Technical Papers
Jul 24, 2023

Remediation of NAPL-Contaminated Brackish Water by Synthesized Organoclay: Experimental Analysis and BNN Predictive Model

Publication: Journal of Hazardous, Toxic, and Radioactive Waste
Volume 27, Issue 4

Abstract

This study aimed at synthesizing organoclay to remove benzene, toluene, ethylbenzene, and xylene (BTEX) and phenol as nonaqueous phase liquid (NAPL) from brackish water. The cetyltrimethylammonium bromide (CTAB) was used to synthesize organoclay owing to its high hydrophobicity and capability to adsorb aromatic and phenolic compounds with varying cation exchange capacities (CECs). The effects of contact time, concentration of BTEX and phenol as dense nonaqueous phase liquids (DNAPL) and light nonaqueous phase liquids (LNAPL), and organoclay CECs on the removal of contaminants were studied. The adsorption capacity of the synthesized organoclay was determined. Scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR) tests were conducted to investigate the characteristics of the synthesized organoclay. A Bayesian neural network (BNN) was developed to predict the experimental adsorption capacity accounting for uncertainties. The structure and postadsorption changes in the organoclay bonds were probed via FTIR tests. The results indicate that BTEX and phenol removal efficiencies were 95.6% and 68%–84%, respectively. The measured adsorption capacity for benzene, toluene, ethylbenzene, and xylene were 4.7, 6.2, 9.2, and 7.8 g/g, respectively, relative to the initial weight of the sorbent. The developed BNN model can accurately predict the adsorption capacity of organoclay. A sensitivity analysis was performed based on optimized BNN model to examine the influence of each parameter on the adsorption capacity, which confirmed laboratory results and revealed that the optimal values of CECs are approximately 150%–200%. Given the high removal capacity and ease of synthesis, it was concluded that the synthesized organoclay could be an efficient and competitive alternative to existing removal systems.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

The authors are grateful to the Civil and Environmental Engineering Faculty members at Babol Noshirvani University of Technology, Iran, for their insightful remarks and thorough review of this research.

References

Adeniyi, A. G., C. A. Igwegbe, and J. O. Ighalo. 2021. “ANN modelling of the adsorption of herbicides and pesticides based on sorbate–sorbent interphase.” Chem. Afr. 4 (2): 443–449. https://doi.org/10.1007/s42250-020-00220-w.
Afolabi, I. C., S. I. Popoola, and O. S. Bello. 2020. “Machine learning approach for prediction of paracetamol adsorption efficiency on chemically modified orange peel.” Spectrochim. Acta, Part A 243: 118769. https://doi.org/10.1016/j.saa.2020.118769.
Al-Ghouti, M. A., J. Li, Y. Salamh, N. Al-Laqtah, G. Walker, and M. N. M. Ahmad. 2010. “Adsorption mechanisms of removing heavy metals and dyes from aqueous solution using date pits solid adsorbent.” J. Hazard. Mater. 176 (1–3): 510–520. https://doi.org/10.1016/j.jhazmat.2009.11.059.
Al-Muhtaseb, S. A. 2010. “Adsorption and desorption equilibria of nitrogen, methane, ethane, and ethylene on date-Pit activated carbon.” J. Chem. Eng. Data 55 (1): 313–319. https://doi.org/10.1021/je900350k.
Alalm, M. G., and M. Nasr. 2018. “Artificial intelligence, regression model, and cost estimation for removal of chlorothalonil pesticide by activated carbon prepared from casuarina charcoal.” Sustainable Environ. Res. 28 (3): 101–110. https://doi.org/10.1016/j.serj.2018.01.003.
Alam, G., I. Ihsanullah, M. Naushad, and M. Sillanpää. 2022. “Applications of artificial intelligence in water treatment for optimization and automation of adsorption processes: Recent advances and prospects.” Chem. Eng. J. 427: 130011. https://doi.org/10.1016/j.cej.2021.130011.
Asl, S. M. H., M. Masomi, and M. Tajbakhsh. 2020. “Hybrid adaptive neuro-fuzzy inference systems for forecasting benzene, toluene & m-xylene removal from aqueous solutions by HZSM-5 nano-zeolite synthesized from coal fly ash.” J. Cleaner Prod. 258: 120688. https://doi.org/10.1016/j.jclepro.2020.120688.
ASTM. n.d.-a. Standard test methods for sorbent performance of absorbents-designation. ASTM F726-99. West Conshohocken, PA: ASTM.
ASTM. n.d.-b. Standard test methods for sorbent performance of absorbents-designation. ASTM F716-82. West Conshohocken, PA: ASTM.
ASTM. 2022a. Standard test method for measuring the exchange complex and cation exchange capacity of inorganic fine-grained soils. ASTM D7503-18. West Conshohocken, PA: ASTM.
ASTM. 2022b. Standard test method for swell index of clay mineral component of geosynthetic clay liners. ASTM D5890-95. West Conshohocken, PA: ASTM.
ASTM. 2022c. Standard test methods for specific gravity. ASTM D4546. West Conshohocken, PA: ASTM.
Awad, A. M., S. M. R. Shaikh, R. Jalab, M. H. Gulied, M. S. Nasser, A. Benamor, and S. Adham. 2019. “Adsorption of organic pollutants by natural and modified clays: A comprehensive review.” Sep. Purif. Technol. 228: 115719. https://doi.org/10.1016/j.seppur.2019.115719.
Bandura, L., A. Woszuk, D. Kołodyńska, and W. Franus. 2017. “Application of mineral sorbents for removal of petroleum substances: A review.” Minerals 7 (3): 37. https://doi.org/10.3390/min7030037.
Bazrafshan, E., F. K. Mostafapour, and H. J. Mansourian. 2013. “Phenolic compounds: Health effects and its removal from aqueous environments by low cost adsorbents.” Health Scope 2 (2): 65–66. https://doi.org/10.17795/jhealthscope-12993.
Bouhedda, M., S. Lefnaoui, S. Rebouh, and M. M. Yahoum. 2019. “Predictive model based on adaptive neuro-fuzzy inference system for estimation of cephalexin adsorption on the octenyl succinic anhydride starch.” Chemom. Intell. Lab. Syst. 193: 103843. https://doi.org/10.1016/j.chemolab.2019.103843.
Burns, S. E., S. L. Bartelt-Hunt, J. A. Smith, and A. Z. Redding. 2006. “Coupled mechanical and chemical behavior of bentonite engineered with a controlled organic phase.” J. Geotech. Geoenviron. Eng. 132 (11): 1404–1412. https://doi.org/10.1061/(ASCE)1090-0241(2006)132:11(1404).
Carvalho, M. N., M. da Motta, M. Benachour, D. C. S. Sales, and C. A. M. Abreu. 2012. “Evaluation of BTEX and phenol removal from aqueous solution by multi-solute adsorption onto smectite organoclay.” J. Hazard. Mater. 239–240: 95–101. https://doi.org/10.1016/j.jhazmat.2012.07.057.
Chidi, O., O. U. Nnanna, and O. P. Ifedi. 2018. “The use of organophilic bentonite in the removal phenol from aqueous solution: Effect of preparation techniques.” Mod. Chem. Appl. 6 (2). https://doi.org/10.4172/2329-6798.1000258.
Chittoo, B. S., and C. Sutherland. 2020. “Column breakthrough studies for the removal and recovery of phosphate by lime-iron sludge: Modeling and optimization using artificial neural network and adaptive neuro-fuzzy inference system.” Chin. J. Chem. Eng. 28 (7): 1847–1859. https://doi.org/10.1016/j.cjche.2020.02.022.
Chuang, Y.-H., C.-H. Liu, Y.-M. Tzou, J.-S. Chang, P.-N. Chiang, and M.-K. Wang. 2010. “Comparison and characterization of chemical surfactants and bio-surfactants intercalated with layered double hydroxides (LDHs) for removing naphthalene from contaminated aqueous solutions.” Colloids Surf., A 366 (1–3): 170–177. https://doi.org/10.1016/j.colsurfa.2010.06.009.
Dabbaghi, F., A. Tanhadoust, M. L. Nehdi, M. Dehestani, and H. Yousefpour. 2022. “Investigation on optimal lightweight expanded clay aggregate concrete at high temperature based on deep neural network.” Struct. Concr. 23 (6): 3727–3753.
Dabbaghi, F., A. Tanhadoust, M. L. Nehdi, S. Nasrollahpour, M. Dehestani, and H. Yousefpour. 2021. “Life cycle assessment multi-objective optimization and deep belief network model for sustainable lightweight aggregate concrete.” J. Cleaner Prod. 318: 128554. https://doi.org/10.1016/j.jclepro.2021.128554.
Dalhat, M. A., N. D. Mu’azu, and M. H. Essa. 2021. “Generalized decay and artificial neural network models for fixed-bed phenolic compounds adsorption onto activated date palm biochar.” J. Environ. Chem. Eng. 9 (1): 104711. https://doi.org/10.1016/j.jece.2020.104711.
Djebbar, M., F. Djafri, M. Bouchekara, and A. Djafri. 2012. “Adsorption of phenol on natural clay.” Appl. Water Sci. 2 (2): 77–86. https://doi.org/10.1007/s13201-012-0031-8.
Elemen, S., E. P. A. Kumbasar, and S. Yapar. 2012. “Modeling the adsorption of textile dye on organoclay using an artificial neural network.” Dyes Pigm. 95 (1): 102–111. https://doi.org/10.1016/j.dyepig.2012.03.001.
Fatimah, I., W. Novita, Y. Andika, I. Sahroni, and B. Djaelani. 2013. “Organoclay of cetyl trimethyl ammonium–montmorillonite: Preparation and study in adsorption of benzene–toluene-2–chlorophenol.” Int. J. Chem. Mol. Eng. 7 (6): 836–839.
Froehner, S., R. F. Martins, W. Furukawa, and M. R. Errera. 2009. “Water remediation by adsorption of phenol onto hydrophobic modified clay.” Water Air Soil Pollut. 199 (1–4): 107–113. https://doi.org/10.1007/s11270-008-9863-0.
Gentry, J. L., M. R. Niemet, D. G. Grubb, M. Bruno, D. R. V. Berggren, and C. D. Tsiamis. 2015. “Gowanus canal superfund site. II: Stabilization/solidification of MGP-impacted sediments.” J. Hazard. Toxic Radioact. Waste 19 (1): C4014004. https://doi.org/10.1061/(ASCE)HZ.2153-5515.0000252.
Ghaedi, A. M., and A. Vafaei. 2017. “Applications of artificial neural networks for adsorption removal of dyes from aqueous solution: A review.” Adv. Colloid Interface Sci. 245: 20–39. https://doi.org/10.1016/j.cis.2017.04.015.
Ghavami, M. 2017. “Cationic surfactant modification and its impact on the engineering behaviors of montmorillonite.” Ph.D. thesis, Dept. of Civil Engineering, Babol Noshirvani Univ. of Technology.
Ghavami, M., D. Yousefi Kebria, S. Javadi, and O. Ghasemi-Fare. 2019. “Cement–organobentonite admixtures for stabilization/solidification of PAH-contaminated soil: A laboratory study.” Soil Sediment Contam. 28 (3): 304–322. https://doi.org/10.1080/15320383.2018.1564734.
Gürses, A., M. Ejder-Korucu, and Ç Doǧar. 2012. “Preparation of PEO/clay nanocomposites using organoclay produced via micellar adsorption of CTAB.” Sci. World J. 2012: 270452. https://doi.org/10.1100/2012/270452.
Hosseinzadeh, A., A. A. Najafpoor, A. J. Jafari, R. K. Jazani, M. Baziar, H. Bargozin, and F. G. Piranloo. 2018. “Application of response surface methodology and artificial neural network modeling to assess non-thermal plasma efficiency in simultaneous removal of BTEX from waste gases: Effect of operating parameters and prediction performance.” Process Saf. Environ. Prot. 119: 261–270. https://doi.org/10.1016/j.psep.2018.08.010.
Hou, B., R. Zhang, X. Liu, Y. Li, P. Liu, and J. Lu. 2021. “Study of membrane fouling mechanism during the phenol degradation in microbial fuel cell and membrane bioreactor coupling system.” Bioresour. Technol. 338: 125504. https://doi.org/10.1016/j.biortech.2021.125504.
Huang, R., D. Zheng, B. Yang, and B. Wang. 2012. “Preparation and simultaneous sorption of CTMAB–HTCC bentonite towards phenol and Cd(II).” Desalin. Water Treat. 44 (1–3): 276–283. https://doi.org/10.1080/19443994.2012.691769.
Ikhtiyarova, G. A., A. S. Özcan, Ö Gök, and A. Özcan. 2012. “Characterization of natural- and organobentonite by XRD, SEM, FT-IR and thermal analysis techniques and its adsorption behaviour in aqueous solutions.” Clay Miner. 47 (1): 31–44. https://doi.org/10.1180/claymin.2012.047.1.31.
Karpińska, J., and U. Kotowska. 2019. “Removal of organic pollution in the water environment.” Water 11 (10): 2017. https://doi.org/10.3390/w11102017.
Lazorenko, G., A. Kasprzhitskii, and V. Yavna. 2020. “Comparative study of the hydrophobicity of organo-montmorillonite modified with cationic, amphoteric and nonionic surfactants.” Minerals 10 (9): 732. https://doi.org/10.3390/min10090732.
Mahmoud, A. S., A. Ismail, M. K. Mostafa, M. S. Mahmoud, W. Ali, and A. M. Shawky. 2020. “Isotherm and kinetic studies for heptachlor removal from aqueous solution using Fe/Cu nanoparticles, artificial intelligence, and regression analysis.” Sep. Sci. Technol. 55 (4): 684–696. https://doi.org/10.1080/01496395.2019.1574832.
Mahmoud, A. S., M. K. Mostafa, and S. A. Abdel-Gawad. 2018. “Artificial intelligence for the removal of benzene, toluene, ethyl benzene and xylene (BTEX) from aqueous solutions using iron nanoparticles.” Water Supply 18 (5): 1650–1663. https://doi.org/10.2166/ws.2017.225.
Maiti, S., V. C. Erram, G. Gupta, R. K. Tiwari, U. D. Kulkarni, and R. R. Sangpal. 2013. “Assessment of groundwater quality: A fusion of geochemical and geophysical information via Bayesian neural networks.” Environ. Monit. Assess. 185 (4): 3445–3465. https://doi.org/10.1007/s10661-012-2802-y.
Mallakpour, S., and M. Dinari. 2011. “Preparation and characterization of new organoclays using natural amino acids and Cloisite Na+.” Appl. Clay Sci. 51 (3): 353–359. https://doi.org/10.1016/j.clay.2010.12.028.
Marshall, T., K. M. Estepa, M. Corradini, A. G. Marangoni, B. Sleep, and E. Pensini. 2020. “Selective solvent filters for non-aqueous phase liquid separation from water.” Sci. Rep. 10 (1): 1–13. https://doi.org/10.1038/s41598-019-56847-4.
Masooleh, M. S., S. Bazgir, M. Tamizifar, and A. Nemati. 2010. “Adsorption of petroleum hydrocarbons on organoclay archive of SID.” J. Appl. Chem. Res. 4 (14): 19–23.
Mohebbi, M., S. Gitipour, and E. Madadian. 2013. “Solidification/stabilization of cresol-contaminated soil: Mechanical and leaching behavior.” Soil Sediment Contam. 22 (7): 783–799. https://doi.org/10.1080/15320383.2013.768203.
Nafees, M., and A. Waseem. 2014. “Organoclays as sorbent material for phenolic compounds: A review.” CLEAN—Soil Air Water 42 (11): 1500–1508. https://doi.org/10.1002/clen.201300312.
Nasrollahpour, S., D. Y. Kebria, and M. Ghavami. 2019. “Remediation of phenol-contaminated aqueous solutions by synthesized organoclay.” Iran. J. Energy Environ. 10 (4): 242–247.
Nasrollahpour, S., D. Y. Kebria, M. Ghavami, and O. Ghasemi-Fare. 2020. “Application of organically modified clay in removing BTEX from produced water.” In Proc., Geo-Congress 2020: Geo-Systems, Sustainability, Geoenvironmental Engineering, and Unsaturated Soil Mechanics, edited by J. P. Hambleton, R. Makhnenko, and A. S. Budge, 275–283. Reston, VA: ASCE.
Nourmoradi, H., M. Nikaeen, and M. Khiadani (Hajian). 2012. “Removal of benzene, toluene, ethylbenzene and xylene (BTEX) from aqueous solutions by montmorillonite modified with nonionic surfactant: Equilibrium, kinetic and thermodynamic study.” Chem. Eng. J. 191: 341–348. https://doi.org/10.1016/j.cej.2012.03.029.
Onwuka, K. E., P. O. Emole, J. C. Igwe, and O. C. Atasie. 2022. “"Monitoring BTEX adsorption on to organoclays in aqueous solution: Multi-isotherm and kinetics studies".” Biomed. J. Sci. Tech. Res. 41 (5): 33143–33163. https://doi.org/10.26717/BJSTR.2022.41.006678.
Park, Y., G. A. Ayoko, and R. L. Frost. 2011. “Characterisation of organoclays and adsorption of p-nitrophenol: Environmental application.” J. Colloid Interface Sci. 360 (2): 440–456. https://doi.org/10.1016/j.jcis.2011.04.085.
Salehi, T., and D. Yousefi Kebria. 2020. “Synergy of granular activated carbon and anaerobic mixed culture in phenol bioremediation of aqueous solution.” Iran. J. Energy Environ. 11 (3): 178–185.
Saputera, W. H., A. S. Putrie, A. A. Esmailpour, D. Sasongko, V. Suendo, and R. R. Mukti. 2021. “Technology advances in phenol removals: Current progress and future perspectives.” Catalysts 11 (8): 998. https://doi.org/10.3390/catal11080998.
Sarkar, B., R. Rusmin, U. C. Ugochukwu, R. Mukhopadhyay, and K. M. Manjaiah. 2019. “Modified clay minerals for environmental applications.” In Modified clay and zeolite nanocomposite materials: Environmental and pharmaceutical applications, edited by M. Mercurio, B. Sarkar, and A. Langella, 113–127. Amsterdam, Netherlands: Elsevier.
Sarkar, B., Y. Xi, M. Mallavarapu, G. S. R. Krishnamurti, and R. Naidu. 2010. “Adsorption of phenol by HDTMA-modified organoclay.” In Proc., 19th World Congress of Soil Science, Soil Solutions for a Changing World. Vienna, Austria: International Union of Soil Sciences.
Shahryari, Z., A. Sharifi, and A. Mohebbi. 2013. “Artificial neural network (ANN) approach for modeling and formulation of phenol adsorption onto activated carbon.” J. Eng. Thermophys. 22 (4): 322–336. https://doi.org/10.1134/S181023281304005X.
Sharafi, K., M. Pirsaheb, V. K. Gupta, S. Agarwal, M. Moradi, Y. Vasseghian, and E.-N. Dragoi. 2019. “Phenol adsorption on scoria stone as adsorbent—Application of response surface method and artificial neural networks.” J. Mol. Liq. 274: 699–714. https://doi.org/10.1016/j.molliq.2018.11.006.
Sharafimasooleh, M., S. Bazgir, M. Tamizifar, and A. Nemati. 2011. “Adsorption of hydrocarbons on modified nanoclays.” IOP Conference Series: Materials Science and Engineering, 182012. Bristol, UK: IOP Publishing.
Słomkiewicz, P., B. Szczepanik, and M. Czaplicka. 2020. “Adsorption of phenol and chlorophenols by HDTMA modified halloysite nanotubes.” Materials 13 (15): 3309. https://doi.org/10.3390/ma13153309.
Słoński, M. 2005. “Prediction of concrete fatigue durability using Bayesian neural networks.” Comput. Assisted Mech. Eng. Sci. 12 (2–3): 259–265.
Słoński, M. 2011. “Bayesian neural networks and Gaussian processes in identification of concrete properties.” Comput. Assisted Mech. Eng. Sci. 18 (4): 291–302.
Song, D.-I., J. Choi, and W. S. Shin. 2021. “The modified song isotherm model: Application to multisolute sorption of phenols in organoclays using the ideal adsorbed solution theory.” Environ. Technol. 42 (10): 1591–1602. https://doi.org/10.1080/09593330.2019.1674929.
Theobald, C., F. Pennerath, B. Conan-Guez, M. Couceiro, and A. Napoli. 2021. “A Bayesian neural network based on dropout regulation.” Workshop on Uncertainty in Machine Learning (WUML) at ECML-PKDD Conference. https://doi.org/10.48550/arXiv.2102.01968.
Yapar, S., V. Ozbudak, A. Dias, and A. Lopes. 2005. “Effect of adsorbent concentration to the adsorption of phenol on hexadecyl trimethyl ammonium–bentonite.” J. Hazard. Mater. 121 (1–3): 135–139. https://doi.org/10.1016/j.jhazmat.2005.01.021.
Zango, Z. U., K. Jumbri, H. F. M. Zaid, N. S. Sambudi, and J. Matmin. 2021. “Optimizations and artificial neural network validation studies for naphthalene and phenanthrene adsorption onto NH2-UiO-66(Zr) metal-organic framework.” IOP Conf. Ser.: Earth Environ. Sci. 842: 012015. https://doi.org/10.1088/1755-1315/842/1/012015.
Zhang, P., Z.-Y. Yin, and Y.-F. Jin. 2022. “Bayesian neural network-based uncertainty modelling: Application to soil compressibility and undrained shear strength prediction.” Can. Geotech. J. 59 (4): 546–557. https://doi.org/10.1139/cgj-2020-0751.
Zhu, R., J. Zhu, F. Ge, and P. Yuan. 2009. “Regeneration of spent organoclays after the sorption of organic pollutants: A review.” J. Environ. Manage. 90 (11): 3212–3216. https://doi.org/10.1016/j.jenvman.2009.06.015.
Zhuang, G., Z. Zhang, M. Fu, X. Ye, and L. Liao. 2015. “Comparative study on the use of cationic–nonionic–organo–montmorillonite in oil-based drilling fluids.” Appl. Clay Sci. 116–117: 257–262. https://doi.org/10.1016/j.clay.2015.04.004.

Information & Authors

Information

Published In

Go to Journal of Hazardous, Toxic, and Radioactive Waste
Journal of Hazardous, Toxic, and Radioactive Waste
Volume 27Issue 4October 2023

History

Received: Nov 7, 2022
Accepted: May 12, 2023
Published online: Jul 24, 2023
Published in print: Oct 1, 2023
Discussion open until: Dec 24, 2023

Permissions

Request permissions for this article.

Authors

Affiliations

Sepideh Nasrollahpour [email protected]
Dept. of Civil Engineering, Lassonde School of Engineering, York Univ., Toronto, ON M3J 2S5, Canada. Email: [email protected]
Dept. of Civil and Environmental Engineering, Babol Noshirvani Univ. of Technology, Babol 4714873113, Iran (corresponding author). ORCID: https://orcid.org/0000-0001-7983-1568. Email: [email protected]
Moncef L. Nehdi [email protected]
Dept. of Civil Engineering, McMaster Univ., Hamilton, ON L8S 4L8, Canada L8S 4L8. Email: [email protected]
Dept. of Civil Engineering, Isfahan Univ. of Technology (IUT), Isfahan 8415683111, Iran. ORCID: https://orcid.org/0000-0002-1551-5707. Email: [email protected]
Mohammad Ghavami [email protected]
Dept. of Civil Engineering, Univ. of Louisville, Louisville, KY 40292. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share