The effect of using mineral adsorbents along with nanoparticles in porous concrete to improve the quality of urban runoff

Authors

1 Department of Civil Engineering, University of Qom, Iran

2 Department of Chemical Engineering, University of Qom, Iran

3 Department of Civil Engineering, Payam Noor University, Tehran, Iran

Abstract
In the last decade, porous concrete has been considered as one of the effective options in urban runoff management, especially in sidewalks and surface pavements. In the present study, the combined performance of nanoparticles (5 wt%) and mineral adsorbents (15% zeolite, travertine, scoria and pumice) in porous concrete to improve the quality of urban runoff was investigated experimentally and numerically. The samples were evaluated in the laboratory under the passage of 10 liters of runoff for 2 hours and under constant temperature, porosity and permeability. TSS, COD and lead concentration parameters were measured before and after the runoff passage. Experimental results showed that adding pumice with 5% nanoparticles resulted in 75% lead removal, combining 10% zeolite with 5% nanoparticles resulted in 32% TSS removal and 15% zeolite with 2% nanoparticles resulted in 23% COD reduction. In numerical simulation using COMSOL Multiphysics, after calibrating the model with laboratory data, lead removal was reproduced to approximately 80% (with an error of about 20% compared to the experiment) and TSS and COD removal were reproduced to 17% and 9%, respectively (difference of 14–15%). The results show that the addition of inorganic adsorbents and nanoparticles, by reducing pores and increasing the contact surface, plays an effective role in the absorption of physical and chemical pollutants in runoff.

Keywords


1.Kahrizi, E., Rajaee, T., & Sedighi, M. (2024). Probabilistic and Experimental Investigation of the Effect of Mineral Adsorbents on Porous Concrete Using Kriging, PRSM, and RBF Methods. Journal of Architectural Engineering, 30(1), 04023010. https://doi.org/10.1061/AJRUA6.0001258
2.Mousavi, S.-F., et al., Effects of adding mineral adsorbents to porous concrete for enhancing the quality performance of urban runoff systems. 2018. 15(4): p. 489-497. https:// doi.org/10.1108/WJE-10-2017-0314
3.Salari, M., E. Teymouri, and Z.J.J.o.E.T.T. Nassaj, Application of an artificial neural network model for estimating of water quality parameters in the karun river, Iran. 2021. 9(4): p. 720-727. https://doi.org/10.47277/JETT/9(4)727
4.طهرانی، م.ج، و دیگران، بهینه سازی طرح اختلاط بتن متخلخل به منظور کاهش رواناب معابر شهری. 2020.)24 (2 https://doi.org/10.47176/jwss.24.2.1011
5.خسروی، و دیگران، حذف فلزات سنگین دو ظرفیتی (کادمیم، کبالت، روی و سرب) و آمونیوم از پساب ها با استفاده از زئولیت طبیعی استان آذربایجان غربی. 2011. (6(20:ص 61-74. https://doi.org/10.22075/chem.2017.586
6.  Committee, A. Guide for selecting proportions for no-slump concrete reported by ACI committee 211. in American Concrete Institute. 2002.
7.  Sonebi, M. and M. Bassuoni, Investigating the effect of mixture design parameters on pervious concrete by statistical modelling. Construction and Building Materials, 2013. 38: p. 147-154. https://doi.org/10.1016/j.conbuildmat.2012.07.044
8.Xu, F., et al., Influence of aggregate reinforcement treatment on the performance of geopolymer recycled aggregate permeable concrete: From experimental studies to PFC 3D simulations. Construction and Building Materials, 2022. 354: p. 129222. https://doi.org/10.1016/j.conbuildmat.2022.129222
9.Zhao, H., Q. Geng, and X. Liu, Influence of freeze–thaw cycles on mechanical properties of pervious concrete: From experimental studies to discrete element simulations. Construction and Building Materials, 2023. 409: p. 133988. https://doi.org/10.1016/j.conbuildmat.2023.133988
10.Li, J., et al., Performance Simulation of Permeable Concrete Materials Combined with Nanotechnology in Rainwater Management. Processes, 2023. 11(3): p. 768. https://doi.org/10.3390/pr11030768
11. Wen, F., et al., A simplified numerical simulation of uniaxial compression for polyacrylonitrile fiber reinforced permeable concrete based on CT images. Construction and Building Materials, 2024. 411: p. 134319. https://doi.org/10.1016/j.conbuildmat.2023.134319
12.Ahmad, S.A., et al., Mathematical modeling techniques to predict the compressive strength of pervious concrete modified with waste glass powders. Asian Journal of Civil Engineering, 2024. 25(1): p. 773-785. https://doi.org/10.1007/s42107-023-00811-1
13.Jackson, P.J., P.J.L.s.c.o.c. Hewlett, and concrete, Portland cement: classification and manufacture. 1998. 4: p. 25-94.
14.Concreate, A.J.A.I., Standard specification for lightweight aggregates for structural concrete. 2017. 10.1520/C0330_C0330M-17A
15.ASTM, Standard test method for density and void content of freshly mixed pervious concrete. 2014, ASTM international West Conshohocken, PA. 10.1520/C1754-14
16.Institutions, B.S., method for Making Test Cubes from Fresh Concrete. 1881, BS.
17.Concrete, A.C.J.G.o.S.P.f.N.-S., Comittee 211–ACI 211.3 R-97. 1977. https://www.concrete.org/publications/internationalconcreteabstractsportal/m/details/id/5094
18. 522, A.C. ACI Committee 522. (2006), "Pervious Concrete", ACI 522R-06 Report. 2006. American Concrete Institute. https://www.concrete.org/publications/internationalconcreteabstractsportal/m/details/id/15614
19.Ani, E.-C., et al., Dynamic Simulation of Someº River Pollution Using MATLAB and COMSOL Models. 2010.https://www.researchgate.net/publication/228417660_Dynamic_Simulation_of_Some_River_Pollution_Using_MATLAB_and_COMSOL_Models
20.Multiphysics, C.J.C.M., Burlington, MA, accessed Feb, Introduction to COMSOL multiphysics®. 1998. 9(2018): p. 32. https://cdn.comsol.com/doc/5.5/IntroductionToCOMSOLMultiphysics.pdf

  • Receive Date 26 July 2025
  • Revise Date 23 September 2025
  • Accept Date 28 October 2025
  • First Publish Date 28 October 2025
  • Publish Date 23 September 2025