Artificial intelligence, regression model, and cost estimation for removal of chlorothalonil pesticide by activated carbon prepared from casuarina charcoal

Mohamed Gar Alalm, Mahmoud Nasr

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13 Citations (Scopus)

Abstract

Chlorothalonil is a pesticide that can contaminate water bodies, detriment aquatic organisms, and cause cancers of the forestomach and kidney. In this study, a powdered activated carbon prepared from casuarina wood was used for the adsorption of chlorothalonil from aqueous solutions. Based on Scanning Electron microscopy and Fourier Transform Infrared Spectroscopy analyses, the adsorbent material comprised pores and multiple functional groups that favored the entrapment of chlorothalonil onto its surface. At initial chlorothalonil concentration of 480 mg L−1, the equilibrium uptake capacity was 187 mg g−1 at pH: 7, adsorbent dosage: 0.5 g L−1, contact time: 40 min, and room temperature (25 ± 4 °C). The kinetic and isotherm studies indicated that the rate constant of pseudo-second-order model (k2) was 0.003 g mg−1 min−1, and the monolayer adsorption capacity was 192 mg g−1. Results from a quadratic model demonstrated that the plot of adsorption capacity versus pH, chlorothalonil concentration, adsorbent dosage, and contact time caused quadratic-concave, linear-up, flat, and quadratic-linear concave up curves, respectively. An artificial neural network with a structure of 4–5–1 was able to predict the adsorption capacity (R2: 0.982), and the sensitivity analysis using connection weights showed that pH was the most influential factor. An economic estimation using amortization and operating costs revealed that an adsorption unit subjected to 100 m3 d−1 containing chlorothalonil concentration of 250 ± 50 mg L−1 could cost 1.18 $ m−3.

Original languageEnglish
Pages (from-to)101-110
Number of pages10
JournalSustainable Environment Research
Volume28
Issue number3
DOIs
Publication statusPublished - 1 May 2018

Fingerprint

Charcoal
artificial intelligence
Pesticides
charcoal
Activated carbon
Artificial intelligence
activated carbon
pesticide
Adsorption
Adsorbents
adsorption
cost
Costs
Aquatic organisms
Operating costs
Functional groups
Sensitivity analysis
Fourier transform infrared spectroscopy
Isotherms
aquatic organism

Keywords

  • Activated carbon
  • Artificial neural network
  • Chlorothalonil pesticide
  • Cost estimation
  • Kinetics and isotherms

ASJC Scopus subject areas

  • Environmental Engineering
  • Renewable Energy, Sustainability and the Environment
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution

Cite this

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title = "Artificial intelligence, regression model, and cost estimation for removal of chlorothalonil pesticide by activated carbon prepared from casuarina charcoal",
abstract = "Chlorothalonil is a pesticide that can contaminate water bodies, detriment aquatic organisms, and cause cancers of the forestomach and kidney. In this study, a powdered activated carbon prepared from casuarina wood was used for the adsorption of chlorothalonil from aqueous solutions. Based on Scanning Electron microscopy and Fourier Transform Infrared Spectroscopy analyses, the adsorbent material comprised pores and multiple functional groups that favored the entrapment of chlorothalonil onto its surface. At initial chlorothalonil concentration of 480 mg L−1, the equilibrium uptake capacity was 187 mg g−1 at pH: 7, adsorbent dosage: 0.5 g L−1, contact time: 40 min, and room temperature (25 ± 4 °C). The kinetic and isotherm studies indicated that the rate constant of pseudo-second-order model (k2) was 0.003 g mg−1 min−1, and the monolayer adsorption capacity was 192 mg g−1. Results from a quadratic model demonstrated that the plot of adsorption capacity versus pH, chlorothalonil concentration, adsorbent dosage, and contact time caused quadratic-concave, linear-up, flat, and quadratic-linear concave up curves, respectively. An artificial neural network with a structure of 4–5–1 was able to predict the adsorption capacity (R2: 0.982), and the sensitivity analysis using connection weights showed that pH was the most influential factor. An economic estimation using amortization and operating costs revealed that an adsorption unit subjected to 100 m3 d−1 containing chlorothalonil concentration of 250 ± 50 mg L−1 could cost 1.18 $ m−3.",
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AU - Nasr, Mahmoud

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N2 - Chlorothalonil is a pesticide that can contaminate water bodies, detriment aquatic organisms, and cause cancers of the forestomach and kidney. In this study, a powdered activated carbon prepared from casuarina wood was used for the adsorption of chlorothalonil from aqueous solutions. Based on Scanning Electron microscopy and Fourier Transform Infrared Spectroscopy analyses, the adsorbent material comprised pores and multiple functional groups that favored the entrapment of chlorothalonil onto its surface. At initial chlorothalonil concentration of 480 mg L−1, the equilibrium uptake capacity was 187 mg g−1 at pH: 7, adsorbent dosage: 0.5 g L−1, contact time: 40 min, and room temperature (25 ± 4 °C). The kinetic and isotherm studies indicated that the rate constant of pseudo-second-order model (k2) was 0.003 g mg−1 min−1, and the monolayer adsorption capacity was 192 mg g−1. Results from a quadratic model demonstrated that the plot of adsorption capacity versus pH, chlorothalonil concentration, adsorbent dosage, and contact time caused quadratic-concave, linear-up, flat, and quadratic-linear concave up curves, respectively. An artificial neural network with a structure of 4–5–1 was able to predict the adsorption capacity (R2: 0.982), and the sensitivity analysis using connection weights showed that pH was the most influential factor. An economic estimation using amortization and operating costs revealed that an adsorption unit subjected to 100 m3 d−1 containing chlorothalonil concentration of 250 ± 50 mg L−1 could cost 1.18 $ m−3.

AB - Chlorothalonil is a pesticide that can contaminate water bodies, detriment aquatic organisms, and cause cancers of the forestomach and kidney. In this study, a powdered activated carbon prepared from casuarina wood was used for the adsorption of chlorothalonil from aqueous solutions. Based on Scanning Electron microscopy and Fourier Transform Infrared Spectroscopy analyses, the adsorbent material comprised pores and multiple functional groups that favored the entrapment of chlorothalonil onto its surface. At initial chlorothalonil concentration of 480 mg L−1, the equilibrium uptake capacity was 187 mg g−1 at pH: 7, adsorbent dosage: 0.5 g L−1, contact time: 40 min, and room temperature (25 ± 4 °C). The kinetic and isotherm studies indicated that the rate constant of pseudo-second-order model (k2) was 0.003 g mg−1 min−1, and the monolayer adsorption capacity was 192 mg g−1. Results from a quadratic model demonstrated that the plot of adsorption capacity versus pH, chlorothalonil concentration, adsorbent dosage, and contact time caused quadratic-concave, linear-up, flat, and quadratic-linear concave up curves, respectively. An artificial neural network with a structure of 4–5–1 was able to predict the adsorption capacity (R2: 0.982), and the sensitivity analysis using connection weights showed that pH was the most influential factor. An economic estimation using amortization and operating costs revealed that an adsorption unit subjected to 100 m3 d−1 containing chlorothalonil concentration of 250 ± 50 mg L−1 could cost 1.18 $ m−3.

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