Parametric sensitivity analysis for typical heavy metals migration and transformation model in electroplating industrial area of Jingjiang City 靖江市某电镀集中区典型重金属迁移转化模型参数灵敏性分析

Pang，Min1; Xie，Rongrong2,3; Zhu，Tianyi4; Chen，Zhiqi5,6; Pang，Yong5,6

2021-12-26

10.13671/j.hjkxxb.2021.0377

环境科学学报   影响因子和分区

0253-2468

With the increasing risk of potential heavy metal pollution, the development of heavy metal migration and transformation models as well as the prediction of their fate in aquatic environments have attracted extensive attention. Optimizing the model parameters becomes particularly important to promote the accuracy of the model. In this study, the heavy metals (Ni and Cu) simulation model for an electroplating industrial area was constructed. Taking Ni as an example, the parametric sensitivity analyses for model were performed using the Standardized Rank Regression Coefficient (SRRC) and the Mars-Sobol methods. Two sensitive parameters were applied for model calibration and verification to improve the accuracy and efficiency in simulations. Results suggested that the sensitivity of the water-sediment Ni distribution coefficients obtained using SRRC method was between 96.1% and 99.7% (99.2% in average), and the sediment deposition rate was identified from 0.1% to 3.3% (0.5% in average). By using Mars-Sobol method, the total sensitivity of the water-sediment Ni distrubution coefficients was determined in a range of 87.18% and 93.44% (90.28% in average), and the sediment deposition rate was in a range of 5.68% to 10.68% (8.21% in average). Our results revealed that the sensitivity of water-sediment Ni distribution coefficients decreased along the flow direction, while the sediment deposition rate displayed an increasing trend. Compared with SRRC method, Mars-Sobol model had an higher accuracy in predictions with the consideration of interactions between multiple parameters. By carefully calibrating and verifying two sensitive parameters (i.e. water-sediment distribution coefficient and sediment deposition rate), the maximum relative errors of Ni and Cu models were reduced within 15.28% and 14.46%, respectively. Our work suggests the prediction accuracy and efficiency of heavy metal model could be achieved by optimizing sensitive parameters.

Heavy metal Mars-Sobol Model Parameter Sensitivity analysis SRRC

中文

第一

2-s2.0-85121141776

Scopus

1.College of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
2.College of Environmental Science and Engineering,Fujian Normal University,Fuzhou,350007,China
3.Key Laboratory of Pollution Control and Resource Recycling of Fujian Province,Fujian Normal University,Fuzhou,350007,China
4.Shanghai Investigation,Design and Research Nstitute,Shanghai,200335,China
5.College of Environment,Hohai University,Nanjing,210098,China
6.Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes of Ministry of Education,Hohai University,Nanjing,210098,China

Pang，Min,Xie，Rongrong,Zhu，Tianyi,等. Parametric sensitivity analysis for typical heavy metals migration and transformation model in electroplating industrial area of Jingjiang City 靖江市某电镀集中区典型重金属迁移转化模型参数灵敏性分析[J]. 环境科学学报,2021,41(12):5107-5116.

Pang，Min,Xie，Rongrong,Zhu，Tianyi,Chen，Zhiqi,&Pang，Yong.(2021).Parametric sensitivity analysis for typical heavy metals migration and transformation model in electroplating industrial area of Jingjiang City 靖江市某电镀集中区典型重金属迁移转化模型参数灵敏性分析.环境科学学报,41(12),5107-5116.

Pang，Min,et al."Parametric sensitivity analysis for typical heavy metals migration and transformation model in electroplating industrial area of Jingjiang City 靖江市某电镀集中区典型重金属迁移转化模型参数灵敏性分析".环境科学学报 41.12(2021):5107-5116.