Environmental Engineering
N.D. Takarina; N. Matsue; E. Johan; A. Adiwibowo; M.F.N.K. Rahmawati; S.A. Pramudyawardhani; T. Wukirsari
Abstract
BACKGROUND AND OBJECTIVES: Zeolite has been recognized as a potential adsorbent for heavy metals in water. The form of zeolite that is generally available in powder has challenged the use of zeolite in the environment. Embedding powder zeolite in a nonwoven sheet, known as a zeolite-embedded sheet can ...
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BACKGROUND AND OBJECTIVES: Zeolite has been recognized as a potential adsorbent for heavy metals in water. The form of zeolite that is generally available in powder has challenged the use of zeolite in the environment. Embedding powder zeolite in a nonwoven sheet, known as a zeolite-embedded sheet can be an alternative to solve that. Another challenge is that information and models of zeolite-embedded sheet removal efficiency are still limited. The novelty of this study is, first, the development of a zeolite-embedded sheet to remove heavy metals from water, and second, the use of the random forest method to model the heavy metal removal efficiency of a zeolite-embedded sheet in water.METHODS: The heavy metals studied were copper, lead and zinc, considering that those are common heavy metals found in water. For developing the zeolite-embedded sheet, the methods include fabrication of the zeolite-embedded sheet using a heating procedure and heavy metals adsorption treatment using the zeolite-embedded sheet. The machine learning analysis to model the heavy metal removal efficiency using zeolite-embedded sheet was performed using the random forest method. The random forest models were then validated using the root mean square error, mean square of residuals, percentage variable explained and graphs depicting out-of-bag error of a random forest.FINDINGS: The results show the heavy metal removal efficiency was 5.51-95.6 percent, 42.71-98.92 percent and 13.39-95.97 percent for copper, lead and zinc, respectively. Heavy metals were reduced to 50 percent at metal concentrations of 10.355 milligram per liter for copper, 171.615 milligram per liter for lead and 4.755 milligram per liter for zinc. Based on the random forest models, the important variables affecting copper removal efficiency using zeolite-embedded sheet were its contents in water, followed by water temperature and potential of hydrogen. Conversely, lead and zinc removal efficiency was influenced mostly by potential of hydrogen. The random forest model also confirms that the high efficiency of heavy metals removal (>60 percent) will be achieved at water potential of hydrogen ranges of 4.94–5.61 and temperatures equal to 29.1 degrees Celsius.CONCLUSION: In general, a zeolite-embedded sheet can adsorb diluted heavy metals from water because there are percentages of adsorbed heavy metals. The random forest model is very useful to provide information and determine the threshold of heavy metal contents, water potential of hydrogen and temperature to optimize the heavy metal removal efficiency using a zeolite-embedded sheet and reducing pollutants in the environment.
M. Keshvardoostchokami; L. Babaei; A.A. Zamani; A.H. Parizanganeh; F. Piri
Abstract
In this study, an easy synthesized method for preparation of chitosan/iron oxide nanocomposite as a bio-sorbent has been applied. Analytical techniques such as Fourier transform infrared spectroscopy, X-ray diffraction; Field emission scanning electron microscopy and transmission electron microscopy ...
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In this study, an easy synthesized method for preparation of chitosan/iron oxide nanocomposite as a bio-sorbent has been applied. Analytical techniques such as Fourier transform infrared spectroscopy, X-ray diffraction; Field emission scanning electron microscopy and transmission electron microscopy were utilized to survey of morphological structure and the functional groups characterization. The histogram of frequency of particle size confirmed that medium size of the synthesized nanoparticles was 50 nm. Beside the obtained nanocomposite, application of chitosan as the precursor and shrimp shell as natural chitin and a natural polymer were assessed as adsorbents for decontamination of Ni2+, Cd2+ and Pb2+ as examples of heavy metals from drinking water. Batch studies were performed for adsorption experiments by changing variables such as pH, contact time and adsorbent dose. Based on the experimental sorption capacities, 58, 202 and 12 mg of Ni, Cd and Pb per g of Chitosan-Fe2O3 nanocomposite as adsorbent respectively, confirm that combination of Fe2O3 nanoparticles with chitosan makes a more efficient adsorbent than chitosan and chitin. Adsorbents in uptake of the mentioned heavy metals are in the order of Chitosan-Fe2O3 nanocomposite > chitosan> chitin. In addition, the kinetics and isotherm investigations were surveyed. Moreover, it has been shown that the synthesized nanocomposite significantly reduces the amount of the mentioned ions from the real wastewater sample.
