power production planning in a waste-to-energy plant on a short-term basis

Combined heat and power production planning in a waste-to-energy plant on a short-term basis

An Environmental Risk Evaluation Method Employing Atmospheric Dispersion Models and GIS

Influence of chlorine substitution on adsorption of gaseous chlorinated phenolics on multi-walled carbon nanotubes embedded in SiO2

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