Ecological Risk Assessment of Heavy Metal in the Bottom Sediment of River Surma, Bangladesh using Monte Carlo Simulation and Multivariate Statistical Analysis. Arup Acharjee Shahjalal University of Science and Technology Zia Ahmed (
[email protected] ) Shahjalal University of Science and Technology Raul Alam BRAC University Md. Saur Rahman Bangladesh Atomic Energy Commission Zhixiao Xie Florida Atlantic University Research Article Keywords: Heavy metals, Ecological risk, Surma river, Monte Carlo simulation, Multivariate statistics, Hakanson risk index Posted Date: May 17th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-499511/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License 1 Ecological risk assessment of heavy metal in the bottom sediment of River Surma, Bangladesh using Monte 2 Carlo simulation and multivariate statistical analysis. 3 1Arup Acharjee, 1*Zia Ahmed, 2Rafiul Alam, Md. Safiur Rahman3 Zhixiao Xie4 4 1 Department of Geography and Environment, Shahjalal University of Science & Technology 5 2 BRAC James P Grant School of Public Health, BRAC University 6 3 Chemistry Division, Atomic Energy Centre (AECD), Bangladesh Atomic Energy Commission, Dhaka- 7 1207, Bangladesh 8 5Department of Geosciences, Florida Atlantic University, Boca Raton, Florida, USA 9 10 *Corresponding author email:
[email protected] 11 12 13 Abstract 14 The study aims to achieve an accurate assessment of 7 heavy metals, including Cu, Fe, Mn, Zn, Ni, Pb and Cd. Data 15 were collected from 15 sampling stations and analyzed by atomic absorption spectrophotometry. The potential 16 detrimental effects of these heavy metals were evaluated by Hakanson risk index. Hakanson risk index (RI) and 17 Monte Carlo Simulation (MCS) and the ecological risk were articulated as probability distribution of Risk Index 18 values instead of single point values to estimate the uncertainties in the risk evaluation process.