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Ecological Risk Indicators for Leached Heavy Metals from Coal Ash Generated at a Malaysian Power Plant

Authors :
Teh Sabariah Binti Abd Manan
Affiani Machmudah
Taimur Khan
Fauzan Kamal Mohd Yapandi
Denys Dutykh
Wan Hanna Melini Wan Mohtar
Siddhartha Pati
Hisyam Jusoh
Nur Liyana Mohd Kamal
Daud Mohamad
Nadiah W. Rasdi
Fadzli Mohamed Nazri
Salmia Beddu
Amirrudin Ahmad
Zarina Itam
Source :
Sustainability, Volume 13, Issue 18, Sustainability, Vol 13, Iss 10222, p 10222 (2021)
Publication Year :
2021
Publisher :
Multidisciplinary Digital Publishing Institute, 2021.

Abstract

The application of coal ash (CA) in construction industries has grown rapidly, posing risk to the environment due to heavy metals leaching from the material. This research presents a simulation of ecological risk assessment and model risk indicators (ERI) of leached heavy metals (lead (Pb), copper (Cu), zinc (Zn) and arsenic (As)) from CA (FA: fly ash and BA: bottom ash) via response surface methodology (RSM). The ERI values were based on quantified leached heavy metals from the toxicity characteristic leaching procedure (TCLP-1311) and synthetic precipitation leaching procedure (SPLP-1312). The ecological risk index (RI ) values for TCLP were 10.27 × 100 (FA), 9.91 × 100 (BA) and 12.58 × 100 (FA + BA)<br />whereas RI for SPLP were 10.34 × 100 (FA), 9.90 × 100 (BA) and 12.61 × 100 (FA + BA). Twenty-nine combinations of operations were evaluated based on Box-Behnken design with ERI as the response variable. The established model risk indicator (i.e., coded and actual factors) of Pb, Cu, Zn and ‘As’ showed significant model terms that describe their relationship very well, perfectly fit to the corresponding ERI (sum of squares = 0.4160, F value = 682,375.55) with probability of 0.01% for an F-value could occur due to noise. The optimized models were validated with error percentage of less than 5%. The established ERI models showed significant model terms and will be useful for ecological monitoring of CA application in construction industries.

Details

Language :
English
ISSN :
20711050
Database :
OpenAIRE
Journal :
Sustainability
Accession number :
edsair.doi.dedup.....848ca790119d92d607aded7dd816a1a8
Full Text :
https://doi.org/10.3390/su131810222