Fuzzy modeling of arsenic removal process from groundwater by iron oxide nanoparticles

Document Type : Original Article

Authors

1 Department of geology, Faculty of natural science, University of Tabriz, Tabriz city, Iran

2 Department of geology, Faculty of natural science, University of Tabriz

3 Department of geology, Faculty of natural science, University of Tabriz, Tabriz, Iran

4 University of Tabriz, Tabriz, Iran

Abstract

In recent studies in Iran, arsenic anomalies have shown in excess of the WHO standard (10 ppb) in water resources that the use this water has irreparable effects on human health. Therefore, it is necessary to offer a solution for reducing the arsenic anomalies. In recent years, nanoparticles have been used to reduce the arsenic concentration in water resources at syntheses samples. However, the performance of these nanoparticles to reduce the arsenic concentration in groundwater resources, which generally have different complexes, has not been investigated. In this study, iron oxide nanoparticles have been used to reduce the arsenic anomalies from groundwater resources. Previous studies on iron oxide nanoparticles have been to isolate arsenic added in the laboratory, but the main challenge of this study is the separation of arsenic from groundwater sample. The results of investigation the effective various parameters such as pH, temperature, filtration time and the adsorbent amount on the separation of arsenic from groundwater showed that the highest separation is the temperature conditions above ambient temperature, low pH, time 5 to 15 minutes and the adsorbent amount 0.3 g. Finally, Sugeno fuzzy model was used to simulate and model the process of removing arsenic pollutants from groundwater sources. The fuzzy model results showed this model is very efficient for approximate prediction of arsenic adsorption by iron oxide nanoparticles with NRMSE = 0.03 and R2 = 0.8.

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Main Subjects


اسدی، م.، م. پیروزمند، و م. خاتمیان اسکویی. 1394. سنتز 41-Ni/MCM به روش پساسنتز و مستقیم و مقایسه کارایی آن‌‌‌ها با نانو ذرات نیکل در جذب Co2. پایان‌نامه کارشناسی ارشد نانوشیمی، دانشگاه تبریز.
پورمحمدی، پ.، م. فراستی، ب. فرهادی و م. پیرصاحب. 1398. بررسی تأثیر غلظت جریان ورودی به ستون بستر ثابت بر روی حذف کادمیم توسط جاذب کنوکارپوس. نشریه مهندسی آبیاری و آب ایران، دوره 9، شماره 3، ص 194-182.
فرزی، س، م. فراستی، ب. فرهادی بانسوله و م. پیرصاحب. 1397. حذف کادمیم از محلول آبی توسط نانوساختار پوشال نیشکر. نشریه مهندسی آبیاری و آب ایران، دوره 8، شماره 3، ص 223-210.
کوهپایه‌زاده، ح.، ع. ترابیان، غ. نبی بیدهندی و ن. حبشی. 1391. تاثیر نانوذرات آهن صفر ظرفیتی بر حذف آرسنیک پنج ظرفیتی از آب آشامیدنی. نشریه آب و فاضلاب، شماره 83، ص 67-60.
ندیری، ع.ا.، ا. اصغری مقدم، ف. صادقی­اقدم و ح. آقایی. 1391. بررسی آنومالی آرسنیک موجود در منابع آب سد سهند. نشریه محیط­شناسی، دوره 38، شماره 3، ص 74-61.
Deliyanni, E.A., D.N. Bakpyannakis, A.I. Zouboulis and K.A. Matis. 2003. Sorption of As (V) ions by akaganeite-type nanocrystals. Chemosphere Journal, 50 (1): 155-163.
Hu, J.S., L.S. Zhong, W.G. Song and L.J. Wan. 2008. Synthesis of Hierarchically Structured Metal Oxides and their Application in Heavy Metal Ion Removal. Advanced Materials Journal, 20 (15): 2977-2982.
Kanel, S.R., J.M. Greneche and H. Choi. 2006. Arsenic (V) removal from groundwater using nano scale zero-valent iron as a colloidal reactive barrier material. Environmental Science & Technology Journal, 40 (6): 2045-2050.
Kanel, S.R., B. Manning, L. Charlet and H. Choi. 2005. Removal arsenic (III) from groundwater by nanoscale zero-valent iron. Environmental Science & Technology Journal, 39(5): 1291-1298.
Lata, S. and S.S. Samadder. 2016. Removal of arsenic from water using nano adsorbents and challenges: A review. Journal of Environmental Management, 166: 387-406.
Mohan, D. and J.C.U. Pittman. 2007. Arsenic removal from water/wastewater using adsorbents- a critical review. Journal of Hazardous Materials, 142 (1-2): 1-53.
Nadiri, A.A., F. Sadeghi Aghdam, R. Khatibi and A. Asghari Moghaddam. 2018. The problem of identifying arsenic anomalies in the basin of Sahand dam through risk-based ‘soft modelling’. Science of the Total Environment, 613: 693–706.
Saberi Nasr, A., M. Rezaei and M. Dashti Barmaki. 2013. Groundwater contamination analysis using Fuzzy Water Quality index (FWQI): Yazd province, Iran. Geopersia journal, 3 (1): 47-55.
Soni, R. and D.P. Shukla. 2019. Data on Arsenic (III) removal using zeolite-reduced graphene oxide composite. Journal of Data in Brief, 22: 871-877.
World health organization (WHO). 2004. Guide for drinking water quality, 3rded, Geneva.
Xu, H., B. W. Zeiger and K.S. Suslick. 2013. Sonochemical synthesis of nanomaterials. Journal of Chemical Society Reviews, Issue 7.
Zadeh, L.A. 1965. Fuzzy sets. Information and Control, 8 (3): 338–353.