Trends in Environmental Sustainability and Green Energy: Proceedings of the 6th International Conference on Green Energy and Environment Engineering ... in Earth and Environmental Sciences) [1st ed. 2024] 3031523296, 9783031523298

Table of contents :
Preface
Conference Committees
Contents
Wastewater Treatment, Water Quality Analysis, and Water Resource Management
Black Iron Electrode/Persulfate System: A Reduction Method for Ammonia, Oil and Grease, TSS, and COD Content of Septage Wastewater via Electrocoagulation
1 Introduction
2 Methodology
2.1 Electrocoagulation (EC) Reactor
2.2 Electrocoagulation with Persulfate Additive
2.3 Electrocoagulation Analysis
3 Results and Discussion
4 Conclusion
References
Analysis of Potable Water Supply Scenarios Using WEAP Software and Applied to the Cities of Moquegua and Ilo
1 Introduction
2 Method
2.1 Methodology and Tools
2.2 Study Area
2.3 Description of the WEAP Hydrological Model
2.4 Collection of Meteorological Information and Records
2.5 Input Data to the WEAP Model
2.6 WEAP Software Application
2.7 Simulation of the Hydrological Model
3 Results
3.1 Calibration of the Hydrological Model
3.2 Water Balance of Water Supply in Current Scenario
3.3 Water Balance Projected to a Horizon of 50 Years (Year 2070) of Water Supply for Cities of Moquegua and Ilo
4 Validation
5 Conclusions
References
A Swift, Straightforward, and Innovative Approach for Detecting Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) in Aquatic Matrices Using Direct Immersion (DI) Three-Phase Single-Drop Microextraction (SDME) Coupled In-Line with Capillary Electrophoresis (CE)
1 Introduction
2 Materials and Methods
2.1 Chemicals and Materials
2.2 Instrumentation
2.3 DI-SDME-CE Procedure
3 Results and Discussion
3.1 Enrichment Factor of Three-Phase LLLE System
3.2 Acceptor Phase (Drop Size)
3.3 Organic Phase (Extraction Solvent)
3.4 Agitation Speed
3.5 Extraction Time
3.6 Analytical Performance
4 Conclusions
References
Adsorption of Chromium(VI) from Simulated Wastewater Using Colocasia esculenta Leaf and Petiole Fibers
1 Introduction
2 Methodology
2.1 Characterization of Adsorbents
2.2 Preparation of Cr(VI) Standard Solution
2.3 Preparation and Modification of Adsorbent
2.4 Adsorption Procedure
2.5 Statistical Tools and Treatment
3 Results and Discussion
3.1 FT-IR Analysis of Biosorbents
3.2 Effect of Contact Time
3.3 Comparative Study on the Four Studied Adsorbents
4 Conclusion
References
Debris Flow Modeling Using FLO-2D for Hazard Identification in the Rio Seco Creek
1 Introduction
2 Methodology
2.1 Methodology and Tools
3 Results and Analysis
3.1 Event Occurred on February 2, 2017
3.2 Return Period (Tr = 100 Years)
3.3 Return Period (Tr = 500 Years)
4 Validation
5 Conclusions
References
Ecological Environment Protection and Disaster Management
The Status and Practices of WEEE Management: A Case Study in Thailand
1 Introduction
2 Thailand’s WEEE-related Legislation
3 Status of WEEE Management in Thailand
4 A Case Study of WEEE Management Practices
4.1 Pre-steps of WEEE Processing
4.2 WEEE Processing
4.3 Safety, Environment, and Social Responsibility
5 Conclusions
References
Analysis of Severity of Forest Fires Through Spectral Indices in Altiplanic Zones of Peru
1 Introduction
1.1 Description of the Study Area
2 Materials and Methods
3 Results and Discussions
3.1 Vegetal Cover
3.2 Fire Severity
3.3 Vegetative Recovery
4 Conclusions
References
Natural Disaster Management Using Machine Learning for Resilient Electrical Grids
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Data Set
3.2 Preprocessing Techniques
3.3 Methodology
4 Results and Discussion
5 Conclusion
References
Renewable Energy Power Generation and Clean Energy Technology
Validation of a Model for Predicting the Performance of Evacuated Tube Solar Collectors Based on Internal Parameters of Heat Pipes
1 Introduction
1.1 Thermal Performance of the Heat Pipe
2 Multivariate Polynomial Regression Model
3 Experimental Setup
4 Experimental Results
5 Multivariate Polynomial Regression Analysis Results
5.1 The Performance of the Tube Influenced by Both the Merit Number and the Surface Area of the Insertion
5.2 Efficiency of the Evacuated Heat Pipe as a Function of the Working Fluid’s Boiling Point and Surface Area of the Insert
6 Conclusion
References
Deep Learning-Based Approach for Short-Term Solar Power Forecasting
1 Introduction
2 Methodology
3 Results
4 Conclusion
References
A Pilot–Scale Continuous Torrefier for Bagasse Quality Improvement in a Biomass Powerplant
1 Introduction
2 Materials and Method
2.1 Equipment and Procedure
2.2 Experiment Setup
2.3 Analysis of Torrefaction Performance
2.4 Ultimate Analysis and High Heating Value
3 Results and Discussions
3.1 Analysis of Bagasse Properties
4 Conclusion
References
Evaluation of Bio-Oils Produced from Rapid Heating Pyrolysis of Palm Kernel Shell-Polymer Waste Mixtures
1 Introduction
2 Methodology
2.1 Materials
2.2 Pyrolysis Experiments
2.3 Engine Combustion and Emissions Tests
3 Results and Discussion
3.1 Effects of Waste Polymer Composition on Bio-Oil Yield and Quality
3.2 Engine-Out Responses Across Engine Operational Speed Range
3.3 Reduced ESC Emissions
3.4 Empirical Correlations
4 Conclusions
References
Mixed Schiff Base and 8-hydroxyquinoline Complexes with Manganese, Iron and Zinc– Synthesis, Characterization and Properties
1 Introduction
2 Experimental
2.1 Synthesis of Schiff Base Ligand (L)
2.2 Procedure for the Synthesis of Metal Complexes with Mixed Ligands:
2.3 Gravimetric Estimation of Metals in the Complexes
2.4 The Gravimetric Estimation of Water of Crystallization
3 Results and Discussion
4 Conclusion
References
New Nanocomposite Anticorrosion Materials Based on Copper Ions for Resource and Energy Saving
1 Introduction
2 Experiment and Result
3 Summary
References
Author Index

Citation preview

Springer Proceedings in Earth and Environmental Sciences

Jinkeun Kim Zhe Chen   Editors

Trends in Environmental Sustainability and Green Energy Proceedings of the 6th International Conference on Green Energy and Environment Engineering 2023 (July 21–23, 2023)

Springer Proceedings in Earth and Environmental Sciences Series Editors Natalia S. Bezaeva, The Moscow Area, Russia Heloisa Helena Gomes Coe, Niterói, Rio de Janeiro, Brazil Muhammad Farrakh Nawaz, Institute of Environmental Studies, University of Karachi, Karachi, Pakistan

The series Springer Proceedings in Earth and Environmental Sciences publishes proceedings from scholarly meetings and workshops on all topics related to Environmental and Earth Sciences and related sciences. This series constitutes a comprehensive up-to-date source of reference on a field or subfield of relevance in Earth and Environmental Sciences. In addition to an overall evaluation of the interest, scientific quality, and timeliness of each proposal at the hands of the publisher, individual contributions are all refereed to the high quality standards of leading journals in the field. Thus, this series provides the research community with well-edited, authoritative reports on developments in the most exciting areas of environmental sciences, earth sciences and related fields.

Jinkeun Kim · Zhe Chen Editors

Trends in Environmental Sustainability and Green Energy Proceedings of the 6th International Conference on Green Energy and Environment Engineering 2023 (July 21–23, 2023)

Editors Jinkeun Kim Jeju National University Jeju, Korea (Republic of)

Zhe Chen Aalborg University Aalborg, Denmark

ISSN 2524-342X ISSN 2524-3438 (electronic) Springer Proceedings in Earth and Environmental Sciences ISBN 978-3-031-52329-8 ISBN 978-3-031-52330-4 (eBook) https://doi.org/10.1007/978-3-031-52330-4 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.

Preface

The 2023 6th International Conference on Green Energy and Environment Engineering was successfully held as physical conference at Jeju National University, Korea, during July 21–23, 2023. CGEEE conference is an annual event which has been conducted since 2018. This international event has been successfully held in Korea, Japan and other countries. The aim of the conference is to bring together innovative academics and industrial experts in the field of Green Energy and Environment Engineering to a common forum. CGEEE2023 was highlighted by outstanding keynote speeches, invited speakers, oral and poster reports. Participants came from various countries including Korea, USA, Japan, China, Thailand, Germany, Malaysia, etc. The conference will be continuously organized to provide a much effective platform for further exchange of new knowledge and perhaps potential collaboration in the research areas. The proceedings are a compilation of the accepted papers and represent an interesting outcome of the conference. All these papers were peer-reviewed by conference committee members and international experts, to guarantee their novelty, technical soundness, applicability, clarity of presentation and relevance. Topics include Wastewater Treatment, Water Quality Analysis, Water Resource Management; Ecological Environment Protection and Disaster Management; Renewable Energy Power Generation and Clean Energy Technology; etc. We are herewith extending our thankfulness to all the involved persons for actively contributing to the implementation of the conference and the technical program committee members who gave their valuable comments and suggestions for improving the papers. We also would like to thank the organizing committee, chairpersons and sponsors for their valuable input in the organization of the conference. Jinkeun Kim

Conference Committees

Conference Advisory Chairs Yongsheng Chen Jae K. Park

Georgia Institute of Technology, USA University of Wisconsin-Madison, USA

Conference Chair Hyunook Kim

University of Seoul, Korea

Conference Co-chairs Jinkeun Kim Zhe Chen

Jeju National University, Jeju, Korea Aalborg Universitet, Denmark (FIET, FIEEE)

Conference Program Chairs Yukichika Kawata Suyin Gan Keh-Chin Chang Yu Liu

Kindai University, Japan University of Nottingham Malaysia, Malaysia National Cheng Kung University, Taiwan Northwestern Polytechnical University, Shaanxi, China

International Steering Committee Tan Yiji Kristopher Ray S. Pamintuan

National Taiwan University, China Mapua University, Philippines

Publicity Chairs Saad A. EL-Sayed Kim Hanki

Zagazig University, Al-Sharqia, Egypt Korea Institute of Energy Research, South Korea

viii

Conference Committees

Technical Committee Members Suyin Gan Supachok Tanpichai Yu Liu Yarusova Sofia Borisovna Svenja Hanson Elanur Adar Kristopher Ray S. Pamintuan Yanqiang Di Adzuieen Nordin Karamanis Dimitrios Alissara Reungsang Radin Maya Saphira Radin Mohamed Saad A. El-Sayed Svetla Draganova Tzvetkova Zeeshan Haider Jaffari Keh-Chin Chang Cheng Siong Chin Radu Godina Lorant Andras Szolga Ahmad Zamani Ab Halim Hala Idrassen Sweety Vermas Sunq Won Kim Michel De Paepe Eunsung Kan Nader Nciri

The University of Nottingham Malaysia, Malaysia King Mongkut’s University of Technology, Thailand Northwestern Polytechnical University, Shaanxi, China Far-Eastern Branch of Russian Academy of Sciences, Russian University of Nottingham, Ningbo, China Artvin Coruh University, Turkey Mapua University, Philippines China Academy of Building Research & China Building Technique Group Co., Ltd. Politeknik Ungku Omar, Ipoh, Perak, Malaysia University of Patras, Greece Khon Kaen University, Thailand Universiti Tun Hussein Onn Malaysia, Malaysia Zagazig University, Al-Sharqia, Egypt University of National and World Economy, Bulgaria Chaoyang University of Technology, Taiwan National Cheng Kung University, Taiwan Newcastle University, Singapore Universidade Nove de Lisboa, Caparica, Portugal Technical University of Cluj-Napoca, Romania Universiti Malaysia Pahang, Malaysia Cadi Ayyad University, Morocco Inha University, South Korea Korea National University of Transportation, Korea Ghent University, Belgium Texas A&M University, Texas, USA Seoul National University, Seoul, Republic of Korea

Contents

Wastewater Treatment, Water Quality Analysis, and Water Resource Management Black Iron Electrode/Persulfate System: A Reduction Method for Ammonia, Oil and Grease, TSS, and COD Content of Septage Wastewater via Electrocoagulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kathlia D. Cruz, Brian Harvey A. Villanueva, Mariemme Keilsy D. Martos, Alfredo Jr. G. Asuncion, and May Joy S. Esguerra Analysis of Potable Water Supply Scenarios Using WEAP Software and Applied to the Cities of Moquegua and Ilo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Luis M. Bohorquez P., D. Kenzo Sumikawa, and Rubén E. Mogrovejo G. A Swift, Straightforward, and Innovative Approach for Detecting Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) in Aquatic Matrices Using Direct Immersion (DI) Three-Phase Single-Drop Microextraction (SDME) Coupled In-Line with Capillary Electrophoresis (CE) . . . . . . . . . . . . . . . Nader Nciri Adsorption of Chromium(VI) from Simulated Wastewater Using Colocasia esculenta Leaf and Petiole Fibers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kathlia D. Cruz, Andrei Jericho B. Regindin, Paulo Gabriel I. Rivera, Francis Marcus J. Garcia, Nam Seung Beom, Gerald C. Domingo, and May Joy S. Esguerra Debris Flow Modeling Using FLO-2D for Hazard Identification in the Rio Seco Creek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Juan Castillo S., Amehd R. Atala V., and Rubén E. Mogrovejo G.

3

12

27

41

53

Ecological Environment Protection and Disaster Management The Status and Practices of WEEE Management: A Case Study in Thailand . . . . Piyanart Sommani, Nichit Hongbin, Kanrayaphus Tipves, and Anchaleeporn Waritswat Lothongkum Analysis of Severity of Forest Fires Through Spectral Indices in Altiplanic Zones of Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. H. Ysla Huaman, E. Romero Garcia, M. O. Bacilio Hilario, and J. V. Cornejo Tueros

73

83

x

Contents

Natural Disaster Management Using Machine Learning for Resilient Electrical Grids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Amit Kumar and Hideya Yoshiuchi

95

Renewable Energy Power Generation and Clean Energy Technology Validation of a Model for Predicting the Performance of Evacuated Tube Solar Collectors Based on Internal Parameters of Heat Pipes . . . . . . . . . . . . . . . . . 107 Jean Gad Mukuna Deep Learning-Based Approach for Short-Term Solar Power Forecasting . . . . . . 119 Berny Carrera and Kwanho Kim A Pilot–Scale Continuous Torrefier for Bagasse Quality Improvement in a Biomass Powerplant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 K. Pajampa, A. Suksri, and T. Wongwuttanasatian Evaluation of Bio-Oils Produced from Rapid Heating Pyrolysis of Palm Kernel Shell-Polymer Waste Mixtures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 Victor V. C. Wong, Zheng Yuan Leong, Hoon Kiat Ng, Seyed Amirmostafa Jourabchi, and Suyin Gan Mixed Schiff Base and 8-hydroxyquinoline Complexes with Manganese, Iron and Zinc– Synthesis, Characterization and Properties . . . . . . . . . . . . . . . . . . . 151 M. Amin Mir and Syed M. Hasnain New Nanocomposite Anticorrosion Materials Based on Copper Ions for Resource and Energy Saving . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Ksenia A. Seromlyanova, Ekaterina B. Markova, Anton G. Mushtakov, and Alexander G. Cherednichenko Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

Wastewater Treatment, Water Quality Analysis, and Water Resource Management

Black Iron Electrode/Persulfate System: A Reduction Method for Ammonia, Oil and Grease, TSS, and COD Content of Septage Wastewater via Electrocoagulation Kathlia D. Cruz1,2(B) , Brian Harvey A. Villanueva2 , Mariemme Keilsy D. Martos2 , Alfredo Jr. G. Asuncion2 , and May Joy S. Esguerra3 1 School of Chemical, Biological, and Materials Engineering and Sciences, Mapúa University,

Muralla Street, Intramuros, Manila 1002, Philippines [email protected] 2 Water Quality and Wastewater Research Laboratory, Mapúa University, Muralla Street, Intramuros, Manila 1002, Philippines 3 Institutional Laboratory Management Office, Mapúa University, Muralla Street, Intramuros, Manila 1002, Philippines

Abstract. Septage wastewater is rich in ammonia that could harm human health and the environment if released in nature untreated. Recently, we reported the efficiency and cost-effectiveness of electrocoagulation in treating septage wastewater. An antioxidant like persulfate could act as electron shuttles (ES) and could potentially improve the electrochemical reaction of electrocoagulation (EC) in treating wastewater. Thus, in this research, a black iron electrode with a persulfate additive was considered in the electrocoagulation treatment of septage wastewater and several parameters was monitored through time. EC-treated samples were NH3 and TSS-free after 60 min. Likewise, COD and oil and grease were reduced to 76.30% and 91.63% respectively. Compared to our previous study, the use of persulfate additive improved the pollutants removal and the process is more cost-effective due to a lesser electrode consumption (0.25%). Keywords: Electrocoagulation · persulfate · black iron

1 Introduction Electrocoagulation (EC) is a promising approach to wastewater treatment both domestic [1–3] and industrial [4–21] wastewater [22, 23]. The efficient and low-cost performance of EC serves as an alternative for chemical coagulation treatment on wastewater [3, 24, 25]. The process of EC provides a sacrificial metal anode and electrolysis of the cathode [7] that contributes to the removal of pollutants [26]. Flocs formations are observed after EC treatment, they are less bound to water making the separation of aqueous medium and sludge/flocs by sedimentation, skimming, floatation, and filtration effective [27, 28]. In literature, black iron electrode provides efficient and cost-effective performance in treating septage wastewater [3]. Consumed black iron produces hydroxyl ions through water hydrolysis complexing with ammonia converting it to nitrogen gas [3, 7, 8]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 J. Kim and Z. Chen (Eds.): CGEEE 2023, SPEES, pp. 3–11, 2024. https://doi.org/10.1007/978-3-031-52330-4_1

4

K. D. Cruz et al.

Time difference and continuous application of electric field [23] increase the removal of pollutants during electrocoagulation [1, 27]. In treating wastewater, the time dependence of the EC must be considered to observe the efficiency of pollutant removal [2, 3, 26]. There have been many different reports of treating pollutants in septage wastewater [3, 29–34]. Recently, septage wastewater treatment through EC demonstrated an exceptional reduction of ammonia, COD, oil and grease, and TSS [3]. Septage wastewater is a form of domestic wastewater [31, 35]. The septage wastewater is composed of effluent after the removal of sludge and other solid particles, it is rich in nitrogen due to the removal of the amine group from food during digestion and released in form of urine [32, 36]. Nitrogen together with phosphates can promote eutrophication leading to harm to the environment [37, 38]. This suggests that treating septage wastewater is highly important to prevent environmental disruption. The antioxidant additive in electrocoagulation serves as an electron shuttle (ES) that improves the reduction and oxidation reaction happening in the electrode [2, 39]. Commonly, hydrogen peroxide is used as an electron shuttle [2, 4], but due to its unstable state and toxicity [40], using it as ES is less desirable as compared to when persulfate is used [2, 41]. In recent years, persulfate received more attention due to its outstanding antioxidant activity [42–46]. The high antioxidant property of persulfate reflects effective electron shuttle performance making it easier to store and more stable [42, 45, 47]. The addition of persulfate provides a synergetic effect with iron improving the electrocoagulation treatment [44]. Therefore, persulfate is a promising ES for EC treatment for septage wastewater. Electrocoagulation offers a wide range of wastewater treatment from sewage [2], textile [4, 21], tannery[5, 19], food processing [6, 12, 20, 26], refinery [10, 15], estate and municipal [1, 13, 39], and septage [3]. Hence, this study aims to reduce the pollutant such as NH3 , COD, total suspended solids (TSS), oil and grease in septage wastewater through electrocoagulation using a black iron electrode aided with persulfate as an electron shuttle [2, 3, 12]. Electrode consumption is also considered in this study to demonstrate low-cost treatment.

2 Methodology 2.1 Electrocoagulation (EC) Reactor The reactor design and specifications used in the experiment are shown in Fig. 1 and were based on our previous studies [2, 3, 12]. The use of black iron as an electrode and dimensions were based on our previous work on EC treatment of septage wastewater [3]. The black iron electrode was customized by a local metal shop in Binondo, Manila, Philippines. These electrodes were cleaned, dried, and weighed before use and were connected in a parallel bipolar manner using a DC power supply (KD3005 Korrad) at a constant current of 2A.

Black Iron Electrode/Persulfate System

5

Fig. 1. Electrode and electrocoagulation reactor design, specification [2, 3, 12]

2.2 Electrocoagulation with Persulfate Additive Septage samples were collected from Manila Water Septage Treatment Plant FTI, Taguig, Philippines. Samples were taken from effluent after the screening and grit removal of the large particles. Electrocoagulation was done using the reactor described above in triplicate using 3 L of wastewater with 0.1% persulfate additive at room temperature. Black iron electrodes were cleaned, dried, and weighed before and after use. The electrocoagulation process was done with stirring at 220 rpm and pollutants removal were monitored at 15, 30, 45, and 60 min time interval [3]. 2.3 Electrocoagulation Analysis EC-treated septage wastewater was filtered with 11µm size using Whatman filter paper to remove the biological interferences. Chemical Oxygen Demand (COD) analysis was performed through a COD highrange digestion solution (0-1500 ppm), digested with a thermodigestor (HACH DRB200), and examined with a spectrophotometer (DR6000 HACH Digital Spectrophotometer). 2mL of EC-treated septage wastewater was used in each vial digested for 2 h at 150 °C cooled and analyzed. Total Suspended Solids (TSS) analysis required 20mL while 50mL for ammonia then diluted to 100mL volumetric flask for analysis. Ammonia and TSS were measured using a spectrophotometer (DR6000 HACH Digital Spectrophotometer). Oil and grease content was determined through hexane liquid-liquid extraction using the gravimetric method. 30mL hexane per 1L of EC-treated septage wastewater was used. The final oil and grease content was determined by weighing after the hexane was evaporated with hot water and dried in an oven at 1000 °C. The pH was determined using a pH meter (Mettler Toledo FiveEasyTM). Electrode consumption was determined using Top loading Balance (Apollo GX-A Series Balance). The electrodes were dried and weighed via contant weighing method.

6

K. D. Cruz et al.

3 Results and Discussion The threat of pollutants on human health and the environment from septage wastewater is highly increasing [32, 35]. Ammonia together with oil and grease pollutes septage wastewater posing threat to natural waters and marine life when released in the nvironment untreated [3, 48, 49]. We recently reported the cost-effective and efficient ammonia, COD, TSS, and oil and grease reduction on septage wastewater using black iron electrodes through electrocoagulation [3]. Here, we investigated the use of persulfate as an additive in our EC system. Persulfate has high antioxidant properties [39] that could improve the EC performance by acting as an electron shuttle [42] to drive the electrocoagulation process more efficiently. We considered several wastewater parameters in treating septage wastewater such as NH3 , oil and grease, TSS, and COD to determine the efficiency of EC using black iron with persulfate additive. The results are shown in Fig. 2 wherein the percent removal of all the parameters considered increases with time. Interestingly, it was observed that 100% removal for ammonia and TSS were achieved after 60 min though the result is not significantly different from 30 min (99.26%) and 45 min (99.28%). This means that a shorter EC process could be considered. These results are better than those without persulfate which has only 97.8% and 95.8% ammonia and TSS removal, respectively [3]. Presumably, persulfate helps in the formation of more hydroxyl radicals that facilitate the oxidation of ammonia to nitrogen gas as well as in the formation of more in situ coagulants. Furthermore, the oil and grease removal was also improved. It was 85.20% without persulfate while 91.63% with persulfate after 60 min. The rate of increase in the percent removal concerning time is much better as well. This was a promising result because oil and grease removal is the most challenging parameter to be removed. As explained in our previous study, oil and grease removal was due to the small bubbles formed during the EC process that helped in the oil droplet collision leading to an increase in oil and grease removal efficiency. It was observed that with persulfate more small bubbles were formed, thus explaining the increased efficiency in removal. Concerning chemical oxygen demand (COD) removal, it was also improved from 54.67% (without persulfate) to 76.30% (with persulfate) removal after 60 min of EC treatment. Persulfate additive greatly improved the EC treatment on septage wastewater by greatly reducing ammonia, TSS, COD, and oil and grease compared to the previous study. Another parameter monitored in this study was the pH of the solution as shown in Fig. 3. This was measured to support the idea of hydroxyl ions formation. Indeed, the pH of the solution increased with time due to the formation of more hydroxyl ions from the electrolysis of water which promote the formation of ferric hydroxide which is the in situ coagulant. These further support the electrochemical conversion of ammonia at alkaline pH [49]. Electrocoagulation treatment highly depends on the sacrificial electrode [3]. Here, black iron was used due to its high purity and fast oxidative property driving the treatment faster [3, 7, 13, 50]. As shown in Fig. 4, the electrode consumption at 15 min was 0.05% (0.84 g) a bit higher compared to the 15-min run from the previous study [3]. Although 15 min run time has higher electrode consumption compared to the previous EC of septage wastewater when EC treatment with persulfate additive it only consumes 0.25% (4.13 g) at 60 min which is less than 0.04% from without additive [3]. Longer EC

Black Iron Electrode/Persulfate System

7

Fig. 2. Percent removal of NH3 , TSS, COD, Oil and Grease on septage wastewater after electrocoagulation treated with persulfate.

Fig. 3. pH of the solution during electrocoagulation with persulfate additive.

treatment time with persulfate additive has lower electrode consumption compared to the previous report [3]. Suggesting that EC treatment performs better with persulfate additive, prolonging the EC treatment suggests a further reduction of oil and grease and COD, and saving more electrodes. Furthermore, electrocoagulation proceeded with 2.00 A and 31V of voltage in 60 min resulting in 62W or 0.062kWh electric consumption. Further proving that electrocoagulation with antioxidant additives is much more efficient in pollutant removal on wastewater and cost-effective alternative.

8

K. D. Cruz et al.

Fig. 4. Black iron electrode consumption in EC treatment with additive persulfate of septage wastewater

4 Conclusion In this research, the performance of electrocoagulation with persulfate additive and the black iron electrode was investigated in treating septage wastewater. The high antioxidant property of persulfate improves the separation of flocs and improves the performance of EC treatment. It was found that time dependency on EC treatment is valuable for pollutant removal. The NH3 and TSS were 100% removed while COD and oil and grease were greatly reduced. It can be stated that EC treatment with persulfate additive and the black iron electrode can effectively remove the pollutant in septage wastewater by expanding the time of treatment. Electrode consumption is minimal with black iron metal, making the EC treatment cost-efficient and highly effective.

References 1. Ensano, B.M.B., et al.: Applicability of the electrocoagulation process in treating real municipal wastewater containing pharmaceutical active compounds. J. Hazard. Mater. 361, 367–373 (2019). https://doi.org/10.1016/j.jhazmat.2018.07.093 2. Cruz, K.D., Madrid, C.J.M.: Electrocoagulation-H2O2-dimethicone combined system for COD reduction and phosphate removal of sewage wastewater. In: E3S Web of Conferences, EDP Sciences (2019).. https://doi.org/10.1051/e3sconf/201911700004 3. Cruz, K.D., Villanueva, B.H.A., Martos, M.K.D., Asuncion, A.G., Esguerra, M.J.S.: Ammonia, oil and grease, and COD reduction of septage wastewater via electrocoagulation using black iron electrodes. IOP Conf. Ser. Earth Environ. Sci. (2020). https://doi.org/10.1088/ 1755-1315/612/1/012035 4. GilPavas, E., Dobrosz-Gómez, I., Gómez-García, M.Á.: Optimization and toxicity assessment of a combined electrocoagulation, H2O2/Fe2+/UV and activated carbon adsorption for textile wastewater treatment. Sci. Total. Environ. 651, 551–560 (2019). https://doi.org/10.1016/j.sci totenv.2018.09.125 5. Elabbas, S., et al.: Treatment of highly concentrated tannery wastewater using electrocoagulation: Influence of the quality of aluminium used for the electrode. J. Hazard. Mater. 319, 69–77 (2016). https://doi.org/10.1016/j.jhazmat.2015.12.067 6. Reilly, M., Cooley, A.P., Tito, D., Tassou, S.A., Theodorou, M.K.: Electrocoagulation treatment of dairy processing and slaughterhouse wastewaters. Energy Proc., 343–351 (2019). https://doi.org/10.1016/j.egypro.2019.02.106

Black Iron Electrode/Persulfate System

9

7. Devlin, T.R., Kowalski, M.S., Pagaduan, E., Zhang, X., Wei, V., Oleszkiewicz, J.A.: Electrocoagulation of wastewater using aluminum, iron, and magnesium electrodes. J Hazard Mater., 862–868 (2019). https://doi.org/10.1016/j.jhazmat.2018.10.017 8. Liu, F., et al.: Experimental study on treatment of tertiary oil recovery wastewater by electrocoagulation. Chem. Eng. Proc. - Process Intensif. 144 (2019). https://doi.org/10.1016/j.cep. 2019.107640 9. Changmai, M., Pasawan, M., Purkait, M.K.: Treatment of oily wastewater from drilling site using electrocoagulation followed by microfiltration. Sep. Purif. Technol. 210, 463–472 (2019). https://doi.org/10.1016/j.seppur.2018.08.007 10. Pérez, L.S., et al.: Oil refinery wastewater treatment using coupled electrocoagulation and fixed film biological processes. Phys. Chem. Earth 91, 53–60 (2016). https://doi.org/10.1016/ j.pce.2015.10.018 11. Kobya, M., Demirbas, E.: Evaluations of operating parameters on treatment of can manufacturing wastewater by electrocoagulation. J. Water Process. Eng. 8, 64–74 (2015). https://doi. org/10.1016/j.jwpe.2015.09.006 12. Cruz, K.D., Mateo, N.M., Tangara, N.P., Almendrala, M.C.: Reactor design optimization on the electrocoagulation treatment of sugarcane molasses-based distillery wastewater. IOP Conf. Ser. Earth Environ. Sci. (2019). https://doi.org/10.1088/1755-1315/344/1/012023 13. Yavuz, Y., Ogütveren, Ü.B.: Treatment of industrial estate wastewater by the application of electrocoagulation process using iron electrodes, vol. 207 (2018). https://doi.org/10.1016/j. jenvman.2017.11.034 14. Oden, M.K., Sari-Erkan, H.: Treatment of metal plating wastewater using iron electrode by electrocoagulation process: optimization and process performance. Process. Saf. Environ. Prot. 119, 207–217 (2018). https://doi.org/10.1016/j.psep.2018.08.001 15. Ammar, S.H., Ismail, N.N., Ali, A.D., Abbas, W.M.: Electrocoagulation technique for refinery wastewater treatment in an internal loop split-plate airlift reactor. J. Environ. Chem. Eng. 7 (2019). https://doi.org/10.1016/j.jece.2019.103489 16. Gatsios, E., Hahladakis, J.N., Gidarakos, E.: Optimization of electrocoagulation (EC) process for the purification of a real industrial wastewater from toxic metals. J. Environ. Manage. 154, 117–127 (2015). https://doi.org/10.1016/j.jenvman.2015.02.018 17. Kamil, M., Sari-erkan, H.: Treatment of metal plating wastewater using iron electrode by electrocoagulation process : Optimization and process performance. Process. Saf. Environ. Prot. 119, 207–217 (2018). https://doi.org/10.1016/j.psep.2018.08.001 18. Damaraju, M., Bhattacharyya, D., Panda, T.K., Kurilla, K.K.: Marigold wastewater treatment in a lab-scale and a field-scale continuous bipolar-mode electrocoagulation system. J. Clean Prod. 245 (2020). https://doi.org/10.1016/j.jclepro.2019.118693 19. Deveci, E.Ü., Akarsu, C., Gönen, Ç., Özay, Y.: Enhancing treatability of tannery wastewater by integrated process of electrocoagulation and fungal via using RSM in an economic perspective. Process Biochem. 84, 124–133 (2019). https://doi.org/10.1016/j.procbio.2019.06.016 20. Yul Tak, B., Sik Tak, B., Ju Kim, Y., Jin Park, Y., Hun Yoon, Y., ho Min, G.: Optimization of color and COD removal from livestock wastewater by electrocoagulation process: Application of Box-Behnken design (BBD). J. Indus. Eng. Chem. 28, 307–315 (2015). https://doi.org/10. 1016/j.jiec.2015.03.008 21. Núñez, J., Yeber, M., Cisternas, N., Thibaut, R., Medina, P., Carrasco, C.: Application of electrocoagulation for the efficient pollutants removal to reuse the treated wastewater in the dyeing process of the textile industry. J. Hazard. Mater. 371, 705–711 (2019). https://doi.org/ 10.1016/j.jhazmat.2019.03.030 22. Kobya, M., Soltani, R.D.C., Omwene, P.I., Khataee, A.: A review on decontamination of arsenic-contained water by electrocoagulation: reactor configurations and operating cost along with removal mechanisms. Environ. Technol. Innov. 17 (2020). https://doi.org/10.1016/j.eti. 2019.100519

10

K. D. Cruz et al.

23. Yousuf, M., Mollah, A., Schennach, R., Parga, J.R., Cocke, D.L.: Electrocoagulation (EC)science and applications (2001) 24. Padmaja, K., Cherukuri, J., Anji Reddy, M.: A comparative study of the efficiency of chemical coagulation and electrocoagulation methods in the treatment of pharmaceutical effluent. J. Water Process Eng. 34 (2020). https://doi.org/10.1016/j.jwpe.2020.101153 25. Mei Chen, Y., Ming Jiang, W., Liu, Y., Kang, Y.: Quantitative contribution study and comparison between electrocoagulation, anode-electrocoagulation and chemical coagulation using polymer-flooding sewage. Chemosphere 250 (2020). https://doi.org/10.1016/j.chemosphere. 2020.126128 26. Cruz, K.D., Francisco, J.T.J., Mellendrez, K.J.M., Pineda, J.M.F.: Electrocoagulation treatment of swine slaughterhouse wastewater: effect of electrode material. In: E3S Web of Conferences, EDP Sciences (2019). https://doi.org/10.1051/e3sconf/201911700020 27. Liu, Y., Zhang, X., Jiang, W.M., Wu, M.R., Li, Z.H.: Comprehensive review of floc growth and structure using electrocoagulation: Characterization, measurement, and influencing factors. Chem. Eng. J. 417 (2021). https://doi.org/10.1016/j.cej.2021.129310 28. Nasrullah, M., Singh, L., Krishnan, S., Sakinah, M., Mahapatra, D.M., Zularisam, A.W.: Electrocoagulation treatment of raw palm oil mill effluent: Effect of operating parameters on floc growth and structure. J. Water Process Eng. 33 (2020). https://doi.org/10.1016/j.jwpe.2019. 101114 29. De Rozari, P., Greenway, M., El Hanandeh, A.: Science of the Total Environment Phosphorus removal from secondary sewage and septage using sand media amended with biochar in constructed wetland mesocosms. Sci. Total Environ The. 569–570, 123–133 (2016). https:// doi.org/10.1016/j.scitotenv.2016.06.096 30. Gan, C., Champagne, P., Hall, G.: Pilot-scale evaluation of semi-passive treatment technologies for the treatment of septage under temperate climate conditions. J. Environ. Manage. 216, 357–371 (2018). https://doi.org/10.1016/j.jenvman.2017.05.079 31. de Rozari, P., Greenway, M., El Hanandeh, A.: Phosphorus removal from secondary sewage and septage using sand media amended with biochar in constructed wetland mesocosms. Sci. Total. Environ. 569–570, 123–133 (2016). https://doi.org/10.1016/j.scitotenv.2016.06.096 32. de Rozari, P., Greenway, M., El Hanandeh, A.: Nitrogen removal from sewage and septage in constructed wetland mesocosms using sand media amended with biochar. Ecol. Eng. 111, 1 (2018). https://doi.org/10.1016/j.ecoleng.2017.11.002 33. Ebrahimi, A., Yousefi Kebria, D., Najafpour, G.D.: Co-treatment of septage and municipal wastewater in a quadripartite microbial desalination cell. Chem. Eng. J. 354, 1092–1099 (2018) . https://doi.org/10.1016/j.cej.2018.08.107 34. Hamersley, M.R.: Nitrogen balance and cycling in an ecologically engineered septage treatment system (2001). www.elsevier.com/locate/ecoleng 35. Yen-Phi, V.T., Rechenburg, A., Vinneras, B., Clemens, J., Kistemann, T.: Pathogens in septage in Vietnam. Sci. Total. Environ. 408, 2050–2053 (2010). https://doi.org/10.1016/j.scitotenv. 2010.01.030 36. Yuan, X., Feng, Y., Han, C., Jiang, Z., Li, Y., Liu, J.: A novel approach for enhancing nitrogen and hydrogen recovery from urine in microbial electrochemical gas-permeable membrane system. Sci. Total Environ. 867 (2023). https://doi.org/10.1016/j.scitotenv.2023.161446 37. Soro, M.P., N’goran, K.M., Ouattara, A.A., Yao, K.M., Kouassi, N.L.B., Diaco, T.: Nitrogen and phosphorus spatio-temporal distribution and fluxes intensifying eutrophication in three tropical rivers of Côte d’Ivoire (West Africa). Mar Pollut. Bull. 186 (2023). https://doi.org/ 10.1016/j.marpolbul.2022.114391 38. Liu, J., Feng, Y., Zhang, Y., Liang, N., Wu, H., Liu, F.: Allometric releases of nitrogen and phosphorus from sediments mediated by bacteria determines water eutrophication in coastal river basins of Bohai Bay. Ecotoxicol Environ. Saf. 235 (2022). https://doi.org/10.1016/j.eco env.2022.113426

Black Iron Electrode/Persulfate System

11

39. Pramanik, B.K., Shu, L., Jegatheesan, V., Bhuiyan, M.A.: Effect of the coagulation/persulfate pre-treatment to mitigate organic fouling in the forward osmosis of municipal wastewater treatment. J. Environ. Manage. 249 (2019). https://doi.org/10.1016/j.jenvman.2019.109394 40. Murphy, E., Friedman, A.J.: Hydrogen peroxide and cutaneous biology: translational applications, benefits, and risks. J. Am. Acad. Dermatol. 81, 1379–1386 (2019). https://doi.org/ 10.1016/j.jaad.2019.05.030 41. Zhang, W., Yang, P., Yang, X., Chen, Z., Wang, D.: Insights into the respective role of acidification and oxidation for enhancing anaerobic digested sludge dewatering performance with Fenton process. Bioresour. Technol. 181, 247–253 (2015). https://doi.org/10.1016/j.biortech. 2015.01.003 42. Zhou, X., Wang, Q., Jiang, G., Liu, P., Yuan, Z.: A novel conditioning process for enhancing dewaterability of waste activated sludge by combination of zero-valent iron and persulfate. Bioresour. Technol. 185, 416–420 (2015). https://doi.org/10.1016/j.biortech.2015.02.088 43. Yazici Guvenc, S.: Optimization of COD removal from leachate nanofiltration concentrate using H 2 O 2 /Fe +2 /heat – Activated persulfate oxidation processes. Process Safety Environ. Protect. 126, 7–17 (2019). https://doi.org/10.1016/j.psep.2019.03.034 44. Li, Y., et al.: Enhancing the sludge dewaterability by electrolysis/electrocoagulation combined with zero-valent iron activated persulfate process. Chem. Eng. J. 303, 636–645 (2016). https:// doi.org/10.1016/j.cej.2016.06.041 45. Hou, X., Zhan, G., Huang, X., Wang, N., Ai, Z., Zhang, L.: Persulfate activation induced by ascorbic acid for efficient organic pollutants oxidation. Chem. Eng. J. 382, 122355 (2020). https://doi.org/10.1016/j.cej.2019.122355 46. Ozyildiz, G., Olmez-Hanci, T., Arslan-Alaton, I.: Effect of nano-scale, reduced graphene oxide on the degradation of bisphenol A in real tertiary treated wastewater with the persulfate/UV-C process. Appl. Catal. BCatal. B 254, 135–144 (2019). https://doi.org/10. 1016/j.apcatb.2019.04.092 47. Shi, Y., et al.: Synergetic conditioning of sewage sludge via Fe 2+ /persulfate and skeleton builder: Effect on sludge characteristics and dewaterability. Chem. Eng. J. 270, 572–581 (2015). https://doi.org/10.1016/j.cej.2015.01.122 48. Sun, D., Hong, X., Wu, K., Hui, K.S., Du, Y., Hui, K.N.: Simultaneous removal of ammonia and phosphate by electro- oxidation and electrocoagulation using RuO 2 e IrO 2 / Ti and microscale zero-valent iron composite electrode. Water Res. 169, 115239 (2020). https://doi. org/10.1016/j.watres.2019.115239 49. Sun, D., Hong, X., Wu, K., Hui, K.S, Du, Y., Hui, K.N.: Simultaneous removal of ammonia and phosphate by electro-oxidation and electrocoagulation using RuO2–IrO2/Ti and microscale zero-valent iron composite electrode. Water Res. 169 (2020). https://doi.org/10. 1016/j.watres.2019.115239 50. Dubrawski, K.L., Mohseni, M.: Standardizing electrocoagulation reactor design: Iron electrodes for NOM removal. Chemosphere 91, 55–60 (2013). https://doi.org/10.1016/j.chemos phere.2012.11.075

Analysis of Potable Water Supply Scenarios Using WEAP Software and Applied to the Cities of Moquegua and Ilo Luis M. Bohorquez P.(B)

, D. Kenzo Sumikawa , and Rubén E. Mogrovejo G.

Department of Civil Engineering Lima, Peruvian University of Applied Sciences, Lima 15023, Peru [email protected]

Abstract. The cities of Moquegua and Ilo are located in a desert close to the Atacama Desert and the supply of water for population use in the current scenario and projected for a 50-year horizon is a concern, that is, to the year 2071; For this reason, the calculations of the current and projected population quantity have been made with a growth rate of 1.6% established by the National Institute of Statistics (INEI). Currently, the demand for water for population use in Moquegua is fully met with contributions from the Pasto Grande dam, but there is a water deficit for Ilo of 43 l/s. In the year 2071 the city of Moquegua will have a population of 204,340 inhabitants and the demand for water for population use will be 0.591 m3/s with an average increase of 7 l/s per year; and the city of Ilo will have a population of 178,722 inhabitants and the demand for water will increase to 0.517 m3 /s with an average increase of 5 l/s per year. To analyze the future water supply of the cities of Moquegua and Ilo, a hydrological simulation model has been developed using the WEAP (Water Evaluation and Planning System) software, where the operation of the Pasto Grande dam has been considered, which has a capacity of 200 MMC (Millions of cubic meters), as well as the extraction of water according to the projected water demands, and it is concluded that the water demands for population use of the cities of Moquegua and Ilo can be met with an index of reliability in time and volume of 100%; that is to say, it can be attended in its entirety. Keywords: Water supply · WEAP · Hydrological Simulation · Growth Rate · Projected Water Demand

1 Introduction Moquegua is a department with scarce water resources, which is why in critical years the Peruvian state declares it in emergency, as happened in 2016, which with Supreme Decree No. 086–2016-PCM, declared the State of Emergency in the department of Moquegua, due to water deficit, for a period of sixty (60) calendar days; for the execution of the immediate and necessary emergency response measures, as well as the reduction of the existing very high risk. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 J. Kim and Z. Chen (Eds.): CGEEE 2023, SPEES, pp. 12–26, 2024. https://doi.org/10.1007/978-3-031-52330-4_2

Analysis of Potable Water Supply Scenarios Using WEAP Software

13

Moquegua Before the operation of the transfer works of the Pasto Grande dam in 1994, the demand for water was met with limitations by the water supply of the Torata, Huaracane and Tumilaca rivers. When the new waters of the Pasto Grande dam came into operation, an oversupply of water was presented, a reason for this in the document “Agrarian Strategic Plan of the Moquegua region (2016–2023), the Office of Agrarian Planning. Moquegua, December 2017” [6], mentions that according to the Agrological Study and Irrigation Planning prepared by the National Agrarian University - La Molina; 200 hectares in the valley of Moquegua, Samegua and 300 hectares in the valley of Ilo, are being affected by the elevation of the water table, this as a consequence of the mismanagement of the water resource, It is important to high-light that the Pasto Grande dam has been built with the objective of meeting the demand for water for population use and for the expansion of the agricultural frontier in Lomas de Ilo, which to date has not been carried out due to construction problems. of the water conduction line through pipes in the Moquegua-Lomas de Ilo section due to the litigation between the Contractor and the Regional Government of Moquegua; therefore, the use of the water supply of the Pasto Grande dam should be based on the current demand for water and giving priority to the demand for water for population use, as established by the Water Resources Law 29338. A key component for the transformation of precipitation into runoff is potential evapotranspiration, and in Peru it has recently been calculated by Senmahi using the application called PISCO for the period 1981–2016 at a spatial resolution of ~ 1 km (0.01°) for the entire continental Peruvian territory [1]. For a study of water supply taking dams into account, it is important to consider the concept of climate change, as has been done in the study of the Milluni reservoir for water supply for the city of La Paz-Bolivia [2]. It is also important to indicate that, to carry out the calculations of the water supply, it has been important to download from the National Meteorology and Hydrology Service [3]. The historical records of precipitation and discharges of the Moquegua River basin and the headwaters of the Tambo River for the period (1965–2018) at a monthly level. The disparity between supply and demand has caused diversities for the inhabitants who use the water every day; but, due to the growing demand for water in urban areas, as well as the contamination of water resources, there is also a discharge of wastewater without adequate treatment; Therefore, the Water Evaluation And Planning (WEAP) software was used in the Aipe river basin, to create several hydrological simulations in the period 1980- 2011, resulting in a Nash coefficient of 0.75, this is greater than 0.60 per cent. Which is highly reliable [8].

14

L. M. Bohorquez et al.

As per the information from various previous studies, the contribution of this research consists in the elaboration of the water balance for the supply of water for population use, in the cities of Moquegua and Ilo. Through a hydrological model calibrated with the Nash-Sutliffe reliability index, in time and volume. And using the WEAP software as a tool, used in different projects worldwide.

2 Method 2.1 Methodology and Tools The methodology in this research was experimental, whose procedure was as follows: • first step was the delimitation of the basins and sub-basins of the Moquegua region and area of influence of the Pasto Grande dam using the Arc Gis 10.7 software. • Second step was the compilation of historical records of precipitation and discharges at a monthly level from the year 1964 to 2019 of the Moquegua region and neighboring basins such as Tambo, Ilave, Locumba and Maure. • In third step, the graphic analysis of the temporal variation of rainfall and discharges has been carried out in order to see anomalous or extremely anomalous years in the period 1964–2019 and detect possible inconsistencies. • In the fourth step, and with the purpose of visualizing inconsistencies in the historical records, a double mass analysis of precipitation and discharges has been carried out, for which groups of stations in the upper and middle part of the basin have been selected. In the lower part of the basin there is no precipitation because it is a desert. • In fifth step, an isohyet map has been prepared in order to visualize the behavior of precipitation for which 03 methods have been used: Thiessen Polygon, Inverse Square Distance and Kriging. • In Sixth step, a hydrological simulation model was built on the Weap platform where the Pasto Grande regulation dam was inserted, the water contributions to the dam and the water withdrawals from the dam for the diversion to Moquegua to meet the water requirement for the population and agricultural. • In seventh step, the model was calibrated taking into account the historical records of water volumes stored in the Pasto Grande dam and using the Nash and Bias calibration indices. • In Eighth step, the water demand calculations were made in the current and projected scenario, for which the crop schedule, the Kc of the crops, the effective rainfall and the irrigation efficiency were taken into account. • Finally, the water balance simulations have been prepared and the reliability indices of water supply in volume and time expressed as a percentage have been determined. In Fig. 1 you can see a conceptual map of the methodology described for this research.

Analysis of Potable Water Supply Scenarios Using WEAP Software

15

Fig. 1. Methodology adopted for the study

2.2 Study Area The study area is located in southern Peru, approximately at kilometer 980 km of the Panamericana Sur highway and extends from sea level to the line of the summits of the Tumilaca, Torata and Huaracane river basin at 4,537 masl. With coordinates of 17° 40 27” to 16° 39 38” and 12°25 00"S 76°47 00"W, whose details are presented in Fig. 2.

Fig. 2. The Tumilaca, Torata and Huaracane river basin with the delimited sub-basins.

16

L. M. Bohorquez et al.

2.3 Description of the WEAP Hydrological Model According to [4]. Weap supports water resources planning by balancing the supply of water (generated through physical modules of a hydrological type at the sub-basin scale) with the demand for water (characterized by a distribution system of spatial and temporal variability with differences in priorities demand and supply). WEAP employs a palette of different objects and procedures accessible through a graphical interface that can be used to analyze a wide range of issues and uncertainties facing water resource planners, including those related to weather, flow conditions, the basin, demand projections, regulatory conditions, operation objectives and available infrastructure. Unlike other typical water resource models based on external hydrological modeling, WEAP is a model forced by climatic variables. On the other hand, and in a similar way to these models of water resources, WEAP includes routines designed to distribute water among different types of users from a human and ecosystem perspective. These characteristics make WEAP an ideal model for conducting climate change studies, in which it is important to estimate changes in water supply (eg projected changes in precipitation) and in water demand (eg changes in evaporative demand). in crops), which will produce a different water balance at the basin level. On the other hand, and in a similar way to these models of water resources, WEAP includes routines designed to distribute water among different types of users from a human and ecosystem perspective. These characteristics make WEAP an ideal model for conducting climate change studies, in which it is important to estimate changes in water supply (eg projected changes in precipitation) and in water demand (eg changes in evaporative demand). in crops), which will produce a different water balance at the basin level. On the other hand, and in a similar way to these models of water resources, WEAP includes routines designed to distribute water among different types of users from a human and ecosystem perspective. These characteristics make WEAP an ideal model for conducting climate change studies, in which it is important to estimate changes in water supply (eg projected changes in precipitation) and in water demand (eg changes in evaporative demand). in crops), which will produce a different water balance at the basin level. WEAP Components. WEAP is used to simulate the precipitation/runoff transformation in a basin. Includes basin model, meteorological models, control specifications and output data, which have been applied to the particular case of the Tumilaca, Torata and Huaracane River desert basin according to their geomorphological and precipitation characteristics.

2.4 Collection of Meteorological Information and Records The topographic data of the Tambo River basin were obtained from the ASTER GDEM files offered by the Ministry of the Environment of Peru (MINAM), in which the files S17W72, S18W71 and S18W72 were downloaded. These files, downloaded in DEM (Digital Elevation Model) format, were inserted into the ArcMap Software, in which they were strategically divided into 8 sub-basins, as can be seen in Fig. 3.

Analysis of Potable Water Supply Scenarios Using WEAP Software

17

For these 8 sub-basins, the geomorphological parameters of each one was obtained with the help of the mentioned software; These are: area, perimeter, river length, coef. of compactness and form factor; whose details are presented in Table 1. Table 1. Geomorphological parameters of the sub-basin BASINS

Area (km2 )

Chilota

474.128

Perimeter (km)

River lenght (km)

108.5

28.58

69.08

Compactness coefficient 1.06

Form factor 0.47

Quellaveco

250.129

20.691

1.35

0.53

Pasto Grande

556.464

135.2

25.178

1.83

0.43

Carumas

633.172

143.5

43.93

1.76

0.62

Tumilaca

630.609

146.5

58.05

Huaracane

499.171

135.3

57.35

Torata

405.262

163.6

61.03

1.62

0.68

327.1

94.31

2.43

0.63

Moquegua

2069.71

2.35 71.9

0.72 0.78

Considering that in the Moquegua basin and neighboring sub-basins there are no historical records of precipitation in the upper and middle part of the basin, stations from neighboring basins, such as Locumba, Ilave and Tambo, have been taken into consideration. These stations are: Suches, Vizcachas, Mazo Cruz, Pasto Grande, Vilacota, El Frayle, Salinas and Quinistaquillas. These hydrometeorological data records were obtained from the National Service of Meteorology and Hydrology of Peru [3]. 2.5 Input Data to the WEAP Model The input data to the Weap model (Water Evaluation and Planning System) are climatic variables, such as: Average temperature, Relative Humidity, Wind Speed and the nine parameters of the model that are related to the vegetation cover and the soil of the basin, whose details are described below: • • • • • • • • •

Vegetation cover coefficient (Kc) Field Capacity (SWC) Deep Soil Capacity (DWC) Runoff Resistance Factor (RRF) Conductivity in root zone (ks) Deep zone conductivity (kd) Flow direction (pfd). Soil moisture top layer Z1 Soil moisture lower layer Z2

The values of the aforementioned parameters have been taken from the Weap software user manual and from some hydrological studies developed by the National Water Authority, such as “Hydrological Assessment of the Tambo River Basin, 2020” [5].

18

L. M. Bohorquez et al.

Fig. 3. Moquegua and Pasto Grande river sub-basins

The values considered for the parameters of the superficial layer where the roots of the crops or vegetation cover of the basin predominate, are presented in Table 2. Table 2. Parameters (upper tank) of the Weap hydrological model. Coverage

SWC (mm)

ks (mm/month)

RRF

Z1 (%)

bofedal

800

210

1.3

35

pajonal

600

165

1.3

35

Tundra

600

165

1.3

35

sparse vegetation

700

165

1.3

35

Table 3 shows the considered values of the parameters of the lower layer where water storage capacity and hydraulic conductivity predominate and is responsible for the base flow.

Analysis of Potable Water Supply Scenarios Using WEAP Software

19

Table 3. Parameters (lower tank) of the Weap hydrological model. Parameter

hydrographic unit

DWC (mm)

750

Kd (mm/month)

37.5

pfd

0.8

z2 (%)

8

Likewise, Fig. 4 shows a photograph of the Pasto Grande sub-basin and the predominant vegetation in the area.

Fig. 4. Plant cover of the Pasto Grande sub-basin, where Ichu, tola and bofedal predominate.

2.6 WEAP Software Application The model was built in the WEAP software from the sub-basins delimited in the ArcMap in Shapes format in UTM coordinates. The location of the Pasto Grande dam and downstream was placed approximately in the final part of the Pasto Grande sub-basin, the requirements for the El Tambo and Moquegua valleys were placed, and the diversion channel to the Moquegua basin was placed. At the bottom of image below, the demands for population use for the cities of Moquegua and Ilo were placed. The water supply for the city of Ilo is complemented by contributions from the Ite-Ilo canal with a contribution of 50 l/s. In Fig. 5. The model built with the WEAP software is observed.

20

L. M. Bohorquez et al.

Fig. 5. Model built in the WEAP software for the water supply of Moquegua and Ilo.

The data inserted to be able to simulate with the built hydrological model were: precipitation, temperature, relative humidity, wind speed, soil hydraulic conductivity, soil storage capacity, soil moisture content, flow resistance factor and the projection of the water demand of the cities of Moquegua and Ilo until the year 2070, whose increase is presented in Fig. 6 and Fig. 7.

Fig. 6. Projection of population water demand in the city of Moquegua

Analysis of Potable Water Supply Scenarios Using WEAP Software

21

Fig. 7. Projection of population water demand in the city of Ilo

2.7 Simulation of the Hydrological Model In the simulation of the model, 02 scenarios have been created, one for the current scenario and another with a projection to the year 2070, where it has been essential to take into account the population growth rate of 1.6% per year and an endowment of 250 l/day / inhabitant contemplated in the National Building Regulations for coastal cities of Peru.

3 Results 3.1 Calibration of the Hydrological Model The calibration of the hydrological model has been carried out through a comparison of the discharges registered in the Pasto Grande station and the discharges generated with the model, as can be seen in Fig. 8, they are very similar. The Nash Index of 0.67 has been considered as an indicator of calibration, which is a very compatible value.

22

L. M. Bohorquez et al.

Fig. 8. Comparison of hydrographs observed and generated monthly at the Pasto Grande station

At the monthly average level, the similarity between the registered and simulated flow at the Pasto Grande station is very close, as detailed in Table 4 and Fig. 9, where it is detailed that the observed annual average flow is 2.8 m3 /s and the simulated is 2.7 m3 /s. Table 4. Average monthly discharges registered and generated at the Pasto Grande Hydrometric Station. Statistics Jan Feb Sea Apr May Jun Jul

Aug Sep

Oct

Nov Dec

Avg

observe

5.6

8.5

7.7

3.4

1.3

1.1

0.97 0.86 0.75 0.69 0.92 1,533 2.8

model

5.4

8.9

6.6

3.1

1.5

1.1

1.3

1.0

0.9

0.7

0.86 0.99

2.7

Fig. 9. Comparison of observed and simulated hydrographs at the monthly average level at the Pasto Grande station

Analysis of Potable Water Supply Scenarios Using WEAP Software

23

A correlation has also been made between the series of observed and simulated discharges at the Pasto Grande station, as detailed in Fig. 10, where it can be observed that the correlation coefficient is 0.79.

Fig. 10. Correlation between recorded and simulated data at the Pasto Grande station.

3.2 Water Balance of Water Supply in Current Scenario Currently, the city of Moquegua has a population of 92,399 inhabitants and the demand for drinking water is 0.267 m3 /s, which is met with the water supply from the Pasto Grande dam and there is 100% coverage, but the demand for water It will increase each year on average at a rate of 7 l/s each year due to population growth, which is 1.6% according to the last census of 2017 carried out by the INEI, and for the year 2071 the projection of the Population growth is 204,340 inhabitants and the demand for water for population use in the city of Moquegua will be 0.591 m3 /s. The city of Ilo currently has a population of 80,815 inhabitants and the demand for water for population consumption is 0.234 m3/s, whose supply comes from 02 water sources: Aguas del rio Osmore in the Ilo sector with 0.127 m3 /s and the waters from the North Ite Canal with. 0.064 m3/s from the Locumba river in the Tacna region with a high content of Boron and Arsenic, which is treated at the treatment plant. The current water supply for the city of Ilo is 0.191 m3 /s, therefore, there is a water deficit of 0.043 m3 /s, which will increase over time if appropriate measures are not taken. According to the population growth projection made, the city of Ilo in the year 2071 will have a population of 178,722 inhabitants and the demand for water will increase to 0.517 m3 /s. The increase in the demand for water for population use in Ilo is 5 l/s per year on average.

24

L. M. Bohorquez et al.

3.3 Water Balance Projected to a Horizon of 50 Years (Year 2070) of Water Supply for Cities of Moquegua and Ilo In other words, a horizon of 50 years the model counts the number of months in which the demands have been satisfied and the number of months in which they have not been satisfied and makes calculations of probability reliability and frequency of satisfaction of the demands. The final objective of the simulation is to know the situation of water use in current conditions and in future conditions to carry out preventive measures and avoid or mitigate the problems that arise with water scarcity. The projected Balance has been carried out with 600 months of water supply and demand, and since the water supply for population use has been prioritized, there are no months with a water deficit, which is why the reliability index is 100%.    Simulated Months − Months with Deficit ∗ 100 (RT) =  (1) Simulated Months where: RT: Reliability Time. The total demand in the 50-year horizon of the city of Moquegua is 18.6 MMC/year and from Ilo it is 16.3 MMC/year, making a total of 34.9 MMC/year, which should be attended in its entirety and since there is no deficit. of water, also the reliability index in volume will be 100%.    Total Demands − Months with Deficit ∗ 100 (VR) =  (2) Total Demands where: VR: Volume Reliability.

4 Validation For the validation, the storage capacity of the Pasto Grande Dam of 200 MMC of water has been taken into account, which currently supplies all the population demand of the city of Moquegua, but there is still a deficit of 0.043 m3/s in the city of ilo; but this limitation will be resolved with the completion of the laying of the water pipeline from Moquegua to Ilo, which is currently paralyzed due to legal problems between the Contractor and the Moquegua Regional Government. When the aforementioned conduction pipeline enters into operation, there will be water that can fully cover the population demand of the city of Ilo. In summary, the adequate operation of the Pasto Grande dam and the completion of the Moquegua-Ilo pipeline work will fully guarantee the water supply of the cities of Moquegua ë Ilo. Figure 11 shows the variation in the storage volume of the Pasto Grande Dam.

Analysis of Potable Water Supply Scenarios Using WEAP Software

25

Fig. 11. Variation of the volume of water in the Pasto Grande dam for population supply of Moquegua é Ilo

In a complementary way, Fig. 12 shows the monthly variation of the volume of water demand of the cities of Moquegua for the years 2022 and for the year 2071.

Fig. 12. Variation in the volume of water demand in the cities of Moquegua and Ilo.

5 Conclusions The main source of water supply to meet the water demands for population use in the cities of Moquegua and Ilo is the Pasto Grande dam, whose operation has been simulated for a 50-year horizon, that is, until the year 2071, to which is taken into consideration that the dam has a total volume of 200 MMC of storage capacity, a dead volume of 38.89

26

L. M. Bohorquez et al.

MMC, as detailed in Fig. 11 and the extraction of water has been taken into consideration to meet the demands of water for population use. According to the simulation carried out, the Pasto Grande dam would be completely full in wet years and could drop on average to a volume of the order of 100 MMC, as can be seen in Fig. 11. In order to carry out the hydrological simulation, it has been vital to carry out a projection of the population for a horizon of 50 years, that is, until the year 2071, with a growth rate of 1.6% established in the population census of the year 2017, from which it is concluded that the city of Moquegua would have a population of 204,340 inhabitants and a water demand of 0.591 m3/s and the city of Ilo would have a population of 178,722 inhabitants and a water demand of 0.571 m3/s, relevant details are presented in Fig. 6 and Fig. 7. As per the reliability indices in time and volume, we know that the demand for water for population use in the cities of Moquegua and Ilo will be 100% met, due to the fact that water is available in the Pasto de Grande dam, which has a capacity of 200 MMC and according to the Water Resources Law, attention to population demand is a first priority. Acknowledgment. Upon this paper we thanks to the engineers Rubén Mogrovejo, Sissi Santos and Manuel Collas Chavez for their support and dedication as professional teachers of the Peruvian University of Applied Sciences and our parents who inspired us and motivated us to prepare this scientific article.

References 1. Huerta, A., et al.: Evapotraspiration gridded database based on FAO Penman-Monteith in Peru, PISCOeo_pm (2022) 2. Medina, C.: Hydrological modeling under climate change scenarios for a water supply reservoir in La Paz, Bolivia, I&D, pp 1–16 (2021) 3. SENAMHI “Use of the gridded product Pisco of precipitation in studies, investigations and operational systems for monitoring and hydrometeological forecasting” Senamhi (2017) 4. Stockholm Environment Institute, “Weap Water Evaluation and Planning system” (2009) 5. Direction of quality and evaluation of water resources “Hydrological study of the Tambo hydrographic unit” National Water Authority (2019) 6. DRA «Institutional Strategic Plan 2020–2022» Moquegua (2022) 7. National Water Authority Hydrological study and location of the hydrometric stations network (2010) 8. Abrador, A., Zuñiga, J., Romero, J.: Hydrological simulation of the potential impacts of climate change in the Aipe river basin in Huila”, Colombia, IMW (2016)

A Swift, Straightforward, and Innovative Approach for Detecting Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) in Aquatic Matrices Using Direct Immersion (DI) Three-Phase Single-Drop Microextraction (SDME) Coupled In-Line with Capillary Electrophoresis (CE) Nader Nciri(B) Department of Chemistry, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea [email protected]

Abstract. The detection and quantification of nonsteroidal anti-inflammatory drugs (NSAIDs) in water sources have become crucial due to their widespread use and potential environmental impact. In this study, we propose a swift, straightforward, and innovative approach for determining NSAIDs in a water matrix. This approach combines direct immersion (DI), three-phase single-drop microextraction (SDME), and capillary electrophoresis (CE). The DI-SDME technique offers several advantages, including simplicity, high extraction efficiency, and low organic solvent consumption. By immersing a microdrop covered with a thin layer of organic solvent into the aqueous sample, NSAIDs were selectively extracted into the organic phase, enabling their preconcentration and subsequent analysis. The developed method was validated using various NSAIDs, including ketoprofen (KTP), ibuprofen (IBU), and naproxen (NAP). The analytical performance was evaluated based on parameters such as drop size, extraction solvent, agitation speed, and extraction time, which showed excellent reproducibility. Due to the small dimensions of the acceptor and organic phases, quite high enrichment factors (EFs) of 470–730 were obtained from a 5-min DI-SDME at +25 ºC with stirring. The limits of detection (LODs) were found to be 1.3–3.8 nM, demonstrating the sensitivity of the method. In summary, DI-SDME combined with CE provides an innovative solution for determining NSAIDs in complex matrices with high sensitivity and selectivity while minimizing sample requirements compared to traditional methods – making it an appealing option for environmental monitoring or forensic toxicology applications where low levels may be present but are otherwise difficult to detect via conventional analytical protocols. Keywords: Nonsteroidal Anti-inflammatory Drugs (NSAIDs) · Ketoprofen · Ibuprofen · Naproxen · Water Sources · Direct Immersion (DI) · Three-Phase © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 J. Kim and Z. Chen (Eds.): CGEEE 2023, SPEES, pp. 27–40, 2024. https://doi.org/10.1007/978-3-031-52330-4_3

28

N. Nciri Single-Drop Microextraction (SDME-CE) · Capillary Electrophoresis (CE) · Environmental Monitoring

1 Introduction Nonsteroidal anti-inflammatory drugs (NSAIDs) are widely used pharmaceutical compounds that have become ubiquitous in the environment due to their extensive use and improper disposal. These compounds pose potential risks to aquatic ecosystems and human health when they enter water sources through various routes, such as wastewater discharge, agricultural runoff, and pharmaceutical manufacturing effluents [1–3]. Consequently, the development of reliable and efficient analytical methods for the detection and quantification of NSAIDs in water is of significant importance for environmental monitoring and safeguarding public health. Traditional analytical techniques for NSAID analysis in water samples often involve complex sample preparation procedures, extensive extraction steps, and time-consuming instrumental analysis [4–6]. Therefore, there is a growing demand for swift, straightforward, and innovative approaches that can streamline the analysis process without compromising sensitivity and accuracy. In this context, the combination of direct immersion (DI) three-phase single-drop microextraction (SDME) with capillary electrophoresis (CE) has emerged as a promising and efficient strategy for NSAID determination in water samples. Direct immersion SDME is a microextraction technique that involves immersing a single drop wrapped with a thin membrane of organic solvent into the water sample, creating a three-phase system that facilitates the extraction of target analytes. This technique offers several advantages, including simplicity, minimal solvent consumption, and reduced sample volume requirements. Coupling DI-SDME with capillary electrophoresis (CE) further enhances the analytical capabilities by providing high-resolution separation and sensitive detection of NSAIDs. The objective of this research is to develop a swift, straightforward, and innovative approach for the determination of NSAIDs in water using the DI-SDME technique coupled in-line with capillary electrophoresis (CE). By combining the extraction efficiency of DI-SDME with the separation and detection capabilities of CE, this approach aims to provide a comprehensive and reliable analytical method for NSAID analysis in water samples. In this study, we optimized key experimental parameters such as drop size, extraction solvent, agitation speed, and extraction time to maximize the extraction efficiency of the DI-SDME technique. Several commonly encountered NSAIDs, including ketoprofen (KTP), ibuprofen (IBU), and naproxen (NAP) were selected as model compounds to validate the method’s performance. The developed approach was evaluated for its linearity, precision, and accuracy in determining NSAIDs in water samples. Furthermore, the applicability of the proposed method was assessed by analyzing real water samples spiked with known concentrations of NSAIDs. Comparative studies with similar extraction techniques were conducted to evaluate the advantages and superiority of the DI-SDME approach in terms of simplicity, efficiency, and speed.

A Swift, Straightforward, and Innovative Approach

29

Overall, this research aims to contribute to the field of environmental analysis by introducing a swift, straightforward, and innovative approach for the determination of NSAIDs in water samples. The combination of DI-SDME with CE provides an efficient and reliable analytical platform that addresses the need for sensitive and accurate monitoring of NSAIDs in water bodies. By facilitating the assessment of NSAID contamination in aquatic ecosystems, this method can support decision-making processes for environmental protection and public health preservation.

2 Materials and Methods 2.1 Chemicals and Materials The following passage describes the chemicals and materials used in this scientific experiment. The chemicals were acquired from Sigma-Aldrich, a supplier based in St. Louis, MO, USA. The specific chemicals mentioned are ketoprofen (C16 H14 O3 , KTP), ibuprofen (C13 H18 O2 , IBU), naproxen (C14 H14 O3 , NAP), sodium hydroxide (NaOH), sodium tetraborate decahydrate (Na2 B4 O7 ·10H2 O), hydrochloric acid (HCl), ethanol (C2 H6 O), 1-octanol (CH3 (CH2 )7 OH), and methanol (CH3 OH). Additionally, acetic acid (CH3 COOH) was purchased from Merck KGaA in Darmstadt, Germany, and octadecyltrimethoxysilane (ODTS) was acquired from Sigma-Aldrich in Milwaukee, WI, USA. To ensure the purity of the water used in the experiment, a Barnstead™ LabTower™ EDI Water Purification System manufactured by Thermo Fisher Scientific in Langenselbold, Germany, was employed to provide deionized water (DIW). DIW is free from impurities and ions that could potentially affect the experimental results. The three-stock solutions of KTP, IBU, and NAP were prepared in 5 mM methanol and stored in a dark environment at a temperature of +4 ºC. These stock solutions serve as the concentrated sources of the respective compounds for subsequent dilutions and analysis. Sodium tetraborate solutions were titrated with 2 M sodium hydroxide (NaOH) to create run buffers. Run buffers are used in capillary electrophoresis (CE) to provide the necessary pH and ionic strength conditions for the separation and analysis of the compounds of interest. Standard samples for CE analysis were created by diluting the respective stock solutions with a run buffer. This step ensures that the standard samples have the desired concentration and composition required for accurate analysis. To prepare the sample donor solutions, the matching stock solutions were first diluted with an HCl solution at pH 2. This adjustment of the pH ensures compatibility with the subsequent analysis. Before usage, each solution, including the stock solutions and sample donor solutions, underwent filtration using a 0.45 µm Whatman syringe filter from Clifton, NY, USA. Filtration removes any particles or impurities present in the solutions that could potentially interfere with the analysis or cause blockages in the capillary system during CE. Overall, the passage provides details about the chemicals, water purification system, stock solutions, run buffers, standard sample preparation, and solution filtration steps involved in the experiment. These steps are essential for ensuring accurate and reliable results in the scientific analysis being conducted.

30

N. Nciri

2.2 Instrumentation The capillary electrophoresis (CE) was conducted using a specific instrument called the P/ACE™ MDQ system, manufactured by Beckman Coulter in Fullerton, CA, USA. The CE system was equipped with a UV detector set at a wavelength of 214 nm, which allows for the detection of specific compounds based on their absorbance at that wavelength. A bare fused silica capillary provided by Polymicro Technologies, based in Phoenix, AZ, USA, was used for the analysis. The capillary had a length of 60 cm, with the detection point located 50 cm from the injection point. It had an inner diameter (I.D.) of 50 µm and an outer diameter (O.D.) of 360 µm. The capillary material, fused silica, is commonly used in CE due to its favorable properties for efficient separations. To facilitate the CE separation, a sodium borate buffer was selected as the run buffer. After testing different sodium borate buffers within the concentration range of 240– 400 mM and pH ranges of 9.2–10.5, a 320 mM sodium borate buffer with a pH of 9.8 was chosen as the most suitable option for the experiment. The run buffer plays a crucial role in providing the appropriate pH and ionic strength for the separation of analytes in CE. Between consecutive runs, the capillary was conditioned to ensure reproducibility. This conditioning process involved rinsing the capillary at a pressure of 60 psi. The capillary was sequentially rinsed with 0.1 M NaOH for 2 min, deionized water (DIW) for 3 min, and the run buffer for 7 min. This procedure helps to remove any residual analytes or contaminants from the capillary, ensuring accurate and consistent results. Throughout the experiment, the capillary temperature was maintained at a constant +25 ºC. Controlling the temperature is important as it affects the separation efficiency and migration times of analytes in CE. 2.3 DI-SDME-CE Procedure Figure 1 visually represents the extraction process of DI-SDME-CE. In this protocol, the capillary’s inlet tip surface is coated with a hydrophobic solution containing ODTS (5% v/v) and acetic acid (0.1% v/v) in ethanol. This coating enables the secure attachment of an acceptor drop, which is encapsulated by an organic phase, during the extraction. Initially, the capillary is filled with a run buffer by rinsing it at 60 psi for 7 min, and then octanol [7, 8] is injected at 2 psi for a specific duration. Subsequently, the capillary’s inlet is dipped into the water sample solution, and a backpressure of 0.7 psi is applied from the outlet to the inlet, resulting in the formation of a drop comprising the basic aqueous acceptor phase surrounded by a thin octanol film, hanging from the capillary inlet tip. The timeframes for octanol injection and drop formation are adjusted using the Poiseuille equation [9] to optimize the volume of the octanol layer. To maintain the drop’s shape, a backpressure of 0.1 psi is applied for a certain period while being monitored with a video camera. The acidic aqueous donor phase is stirred at 300 rpm using a handmade micro-stirrer. After extraction at +25 ºC, a portion of the enriched acceptor drop is hydrodynamically pumped into the capillary at 0.5 psi for 3 s. Finally, the capillary inlet is inserted into a vial containing the run buffer, and electrophoresis is performed at +20 kV, allowing for the separation and analysis of the extracted analytes.

A Swift, Straightforward, and Innovative Approach

31

Fig. 1. Extraction process of DI-SDME-CE.

3 Results and Discussion 3.1 Enrichment Factor of Three-Phase LLLE System In a three-phase liquid-liquid-liquid extraction (LLLE) system, the enrichment of a specific ionizable analyte (S) is driven by the pH difference (pH) between the donor (d) and acceptor (a) phases. The pH values of both the donor and acceptor phases are adjusted to favor the ionized and neutral forms of the analyte, enabling selective preconcentration [10]. By manipulating the pH, analytes with suitable ionization characteristics are preferentially concentrated into the acceptor phase due to the driving force of the pH. This selective enrichment leads to an improved detector signal, enhancing the sensitivity of the analysis. Additionally, the organic phase in the LLLE system acts as a barrier, effectively blocking inorganic ions present in the sample matrix. This contributes to a reduction in background noise during the analysis, improving the overall signal-to-noise ratio [10]. For weakly acidic analytes like KTP (pK a = 4.60), IBU (pK a = 4.91), and NAP (pK a = 4.17), the donor solution is acidified to pH 2 using hydrochloric acid (HCl), while a basic borate buffer with a pH of 9.8 serves as the acceptor phase. Although a higher pH in the acceptor phase may potentially increase the enrichment factor (EF), which is the ratio of the analyte’s concentration in the acceptor phase to its initial concentration in the donor phase, the choice of the run buffer at pH 9.8 is primarily for operational convenience. The DI-SDME-CE technique involves initially extracting the analyte (S) from the aqueous phase into the organic phase and subsequently reintroducing it into the aqueous acceptor phase using a single drop. This extraction approach allows for efficient enrichment and concentration of the analyte. For the three-phase LLLE system, referred to as donor–organic–acceptor (d–o–a) phase system, the equilibrium enrichment factor (EFeq ) can be calculated using Eq. (1) [11]: EF eq =

1 (D2 /D1 ) + (D2 Vo /Vd ) + (Va /Vd )

(1)

32

N. Nciri

In this equation, D1 is the ratio of the equilibrium concentrations of the analyte in the organic phase (Co,eq ) to that in the donor phase (Cd,eq ), and D2 is the ratio of Co,eq to the equilibrium concentration of the analyte in the acceptor phase (Ca,eq ). Vd , Vo , and Va represent the volumes of the donor, organic, and acceptor phases, respectively. Equation (2) provides an approximation of the enrichment factor at a given extraction time (t), denoted as EF(t) [12]. It is applicable when the extraction time is relatively short [12]. The equation involves the volumes of the donor and acceptor phases (Vd and Va ) and the first-order rate constant (k), which is calculated using Eq. (3). The lag-time (tlag ), representing the time required to reach a steady-state extraction, is not considered for the thin octanol layer used in the DI-SDME-CE technique. EF (t) =

 V Vd  d 1 − e−k(t−tlag ) ≈ kt Va Va

(2)

Equation (3) calculates the first-order rate constant (k) based on the interfacial areas (Ad and Aa ) between the donor–organic and organic–acceptor phases. The equation also incorporates the total mass-transfer coefficients (β d and β a ) for the donor–organic and organic–acceptor phases, respectively. D1 and D2 are parameters representing the ratios of equilibrium concentrations (Co,eq /Cd,eq and Co,eq /Ca,eq ) of the analyte [12]. Ad Aa D1 β d β a

k≈

Vd (Ad D2 β d + Aa β a )

(3)

By substituting Eq. (3) into Eq. (2), Eq. (4) is obtained, providing an expression for the enrichment factor (EF(t) ) as a function of time. This equation incorporates the parameters D1 , D2 , β d , β a , Ad , Aa , Vd , Va , and t. EF (t) ≈

D1 β d β a D2 β d + (Aa /Ad )β a



 Aa t Va

(4)

Equation (5) simplifies Eq. (4) by focusing on the relationship between the enrichment factor (EF(t) ) and the ratio of the interfacial area of the organic–acceptor phase to the volume of the acceptor phase (Aa /Va ). The equation suggests that higher EF values can be expected when the acceptor phase is less voluminous (i.e., a few nanoliters) and when D2 is significantly smaller than D1 , and Vo is much smaller than Vd . This condition leads to a larger Aa /Va ratio, resulting in higher EF values.   Aa t (5) EF (t) ∞ Va

3.2 Acceptor Phase (Drop Size) Figure 2 depicts the findings of an extraction experiment that investigated the impact of varying the volume of the acceptor phase while keeping the volume of octanol constant at 30 nL. The objective was to determine the most suitable volume for the acceptor drop by considering both the enhancement factors (EFs) and the stability of the formed

A Swift, Straightforward, and Innovative Approach

33

droplet. The experiment tested different volumes of the acceptor phase, ranging from 3 to 12 nL. The results in Fig. 2 illustrate the relationship between the volume of the acceptor phase and the observed EFs. Upon analyzing the results and considering both the EFs and droplet stability, a volume of 5 nL for the acceptor drop was identified as the optimal choice. This volume was determined to strike the best balance between achieving high EFs, indicating efficient extraction, and ensuring droplet stability, preventing issues such as droplet breakup or instability. Therefore, based on the experimental findings, a volume of 5 nL for the acceptor drop was deemed the most suitable and optimal for the extraction process.

Fig. 2. Effect of the acceptor phase volume variation on the enrichment factor (EF) of ketoprofen (KTP), ibuprofen (IBU), and naproxen (NAP). Instrument: P/ACE™ MDQ system; Bare fused silica capillary: 60/50 bare fused silica (I.D. = 50 µm, O.D. = 360 µm, polyimide coating 5 µm); Temperature: +25 ºC; Absorbance detection: 214 nm; Run buffer: 320 mM sodium tetraborate decahydrate (pH 9.8); Donor phase: 1 µM KTP, 1 µM IBU, and 1 µM NAP (pH 2); Organic phase: 30 nL octanol (2 psi, 7.6 s); Acceptor phase: 320 mM sodium borate buffer (run buffer, pH 9.8); Rinse solution: 60 psi; 0.1 M NaOH, deionized water (DIW), buffer (2, 3, and 7 min); Drop formation: backpressure [0.7 psi; 23.8 s (3 nL), 25.3 s (5 nL), 27.5 s (8 nL), and 30.3 s (12 nL)]; Maintenance of drop shape: 0.4 min with a backpressure of 0.1 psi for every 0.9 min of extraction (3 nL), 0.38 min with a backpressure of 0.1 psi for every 0.88 min of extraction (5 nL), 0.23 min with a backpressure of 0.1 psi for every 0.73 min of extraction (8 nL), and 0.16 min with a backpressure of 0.1 psi for every 0.86 min of extraction (12 nL); Extraction time: 5 min without stirring; Sample injection: (0.5 psi, 3 s); Separation voltage: +20 kV; The standard deviations are shown as error bars (n = 4).

34

N. Nciri

3.3 Organic Phase (Extraction Solvent) This passage explains the impact of reducing the volume of the organic phase during the extraction process, which involves transferring analytes from a donor phase to an acceptor phase with the help of an intermediate organic phase. This reduction in organic phase volume can lead to higher enhancement factors (EFs), which represent the degree of enrichment achieved during the extraction. As shown in Fig. 3, the volume of the octanol shell, serving as the intermediate organic phase, was varied between 25 and 40 nL, while the volume of the acceptor phase remained constant at 5 nL throughout the test.

Fig. 3. Effect of the organic phase volume variation on the enrichment factor (EF) of ketoprofen (KTP), ibuprofen (IBU), and naproxen (NAP). Instrument: P/ACE™ MDQ system; Bare fused silica capillary: 60/50 bare fused silica (I.D. = 50 µm, O.D. = 360 µm, polyimide coating 5 µm); Temperature: +25 ºC; Absorbance detection: 214 nm; Run buffer: 320 mM sodium tetraborate decahydrate (pH 9.8); Donor phase: 1 µM KTP, 1 µM IBU, and 1 µM NAP (pH 2); Organic phase: octanol [2 psi, 6.3 s (25 nL), 7.6 s (30 nL), 8.8 s (35 nL), and 10.1 s (40 nL)]; Drop formation: backpressure (0.7 psi; 21.7 s, 25.3 s, 28.8 s, and 32.5); Acceptor phase: 320 mM sodium borate buffer (run buffer, pH 9.8); Rinse solution: 60 psi; 0.1 M NaOH, deionized water (DIW), buffer (2, 3, and 7 min); Drop formation: backpressure [0.7 psi; 23.8 s (3 nL), 25.3 s (5 nL), 27.5 s (8 nL), and 30.3 s (12 nL)]; Maintenance of drop shape: 0.33 min with a backpressure of 0.1 psi for every 0.83 min of extraction (25 nL), 0.38 min with a backpressure of 0.1 psi for every 0.88 min of extraction (30 nL), 0.4 min with a backpressure of 0.1 psi for every 0.9 min of extraction (35 nL), 0.42 min with a backpressure of 0.1 psi for every 0.92 min of extraction (40 nL); Extraction time: 5 min without (w/o) stirring; Sample injection: (0.5 psi, 3 s); Separation voltage: +20 kV; The standard deviations are shown as error bars (n = 4).

A Swift, Straightforward, and Innovative Approach

35

Figure 3 visually presents the results obtained from this variation. The figure demonstrates that as the thickness of the octanol layer decreased, the EFs increased. This implies that decreasing the volume of the organic phase resulted in higher levels of analyte enrichment during the extraction process. However, the experiment also revealed that for octanol volumes below 30 nL, increasing the extraction time and employing agitation at a rate of 300 rpm caused the drop to become unstable. This instability in the drop could negatively impact the efficiency of the extraction process. Based on these findings, it was concluded that administering 30 nL of octanol as the intermediate organic phase was the most ideal approach. This volume struck a balance between achieving higher EFs and maintaining the stability of the extraction process. 3.4 Agitation Speed Figure 4 reveals that the application of agitation during the extraction process can lead to higher enrichment factor (EF) values for a given extraction time. Agitation promotes the mass transfer coefficients by reducing the Nernst diffusion film thickness [13], which is represented by the equation β = κ/δ, where κ is the diffusion coefficient and δ is the film thickness [13].

Fig. 4. Electropherograms of standards solutions of three NSAIDs (e.g., ketoprofen (KTP, 1), ibuprofen (IBU, 2), and naproxen (NAP, 3)) in different CE modes: (a) Electropherogram obtained from CE after dilution of 500 µM analytes in 320 mM borate buffer (pH 9.8); (b) Electropherogram obtained after enrichment of 1 µM analytes in DI-SDME-CE for 5 min without (w/o) stirring; and (c) Electropherogram obtained after enrichment of 1 µM analytes in DI-SDME-CE for 5 min with stirring (300 rpm).

36

N. Nciri

To evaluate the impact of agitation, the EFs of a 5-min DI-SDME-CE at a temperature of +25 ºC were compared under two conditions: without stirring (w/o) and with stirring at a speed of 300 rpm. The results of this comparison are illustrated in Fig. 4. It was observed that when agitation was applied, the EFs increased significantly, reaching values that were six-to-eightfold higher compared to the non-agitated condition. Specifically, for the analyte KTP, the EF increased from 110 to 700, for IBU it increased from 60 to 470, and for NAP it increased from 105 to 730. This demonstrates that the application of agitation plays a crucial role in enhancing the extraction efficiency. By promoting mass transfer, agitation helps to overcome the diffusion limitations and reduce the thickness of the diffusion film. As a result, the analytes are more effectively transferred from the donor phase to the acceptor phase, leading to higher concentrations in the acceptor phase and thus increasing the EF values. Overall, the findings emphasize the importance of agitation in improving the performance of the DI-SDME-CE technique. By utilizing agitation, it is possible to achieve significantly higher EF values, thereby enhancing the sensitivity and efficiency of the extraction process and subsequent analysis. 3.5 Extraction Time Under the established optimal conditions, the maximum extraction time was set to 5 min. Figure 5 presents the results obtained for the EFs (enrichment factors) of DI-SDME-CE with stirring at 300 rpm and a temperature of +25 °C over different extraction timeframes. It was observed that the EFs increased almost linearly with time until reaching the 5-min mark. However, beyond that point, the increase in EFs became less substantial. Simultaneously, the relative standard deviations (RSDs) of the EFs progressively increased with time. The RSD is a measure of the variability or precision of the extraction process. The increasing RSDs indicate that the extraction efficiency becomes less consistent and more prone to variations as the extraction time is extended. Considering both the EFs and RSDs, the optimal extraction time was determined to be 5 min. This time frame allows for a significant increase in the EFs while still maintaining a reasonable level of precision and reproducibility in the extraction process. By setting the extraction time to 5 min, researchers can achieve a balance between maximizing the enrichment factor and ensuring consistent results. This optimization ensures efficient extraction of analytes while minimizing potential variations and uncertainties associated with longer extraction times. Overall, the determination of the optimal extraction time in DI-SDME-CE is crucial for obtaining reliable and accurate results in the analysis of target analytes. The 5-min extraction time was identified as the most suitable duration based on the trade-off between higher EFs and manageable RSDs.

A Swift, Straightforward, and Innovative Approach

37

Fig. 5. Effect of the extraction time variation on the enrichment factor (EF) of ketoprofen (KTP), ibuprofen (IBU), and naproxen (NAP). Instrument: P/ACE™ MDQ system; Bare fused silica capillary: 60/50 bare fused silica (I.D. = 50 µm, O.D. = 360 µm, polyimide coating 5 µm); Temperature: +25 ºC; Absorbance detection: 214 nm; Run buffer: 320 mM sodium tetraborate decahydrate (pH 9.8); Donor phase: 1 µM KTP, 1 µM IBU, and 1 µM NAP (pH 2); Organic phase: 30 nL octanol (2 psi, 7.6 s); Acceptor phase: 320 mM sodium borate buffer (run buffer, pH 9.8); Rinse solution: 60 psi; 0.1 M NaOH, deionized water (DIW), buffer (2, 3, and 7 min); Drop formation: backpressure [0.7 psi; 23.8 s (3 nL), 25.3 s (5 nL), 27.5 s (8 nL), and 30.3 s (12 nL)]; Maintenance of drop shape: 0.4 min with a backpressure of 0.1 psi for every 0.9 min of extraction (3 nL), 0.38 min with a backpressure of 0.1 psi for every 0.88 min of extraction (5 nL), 0.23 min with a backpressure of 0.1 psi for every 0.73 min of extraction (8 nL), and 0.16 min with a backpressure of 0.1 psi for every 0.86 min of extraction (12 nL); Extraction time: 1, 2.5, 5, 7.5 and 10 min without (w/o) stirring; Sample injection: (0.5 psi, 3 s); Separation voltage: +20 kV; The standard deviations are shown as error bars (n = 4).

3.6 Analytical Performance This section discusses the performance of a DI-SDME-CE (i.e., direct immersion singledrop microextraction coupled in-line with capillary electrophoresis) method for the analysis of three NSAIDs (i.e., nonsteroidal anti-inflammatory drugs): ketoprofen (KTP), ibuprofen (IBU), and naproxen (NAP). Here is an explanation of the key points: Table 1 summarizes the results of the DI-SDME-CE method for the three NSAIDs. The EF (enrichment factor) values indicate the concentration enhancement achieved by the extraction method. For example, when the extraction was conducted at +25 ºC for 5 min with stirring (300 rpm), KTP had an EF value of 700, IBU had an EF value of 470, and NAP had an EF value of 730. Higher EF values indicate a greater concentration increase.

38

N. Nciri

The LOD represents the lowest concentration of an analyte that can be reliably detected. In this case, the LOD for KTP was 1.4 nM, for IBU it was 3.8 nM, and for NAP it was 1.3 nM. Lower LOD values indicate higher sensitivity of the method for detecting the analytes. The study by Garcia-Vazquez and colleagues [14] assessed a three-phase DI-SDMECE method for NSAIDs. They performed an off-line extraction of the analytes from 400 µL of pH 2 solution into 300 µL of organic phase (ethyl acetate). Subsequently, a 10-min back extraction into a 510 nL acceptor phase drop of 0.001 M NaOH was conducted. The resulting EF values were 27 for KTP, 12 for IBU, and 44 for NAP. Comparatively, these EF values were lower than the ones obtained in the current research. The main distinction between the current DI-SDME-CE method and the one used by Garcia-Vazquez et al. [14] is the scale of the extraction apparatus. Assuming that the partition coefficients of the analytes between octanol and water are similar to those between ethyl acetate and water, the equilibrium EF values derived from Eq. (1) are estimated to be 500–600 for the previous research and 50,000–150,000 for the present research. This substantial difference in EF values is attributed to the small volume of the acceptor drop (as described in Eq. (4)) and the thin organic phase used in the current DISDME-CE method. The 5-min extraction in the present research resulted in EF values that were 60–130 times higher than those obtained in the previous study. Overall, the results demonstrate the improved performance of the current DI-SDMECE method in terms of higher EF values and lower LODs, indicating its suitability for the sensitive analysis of NSAIDs. Table 1. DI-SDME-CE Performance. Analyte

RSD (n = 4)

EF

LOD (nM, S/N = 3)

Linear range (nM)

Linearity (r 2 )

Calibration curve(b)

11

700

1.4

100–1000

0.9895

y= 6.1815x + 158.14

0.9

9

470

3.8

100–1000

0.9982

y= 2.3608x + 7.3907

1.0

10

730

1.3

100–1000

0.9921

y = 7.03x + 75.682

MT(a) (%)

CPA(a) (%)

KTP

0.9

IBU

NAP

Donor phase: 1 µM analytes in HCl solution (pH 2); Organic phase: octanol (30 nL); Acceptor phase: run borate buffer (5 nL, pH 9.8); Extraction: 5 min with stirring at a speed of 300 rpm and at a temperature of +25 ºC; a) MT: migration time; CPA: corrected peak area (peak area/MT); b) y: corrected peak area (µAU·s); x: concentration (nM).

A Swift, Straightforward, and Innovative Approach

39

4 Conclusions Direct-immersion (DI) three-phase single-drop microextraction coupled in-line with capillary electrophoresis (SDME-CE) is a relatively new approach to sample preparation. It involves the use of a single droplet that contains three different phases: donor, organic, and acceptor. The donor phase contains the analyte of interest, while the acceptor phase acts as a sink for this analyte. The organic phase forms an octanol film around the droplet, which helps to extract and concentrate the analyte from the donor phase. One advantage of DI-SDME-CE over other extraction techniques is its simplicity. All three phases can be easily manipulated using small volumes of liquid in the microliter or nanoliter range. This makes it particularly useful when working with limited sample volumes, such as biofluids or drug-contaminated drinking water supplies. Moreover, using DI-SDME-CE to separate analytes from complex matrices prior to CE analysis can improve the selectivity and sensitivity of this separation technique. Due to its simple implementation steps without requiring any sophisticated equipment or organic solvents and low reagent consumption, make this method attractive compared to conventional extraction techniques like solid-phase extraction or liquid-liquid extraction. Another advantage is its rapidity and efficiency; due to its small dimensions, high enrichment factors can be obtained within minutes at room temperature with stirring. Furthermore, since only one drop is used in each extraction step, there are no carry-over effects between samples. The DI-SDME-CE method has proven useful for determining trace amounts of NSAIDs accurately while being environmentally friendly. It is believed that this technique will gain more recognition in environmental analysis research because it provides rapid results with high selectivity and sensitivity compared to existing techniques.

References 1. Fent, K., Weston, A., Caminada, D.: Ecotoxicology of human pharmaceuticals. Aquatic Toxicol. 76(2), 122–159 (2006) 2. Rastogi, A., Tiwari, M.K., Ghangrekar, M.M.: A review on environmental occurrence, toxicity and microbial degradation of non-steroidal anti-inflammatory drugs (NSAIDs). J. Environ. Manage. 300, 113694 (2021) 3. da Silva, T.L., Costa, C.S.D., da Silva, M.G.C., Vieira, M.G.A.: Overview of non-steroidal anti-inflammatory drugs degradation by advanced oxidation processes. J. Clean. Prod. 346, 131226 (2022) 4. Gentili, A.: Determination of non-steroidal anti-inflammatory drugs in environmental samples by chromatographic and electrophoretic techniques. Anal. Bioanal. Chem. 387(4), 1185–1202 (2006) 5. Aguilar-Arteaga, K., Rodriguez, J.A., Miranda, J.M., Medina, J., Barrado, E.: Determination of non-steroidal anti-inflammatory drugs in wastewaters by magnetic matrix solid phase dispersion–HPLC. Talanta 80(3), 1152–1157 (2010) 6. Ling, H., Wu, G., Li, S., Zhou, Q., Li, C., Ma, J.: Determination of five nonsteroidal antiinflammatory drugs in water by dispersive solid phase extraction-ultra performance liquid chromatography-tandem mass spectrometry based on metal-organic framework composite aerogel. Chin. J. Chromatogr. 40(4), 323–332 (2022)

40

N. Nciri

7. Ye, C., Zhou, Q., Wang, X.: Improved single-drop microextraction for high sensitive analysis. J. Chromatogr. A 1139(1), 7–13 (2007) 8. Li, X., Li, Q., Xue, A., Chen, H., Li, S.: Dispersive liquid–liquid microextraction coupled with single-drop microextraction for the fast determination of sulfonamides in environmental water samples by high performance liquid chromatography-ultraviolet detection. Anal. Methods 8(3), 517–525 (2016) 9. Petr, J., Jiang, C., Sevcik, J., Tesarova, E., Armstrong, D.W.: Sterility testing by CE: a comparison of online preconcentration approaches in capillaries with greater internal diameters. Electrophoresis 30(22), 3870–3876 (2009) 10. Kannouma, R.E., Hammad, M.A., Kamal, A.H., Mansour, F.R.: Miniaturization of liquidliquid extraction; the barriers and the enablers. Microchem. J. 182, 107863 (2022) 11. Ma, M., Cantwell, F.F.: Solvent microextraction with simultaneous back-extraction for sample cleanup and preconcentration: quantitative extraction. Anal. Chem. 70(18), 3912–3919 (1998) 12. Ma, M., Cantwell, F.F.: Solvent microextraction with simultaneous back-extraction for sample cleanup and preconcentration: preconcentration into a single microdrop. Anal. Chem. 71(2), 388–393 (1998) 13. Jeannot, M.A., Cantwell, F.F.: Mass transfer characteristics of solvent extraction into a single drop at the tip of a syringe needle. Anal. Chem. 69(2), 235–239 (1997) 14. García-Vázquez, A., Borrull, F., Calull, M., Aguilar, C.: Single-drop microextraction combined in-line with capillary electrophoresis for the determination of nonsteroidal antiinflammatory drugs in urine samples. Electrophoresis 37(2), 274–281 (2015)

Adsorption of Chromium(VI) from Simulated Wastewater Using Colocasia esculenta Leaf and Petiole Fibers Kathlia D. Cruz1,3(B) , Andrei Jericho B. Regindin2 , Paulo Gabriel I. Rivera2 , Francis Marcus J. Garcia2 , Nam Seung Beom2 , Gerald C. Domingo3 , and May Joy S. Esguerra4 1 School of Chemical, Biological and Materials Engineering, and Sciences, Mapúa University,

Muralla St., Intramuros, 1002 Manila, Philippines [email protected] 2 Mapua Senior High School Department, Mapúa University, Muralla St., Intramuros, 1002 Manila, Philippines 3 Water Quality and Wastewater Research Laboratory, Mapúa University, Muralla St., Intramuros, 1002 Manila, Philippines 4 Institutional Laboratory Management Office, Mapúa University, Muralla St., Intramuros, 1002 Manila, Philippines

Abstract. Chromium(VI) is a highly toxic metal present in an aqueous environment and wastewater due to its high solubility with water. Meanwhile, Colocasia esculenta is a plant common in wetlands with significant biosorption chemical content. The biosorption capacity of taro leaves and petioles, untreated and treated, was considered using the standard addition method. Concerned parameter like contact time was investigated. A comparative study was also executed to know which among the studied biomasses performed the best. Findings of the study hitherto revealed that at 30 min, the untreated leaves and petioles reached their equilibrium, tallying 99.6798% ± 4.9376% removal and 99.5212% ± 2.9307% removal, respectively. However, results also reported that modification further enhanced the adsorption capacity with 99.9655% ± 0.4514% removal for treated leaves and 99.9889% ± 1.9876% removal for treated petioles. Furthermore, F-test confirmed that the biosorption efficiency of the two treated adsorbents is statistically equal but statistically higher than the efficiency of the two untreated adsorbents. Keywords: Colocasia esculenta · Taro Leaves and Petioles · Biosorption · Chromium(VI)

1 Introduction Chromium is a naturally occurring element in volcanic ash, soils, and rocks [1]. It exists in different oxidation states (i.e., trivalent, quaternary, and hexavalent), of which hexavalent and trivalent are the most stable species. Hexavalent chromium is a highly toxic oxyanion species that can enter the cells, subsequently reduced into radicals (i.e., hydroxyl © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 J. Kim and Z. Chen (Eds.): CGEEE 2023, SPEES, pp. 41–52, 2024. https://doi.org/10.1007/978-3-031-52330-4_4

42

K. D. Cruz et al.

radicals and thiyradicals), Cr(V), and Cr(IV), then finally into Cr(III). The presence of these oxidation states in living organisms damages protein, membrane lipids, and DNA, compromising the cell’s integrity [2–4]. The International Agency for Research on Cancer ranked chromium as the number one carcinogen, and Agency for Toxic Substances and Disease Registry classified chromium as the 17th most dangerous substance [5, 6]. Industrial processes (i.e., dyeing, printing, tanning, metal plating) and mining contribute to the significant increase of chromium concentrations in chromate and dichromate in an aqueous environment and wastewater due to their effluents discharge [7]. Hexavalent chromium, highly soluble in soil and water, can contaminate groundwater and spread down the food chain [8, 9]. Therefore, several methods have been employed to minimize or eliminate the concentration of hexavalent chromium, such as coagulation, chemical settling process, reverse osmosis, ion exchange, and adsorption. Among the said methods, increasing interest lies in adsorption due to its several advantages compared to other methods [10]. Biosorption, a subgroup of adsorption, utilizes biomass as the sorbents. Ion exchange, surface complexation, and microprecipitation are the primary mechanism involved in metal biosorption. In the case of chromium, whose predominant forms exist as anionic, the acidic pH (2.0–4.0) is more favorable due to the greater attraction of anions (metals) with the positive charges of the biomass [11]. Furthermore, the presence of functional groups such as sulfonate, phosphoryl, amino, and carboxyl affects the biosorption of metals [12, 13]. Colocasia esculenta, commonly known as Taro, is primarily grown in tropical areas like Southeast Asia and Africa. It can adapt in wetlands like marshes and swamps, which makes it one of the most readily available plants in the country. More importantly, C. esculenta contains a high concentration of oxalates which is used as a defense mechanism of plants against toxic metals via metal chelation [14, 15]. Furthermore, the chemical composition of Taro leaves includes cellulose (21.73%), hemicellulose (15.18%), crude protein (29.71%), lignin (11.90%), moisture (93.88%), and ash (9.23%) [16]. These cellulose, hemicellulose, and lignin present in the cell walls are the biomass constituents that are the most important sorption sites [11]. Therefore, this study aims to determine the chromium(VI) biosorption of untreated and treated C. esculenta leaves and petioles. Moreover, the effect of contact time of the biosorbents with Cr(VI) is studied for treated and untreated biosorbents, followed by a comparative study to determine the effect of pre-treatment on the biosorption kinetics.

2 Methodology 2.1 Characterization of Adsorbents The samples were examined, observed, and characterized using Fourier transform infrared (FTIR) analysis to identify the chemical groups present in the biosorbents. A study reported that the most important metal sorption sites are functional groups such as carboxyl, hydroxyl, carbonyl, amine, phosphate, and sulfhydryl [11]. The characterization test was used to support the capacity of the biomass to adsorb Cr(VI) ions.

Adsorption of Chromium(VI) from Simulated Wastewater

43

2.2 Preparation of Cr(VI) Standard Solution The 10 mg/L chromium(VI) stock solution was prepared by dissolving 28.3 mg of K2 Cr2 O7 in 1000 mL of 0.05 M of HNO3 in deionized water. Then, 30 mL of the stock solution was diluted to 50 mL to obtain a 6 mg/L concentration as the Cr(VI) standard solution. Meanwhile, 500 mg/L of the complexing reagent solution was prepared by dissolving 50 mg of 1,5 – diphenylcarbazide in 100 mL of acetone and stored in an amber bottle. The wavelength of maximum absorbance was determined spectrophotometrically using a UV-VIS spectrophotometer. 2.3 Preparation and Modification of Adsorbent Four (4) adsorbents were used in this study – untreated taro leaves, modified taro leaves, untreated taro petioles, and modified taro petioles. The Taro leaves, and petioles were collected from a local taro plantation in Open Canal, General Trias, Cavite, Philippines. The leaves were washed severally with tap water to remove dirt and dust and air-dried at room temperature for at least 6 h before being dried in an oven at 110 °C for 24 h. The dried leaves were ground using a highspeed blender and further with mortar and pestle before being sieved through 60 mesh sizes. The petioles were cut into cubes of an average size of 2 cm × 2 cm × 2 cm. The cubes were also air-dried for at least 6 h before drying in an oven at 110 °C for 12 h. The resulting material was ground using a high-speed blender, mortar, and pestle, then sieved through 60 mesh sizes. Half of the powdered leaves and petioles were set aside, and the other half was subjected to modification. The modification involves soaking leaves and petioles powder (separately) in 0.1M HNO3 for 36 h (50 g of leaves and petioles powder will be soaked per liter). It was then filtered and washed with distilled water to remove acid contents until the pH of the filtrate became merely neutral. Afterward, it was dried at room temperature in an oven at 105 °C to remove moisture. These biomasses were stored in an air-tight glass bottle to protect them from humidity. 2.4 Adsorption Procedure Batch experiments were carried out at constant operating conditions: pH level, temperature, initial metal concentration, and biomass dosage. The pH level was maintained at 2.0 ± 0.2 to keep the Cr(VI) ions from converting into Cr(III) ions based on several studies [17–20]. The temperature was set at room temperature while the initial metal concentration and adsorbent dosage were predetermined at 10 mg/L and 1 g, respectively. All experiments were prepared in triplicates. In determining the adsorption equilibrium time, 1 g of each adsorbent was mixed with the prepared 100 mL of 10 mg/L Cr(VI) solutions. The test samples were agitated constantly on a mechanical shaker at 300 rpms, and samples were collected at different predetermined time intervals (5, 10, 15, 30, and 60 min). After the completion of each batch of experiments, the solution was filtered. 10 mL was taken as a sample, and its pH was adjusted to 2.0 ± 0.2 by adding 1 mL of 0.5 M of phosphoric acid and 1 mL of 0.5 M of sulfuric acid before complexation. The solution was then transferred to a 50-mL volumetric flask and diluted to mark using deionized water. Afterward, the solution was

44

K. D. Cruz et al.

developed by adding 0.5 mL of 500 mg/L 1,5 – diphenylcarbazide in acetone solution and allowed to stand for 10 min for untreated adsorbents and 1 min for treated adsorbents before spectrophotometric reading. An appropriate portion was transferred to the cuvette and measured the absorbance at 540 ± 10 nm with the blank as a reference. The standard calibration method was first used to analyze the amount of metal left after biosorption with a calibration equation below having R2 = 0.9965. y = 0.0047x + 0.0071

(1)

where y is the absorbance and x is the concentration in mg/L derived from a calibration curve plotted from different standard concentrations (0.5, 2, 4, 6 mg/L, 8 mg/L, and 10 mg/L) for the quantification of hexavalent chromium ions in the simulated aqueous solutions. However, no pink color was developed on the samples with its complexation with 1,5 diphenylcarbazide in acetone due to the low sensitivity of low Cr (VI) concentrations and low detection limits of Cr (VI) in the samples. Therefore, the standard addition method was employed to determine hexavalent chromium ions. The test samples were spiked with 0, 3, 6, 9, and 12 mL of 6 mg/L Cr (VI) standard. Lastly, % Removal (p) was determined using the formula: p=

C0 − Cf × 100 C0

(2)

where co is the initial concentration of metal in solution in mg/L and cf is the final concentration of the metal in solution in mg/L. The average percent heavy metal removal of the adsorbent for each biomass will be compared with each other and subjected to statistical treatment. 2.5 Statistical Tools and Treatment The data gathered through experimentation was subjected to the Analysis of Variances (ANOVA) test followed by the Tukey test. The test was used to determine whether there was a significant difference among the means of the four biomasses.

3 Results and Discussion 3.1 FT-IR Analysis of Biosorbents To determine the vibration frequency changes in the functional groups in the four studied biosorbents, the FT-IR spectra of the untreated leaves, untreated petioles, treated leaves, and treated petioles before and after biosorption of hexavalent chromium ions were plotted. The samples were examined within the range of 600–4000 cm−1 . Table 1 parades the prominent peaks of all the adsorbents before and after use, while Fig. 1 and 2 display the spectra of taro leaves and taro petioles, respectively. The adsorption peaks shown indicate the complex nature of the studied biosorbents.

Adsorption of Chromium(VI) from Simulated Wastewater

45

Table 1. Prominent peaks (at cm−1 ) in the FT-IR spectra of the of untreated leaves (UL), untreated petioles (UP), treated leaves (TL), and treated petioles (TP) Adsorbents

O-H

C-H

C=O

–CH3

UL – Before

3277.32

2918.81

1619.97

1024.05

UL – After

3258.12

2918.69

1631.86

1016.58

TL – Before

3285.23

2918.58

1625.30

1026.05

TL – After

3285.59

2918.56

1627.16

1029.91

UP – Before

3277.57

2920.75

1504.35

1017.83

UP – After

3328.99

2919.99

1605.10

1014.91

TP – Before

3329.95

2920.96

1618.43

1018.00

TP – After

3331.68

2915.55

1628.39

1018.48

The FT-IR spectra suggest that the four biosorbents contain cellulosic components evident by the strong and broad stretch ranging from 3000 to 3600 cm−1 with peaks around 3200 to 3350 cm−1 indicating the presence of O-H or hydroxyl group, peaks observed around 2900–2950 cm−1 signifying C-H group, peaks located around 1500 to 1650 cm−1 denoting the presence of C = O or a carbonyl group. It can also be seen in the spectra that the strong C-O band around 1000 to 1050 cm−1 due to the –OCH3 group justifies the presence of a lignin structure. The decrease of peaks, shifting of peaks, disappearance of peaks, and appearance of new peaks are apparent in the spectra of untreated and treated taro leaves before and after hexavalent chromium biosorption. As seen in Fig. 1., the stretch around 3300 cm−1 attributed to the O-H group significantly depressed and shifted alongside the C-H stretch about 2900 cm−1 and C = O stretch around 1600 cm−1 . The peaks around 1000 cm−1 attributed to the –CH3 group also weakened. On the other hand, prominent peaks were all shifted, as observed from the spectra of untreated and treated taro petioles before and after hexavalent chromium biosorption presented in Fig. 2. In the FT-IR spectrum of untreated petioles, the band of peaks at 3277.57, 2920.75, 1504.35, and 1017.83 cm−1 were all shifted (shifted to 3328.99, 2919.99, 1605.10, and 1014.91 cm−1 , respectively) and decreased after biosorption of hexavalent chromium ions. Similarly, the treated petioles demonstrated in its FT-IR spectrum that the band of peaks at 3329.95, 2920.96, 1618.43, and 1018.00 all shifted to 3331.68, respectively 2915.55, 1628.39, and 1018.48 cm−1 and decreased.

46

K. D. Cruz et al.

Fig. 1. Fourier transform infrafred (FT-IR) spectrum of untreated (top image) and treated (bottom image) Taro leaves before and after biosorption.

All the above results, a decrease of peaks, shifting of peaks, the disappearance of peaks, and the appearance of new peaks, suggest that functional groups of O-H, C-H, C = O, and –CH3 have actively participated in the Cr(VI) biosorption. 3.2 Effect of Contact Time A previous study reported that evaluating the effect of contact time in the adsorption process is vital preliminary to the kinetic study of the adsorption [21]. A batch adsorption study used untreated and treated Taro (Colocasia esculenta) leaf and petiole fibers as biosorbents at constant operating conditions and varying contact times. Operating conditions are predetermined; initial metal concentration was set at 10 mg/L, adsorbent dose at 1 g per 100 mL solution, pH at 2.0 ± 0.2, temperature at room temperature, and stirring speed at 300 rpms.

Adsorption of Chromium(VI) from Simulated Wastewater

47

Fig. 2. Fourier transform infrafred (FT-IR) spectrum of untreated (top image) and treated (bottom image) taro petioles before and after biosorption.

The results obtained are summarized in Table 2 and Fig. 3 below. Table 2 shows the exact values of hexavalent chromium ions uptake efficiency of the four biosorbents, while Fig. 3 parades the efficiency trend as the contact time increases. As seen in Table 2 and Fig. 3, the plot for the untreated leaves reveals that the rate for the hexavalent chromium ions uptake is higher for the first 30 min before it reached its equilibrium time at the same time point with 97.3314% ± 4.8213% efficiency. Similarly, with the untreated leaves, the plot for the untreated petiole still shows a rapid increase in its first 30 min, although not as rapid as untreated leaves. At 30 min, the chromium (VI) ion removal efficiency of the untreated petioles also reached its equilibrium with 96.0104

48

K. D. Cruz et al. Table 2. Percent removal for hexavalent chromium ions of the four studied biosorbents

Adsorbent

Contact Time 5 min

10 min

15 min

30 min

60 min

U. Leaves

22.0714% ± 1.4387%

24.2819% ± 1.1842%

51.8495% ± 2.9419%

97.3314% ± 4.8213%

98.0733% ± 6.0636%

U. Petioles

86.4959% ± 5.1584%

89.5327% ± 2.5658%

91.0461% ± 2.9385%

96.0104% ± 2.8273%

97.6500% ± 4.3172%

T. Leaves

99.7123% ± 0.4514%

99.7715% ± 0.5798%

99.8782% ± 1.6809%

99.9674% ± 6.1510%

99.9705% ± 6.7042%

T. Petioles

99.9078% ± 1.9876%

99.9236% ± 3.6661%

99.9852% ± 6.0863%

99.9872% ± 3.5828%

99.9930% ± 7.0891%

100

% Removal

80 Treated Leaves Treated Petioles Untreated Leaves Untreated Petioles

60 40 20 0 0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

Contact Time (mins)

Fig. 3. Percent removal for hexavalent chromium ions of the four studied biosorbents

± 2.8273% hexavalent chromium ion percent removal; further increase in contact time does not significantly increase the adsorption capacities of the said biosorbent. Therefore, the optimum contact time of Cr(VI) for the untreated leaves and untreated petioles is 30 min. The plots of both untreated leaves and untreated petioles show that the uptake of hexavalent chromium ions consists of two sorption stages – the first stage wherein the adsorption process proceeds rapidly and the second stage wherein the increment of the adsorption effectivity is not significant even if the contact time is increased. According to da Costa and Leite (1991), the first rapid stage can be ascribed to the abundant availability of sorption sites on the biosorbent, and with the gradual and continuous accumulation of metal ions on these sites, the sorption process turns out to be less efficient in the second slower stage [22]. This is parallel with the observations of Pehlivan et al. (2008) and Yu et al. (2015), stating that the phenomenon could have been because the active sites on the surface of the adsorbent were vacant. After that period, fewer surface active sites are available, resulting in a very low increase in the uptake of metal ions [23, 24].

Adsorption of Chromium(VI) from Simulated Wastewater

49

Conversely, both treated leaves and treated petioles biosorbents show almost 100% removals even in the first 5 min. Treated leaves biomass tallied 99.7123% ± 0.4514%, while treated petioles biomass marked 99.9078% ± 1.9876%. Further increase in the contact time still increases the chromium (VI) uptake of both biosorbents. However, at 30 min, both the treated biosorbents came nearer to a hundred percent removal, with 99.9674% ± 6.1510% for treated leaves and 99.9872% ± 3.5828% for treated petioles. However, the two sorption stage isn’t very evident for these treated biomasses. 3.3 Comparative Study on the Four Studied Adsorbents To know whether there is a significant difference in the hexavalent chromium ion uptake of the four studied adsorbents, data were run in an F-test or One-Way Analysis of Variance (ANOVA). The results of the test are encapsulated in Table 3. Table 3. F-test computation on the significant difference in the percent removal of four studied adsorbents Samples

Mean

F-Value

P-Value

Decision

Remarks

UL

0.973314

322.207

0.000

Reject Ho

Significant

UP

0.960104

TL

0.999674

TP

0.999872

As seen in the table above, there is a significant difference between the percent removals of the four studied biomasses. This is surmised from the F-value obtained of 322.207 or the p-value of 0.000 at a 0.050 level of significance. Results point out the rejection of the null hypothesis since the obtained p-value is less than the significance level, 0.000 < 0.050. In this case, a post hoc test, specifically Tukey, where equal variances are assumed, is executed to know how specific the significant difference is. The results of the post hoc test are summarized in Table 4. Table 4. Post Hoc Test (Tukey) Results Samples

Mean Difference P-Value Decision

Remarks

Interpretation

UL vs. UP

0.013210

0.000

Reject Ho

Significant

UL > UP

UL vs. TL

−0.026360

0.000

Reject Ho

Significant

UL < TL

UL vs. TP

−0.026556

0.000

Reject Ho

Significant

UL < TP

UP vs. TL

−0.039571

0.000

Reject Ho

Significant

UP < TL

UP vs. TP

−0.039768

0.000

Reject Ho

Significant

UP < TP

TL vs. TP

−0.000198

0.999

Do Not Reject Ho

Not Significant TL = TP

50

K. D. Cruz et al.

The post hoc test revealed a significant difference between the percentage uptakes for hexavalent chromium ion of the following biosorbents: 1. Untreated Leaves (mean = 0.973314) and Untreated Petioles (mean = 0.960104); 2. Untreated Leaves (mean = 0.973314) and Treated Leaves (mean = 0.999674); 3. Untreated Leaves (mean = 0.973314) and Treated Petioles (mean = 0.999872); 4. Untreated Petioles (mean = 0.960104) and Treated Leaves (mean = 0.999674), and; 5. Untreated Petioles (mean = 0.960104) and Treated Petioles (mean = 0.999872). On the other hand, there is no significant difference in the means of the percent removals of the two treated biomasses. Moreover, it can also be seen that the means of the hexavalent chromium ion uptake capacity of the two treated adsorbents are significantly higher than those of the two untreated. This suggests, statistically speaking, the treatment or modification method increases the capability of the plant to adsorb chromium (VI) ions from a synthetic aqueous solution. These values are true at a 0.050 level of significance.

4 Conclusion This study confirms the adsorption capability of Colocasia esculenta leaves and petioles (untreated and treated) towards chromium(VI) using a simulated wastewater solution, followed by a comparative study of the prepared adsorbents based on their respective adsorption capacity. The results reveal that at 30 min, the untreated biomasses reached their equilibrium with 97.3314% ± 4.8213% efficiency for untreated leaves and 96.0104% ± 2.8273% efficiency for untreated petioles. However, the treated biomasses showed spectacular performance even in just 5 min, tallying 99.7123% ± 0.4514% removal for treated leaves and 99.9078% ± 1.9876% removal for treated leaves petioles. Moreover, the comparative study reports that the chromium (VI) adsorption of the two treated biomasses is statistically equal but statistically higher and significant than the two untreated biomasses. In essence, the modification or treatment method executed played an important role in increasing the capacity of the Colocasia esculenta leaves and petioles to adsorb hexavalent chromium ions. Hence, untreated and treated taro leaves and petioles exhibit great potential in removing the carcinogenic heavy metal chromium6 from an aqueous solution through adsorption, with treated biosorbents having better adsorption capacity than the two untreated adsorbents.

References 1. Fazlzadeh, M., Rahmani, K., Zarei, A., Abdoallahzadeh, H., Nasiri, F., Khosravi, R.: A novel green synthesis of zero valent iron nanoparticles (NZVI) using three plant extracts and their efficient application for removal of Cr(VI) from aqueous solutions. Adv. Powder Technol. 28(1), 122–130 (2017). https://doi.org/10.1016/j.apt.2016.09.003 2. Samani, M.R., Toghraie, D.: Using of polyaniline-polyvinyl acetate composite to remove mercury from aqueous media. Int. J. Environ. Res. 14(3), 303–310 (2020). https://doi.org/10. 1007/s41742-020-00256-3 3. Tchounwou, P.B., Yedjou, C.G., Patlolla, A.K., Sutton, D.J.: Heavy metal toxicity and the environment. In: Luch, A. (ed.) Molecular, Clinical and Environmental Toxicology. Experientia Supplementum, vol. 101, pp. 133–164. Springer, Basel (2012). https://doi.org/10.1007/ 978-3-7643-8340-4_6

Adsorption of Chromium(VI) from Simulated Wastewater

51

4. Stambulska, U.Y., Bayliak, M.M., Lushchak, V.I.: Chromium(VI) toxicity in legume plants: modulation effects of Rhizobial symbiosis. BioMed Res. Int. 2018, 1–13 (2018). https://doi. org/10.1155/2018/8031213 5. Substance Priority List | ATSDR (2023). https://www.atsdr.cdc.gov/spl/index.html. Accessed 29 Mar 2023 6. Overall evaluations of carcinogenicity: an updating of IARC Monographs volumes 1 to 42. IARC Monogr. Eval. Carcinog. Risks Hum. Suppl. 7, 1–440 (1987) 7. Liu, W., et al.: Different pathways for Cr(III) oxidation: implications for Cr(VI) reoccurrence in reduced chromite ore processing residue. Environ. Sci. Technol. 54(19), 11971–11979 (2020). https://doi.org/10.1021/acs.est.0c01855 8. Kumar, V., et al.: Global evaluation of heavy metal content in surface water bodies: a meta-analysis using heavy metal pollution indices and multivariate statistical analyses. Chemosphere 236, 124364 (2019). https://doi.org/10.1016/j.chemosphere.2019.124364 9. Joutey, N.T., Sayel, H., Bahafid, W., El Ghachtouli, N.: Mechanisms of hexavalent chromium resistance and removal by microorganisms. In: Whitacre, D.M. (ed.) Reviews of Environmental Contamination and Toxicology. Reviews of Environmental Contamination and Toxicology, vol. 233, pp. 45–69. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-10479-9_2 10. Sharma, A., et al.: Chromium bioaccumulation and its impacts on plants: an overview. Plants 9(1), 100 (2020). https://doi.org/10.3390/plants9010100 11. Volesky, B., Weber, J., Park, J.M.: Continuous-flow metal biosorption in a regenerable Sargassum column. Water Res. 37(2), 297–306 (2003). https://doi.org/10.1016/S0043-1354(02)002 82-8 12. Torres, E.: Biosorption: a review of the latest advances. Processes 8(12), 1584 (2020). https:// doi.org/10.3390/pr8121584 13. Zhang, J., Chen, X., Zhou, J., Luo, X.: Uranium biosorption mechanism model of protonated Saccharomyces cerevisiae. J. Hazard. Mater. 385, 121588 (2020). https://doi.org/10.1016/j. jhazmat.2019.121588 14. Gadd, G.M., et al.: Oxalate production by fungi: significance in geomycology, biodeterioration and bioremediation. Fungal Biol. Rev. 28(2–3), 36–55 (2014). https://doi.org/10.1016/j.fbr. 2014.05.001 15. Oxalate content of different taro cultivars grown in central Viet Nam and the effect of simple processing methods on the oxalate concentration of the processed forages. http://www.lrrd. org/lrrd23/6/hang23122.htm. Accessed 29 Mar 2023 16. Saenphoom, P., Chimtong, S., Phiphatkitphaisan, S., Somsri, S.: Improvement of taro leaves using pre-treated enzyme as prebiotics in animal feed. Agric. Agric. Sci. Procedia 11, 65–70 (2016). https://doi.org/10.1016/j.aaspro.2016.12.011 17. Sawalha, M.F., Peralta-Videa, J.R., Romero-González, J., Gardea-Torresdey, J.L.: Biosorption of Cd(II), Cr(III), and Cr(VI) by saltbush (Atriplex canescens) biomass: Thermodynamic and isotherm studies. J. Colloid Interface Sci. 300(1), 100–104 (2006). https://doi.org/10.1016/j. jcis.2006.03.029 18. Romero-González, J., Peralta-Videa, J.R., Rodr´ıguez, E., Ramirez, S.L., Gardea-Torresdey, J.L.: Determination of thermodynamic parameters of Cr(VI) adsorption from aqueous solution onto Agave lechuguilla biomass. J. Chem. Thermodyn. 37(4), 343–347 (2005). https://doi. org/10.1016/j.jct.2004.09.013 19. Oguz, E.: Adsorption characteristics and the kinetics of the Cr(VI) on the Thuja oriantalis. Colloids Surf. Physicochem. Eng. Asp. 252(2–3), 121–128 (2005). https://doi.org/10.1016/j. colsurfa.2004.10.004 20. Cimino, G.: Removal of toxic cations and Cr(VI) from aqueous solution by hazelnut shell. Water Res. 34(11), 2955–2962 (2000). https://doi.org/10.1016/S0043-1354(00)00048-8

52

K. D. Cruz et al.

21. Zhao, X., Zhang, G., Jia, Q., Zhao, C., Zhou, W., Li, W.: Adsorption of Cu(II), Pb(II), Co(II), Ni(II), and Cd(II) from aqueous solution by poly(aryl ether ketone) containing pendant carboxyl groups (PEK-L): equilibrium, kinetics, and thermodynamics. Chem. Eng. J. 171(1), 152–158 (2011). https://doi.org/10.1016/j.cej.2011.03.080 22. da Costa, A.C.A., Leite, S.G.F.: Metals biosorption by sodium alginate immobilized Chlorella homosphaera cells. Biotechnol. Lett. 13(8), 559–562 (1991). https://doi.org/10.1007/BF0103 3409 23. Pehlivan, E., Altun, T., Parlayıcı, S.: Utilization of barley straws as biosorbents for Cu2+ and Pb2+ ions. J. Hazard. Mater. 164(2–3), 982–986 (2009). https://doi.org/10.1016/j.jhazmat. 2008.08.115 24. Yu, H., Pang, J., Ai, T., Liu, L.: Biosorption of Cu2+ , Co2+ and Ni2+ from aqueous solution by modified corn silk: equilibrium, kinetics, and thermodynamic studies. J. Taiwan Inst. Chem. Eng. 62, 21–30 (2016). https://doi.org/10.1016/j.jtice.2016.01.026

Debris Flow Modeling Using FLO-2D for Hazard Identification in the Rio Seco Creek Juan Castillo S.(B)

, Amehd R. Atala V. , and Rubén E. Mogrovejo G.

Department of Civil Engineering, Peruvian University of Applied Sciences, Lima 15023, Peru [email protected]

Abstract. Debris flows are one of the processes of mass movements that are generated by heavy rains and are activated in the upper parts of the basins. The application case of the present research carried out in the Rio Seco stream in the district of San Bartolomé, located in the Province of Huarochirí, Department of Lima seeks to recreate a debris flow event that occurred on February 2, 2017 as a result of the climatic phenomenon in the Lima Andes. Likewise, it seeks to identify the areas of debris flow threats for different return periods Tr = 100 and Tr = 500 years. For this investigation, the mathematical model is applied using the FLO-2D software, which will process topographic data, rheological properties of the debris fluid and liquid hydrographs in different return periods. Finally, processing the data, results such as flow depth, maximum flow velocities of possible deposition zones, sediment concentration and impact force are obtained. This article is focused on comparing the debris flow and its depth with a real event adjusted with watermark control points. From the simulated results, debris flows were obtained with return periods of Tr = 100 years and Tr = 500 years, flows of 0.4 and 0.5 m3 /s, tie rods with flow heights of 1.80 m and 1.90 m, respectively. Additionally, the preliminary threat map was prepared to identify vulnerable areas. Keywords: hydrological model · debris flow · sediments · FLO-2D · vulnerability · mitigation

1 Introduction Debris flows are geodynamic phenomena that occur as a consequence of heavy rains such as those produced by the El Niño phenomenon [1]. Additionally, it is expected that the magnitude and frequency of this type of hazards of water origin will increase as a consequence of climate change. Much of the civil infrastructure, such as homes, communication routes, as well as crops are exposed to these landslide phenomena; In addition, overpopulation, inadequate and inefficient engineering studies, and lack of economic resources allow these events to generate more risk and damage each year, as verified by the Pan-American Health Organization [2]. Debris flows are characterized by being highly viscous saturated granular flows which can move in different directions; frequently compared to wet concrete [3]. Debris flows occur in multiple degrees of concentration within the fluid matrix. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 J. Kim and Z. Chen (Eds.): CGEEE 2023, SPEES, pp. 53–69, 2024. https://doi.org/10.1007/978-3-031-52330-4_5

54

J. Castillo S. et al.

The peculiarity that defines debris flows compared to other mass movements would be the moving interaction of large sediments and rocks mixed in a fine-grained muddy ensemble [4]. The selection and application of techniques depends to a large extent on the characterization of the site and the hazard. In Five studies carried out in Europe, three in Asia and one in the United States in most of the monitored accounts with rugged topography and rainfall between 5 and 15 mm/h are sufficient to trigger debris flows [5]. To carry out the modeling of these debris’ flows, different works have been developed using modeling such as FLO 2D for the preparation of hazard maps to avoid disasters in the period of 50 and 100 years in a town in Tacna [6]. Another work explains in its methodological development considers thresholds and analysis of vulnerability and risk through mathematical methods defining extreme values between 0.8 and 1.0 evaluating that the infrastructure must be demolished, in turn developing protocols for disasters to design containment and/or mitigation measures [7]. In addition, as an example of a containment method from an investigation carried out in Colombia by [8] extreme events, it gives guidelines for evaluation plans and containment of unstable slopes by analysis of triggering factors using the equation: (RVF) = A ∗ V ∗ P

(1)

Describing: RVF: Risk associated with physical vulnerability A: Threat VF: Physical vulnerability and P: Probability of occurrence of the event Giving quantitative results associated with the risks of physical vulnerability of slopes and unstable slopes giving low risk ratings to 66, medium between 66 and 121, high risk from 121 to 176 and very high risk may to 176. The use of FLO-2D will allow simulating flows in complex topographies; as well as the mixture of fluid made by the channels and ejection cone. In other investigations they use the SPH software obtaining results of the physical processes of the debris flow and implemented in ArcGIS for special analysis of the intensity of the threat and identify the risk level of the threat [9]. Therefore, a single software will be used that will provide the necessary data for the analysis of debris flows. This research will focus on the modeling and comparison with the study carried out in the PAIHUA creek [10] using an adequate containment system for the study area. In [11] he argues that during scenario planning in general and with respect to comprehensive risk management in particular, Formative Scenario Analysis enables the development of reliable and reproducible scenarios to more specifically design an application framework for sustainable assessment. The impact of natural hazards. This paper analyzes the identification of debris flow threats for the “San Bartolomé Channel” [12] which is vulnerable to falling debris flows, due to the inefficient or nonexistent containment that the channel presents. This movement of masses, which discharge in the lower areas of the basins, brings with it soils and rocks, which causes the obstruction of the channel, material, physical, psychological damage, crop and economic losses of the population.

Debris Flow Modeling Using FLO-2D for Hazard Identification

55

2 Methodology 2.1 Methodology and Tools The present study is of a descriptive type where the sequence of activities to be developed is summarized in Fig. 1. The topography, geology, rheology and hydrology information were obtained using the CIVIL 3D, ArcGIS 10.5, Alaska satellite facility, Alos Palsar Satellite Images, Google Earth Pro programs, in addition to the debris events that occurred in 2017 with data obtained from SENAHMI (National Service of Meteorology and Hydrology of Peru) [13]. With the contour lines obtained through GEOCATMIN (geological information system and mining contrast) the topographical survey was carried out using the shape files. These files are used in ArcGIS software to get the topographic elevations and morphological parameters. With the topographic information, the slopes covered by the debris flow were modeled. Through the analysis of the elevation data, the establishment of terrain slopes was enabled, giving a three-dimensional form to the study area. Furthermore, the range of terrain slopes according to Fidel [14], as displayed in Table 1, was taken into consideration. Table 1. Range of land slopes Slopes in degrees (°)

Classification

50

Very steep

By knowing the types of slopes of the terrain, the stability of the soil is determined, where it can be stable or unstable for unusual rainfall events. The morphological parameters of the Río Seco stream will be displayed in Table 2. The study area is located in the coordinate grid of its opposite vertices at: 206,000 m E - 9,151,000 m N, 218,000 m E - 9,142,000 m N. In which, in seasons, surface water flows due to the rain events, accumulation and fall from upper parts of the sub-basins. The basin adopts an irregularly elongated shape, slopes with pronounced slopes and in the middle and lower part it has vegetation of prickly pear crops in the great majority. For the Geology of the Huarochirí province, the information was obtained through the GEOCATMIN page. From this, the shapefile files were obtained and used in ArcGIS 10.5 to obtain parameters and enter them into the FLO-2D software.

56

J. Castillo S. et al. Table 2. Morphological parameters of the Río Seco stream Description

Parameters

Perimeter length:

1.67 km

Area:

0.15 Km2

North coordinate:

11°55 20.28 N m

West coordinate:

76°30 50.27 O m

Altitude:

1825 (MASL)

Morphology: The area is characterized by being a natural slope with a steep slope, the lower part of the town is located on the alluvial terrace of the Río Seco. Basement: They are volcanic rocks type andesitic spills of the group - Lithological II. Foundation Terrain The colluvial and residual deposits are of little power (50 cm maximum), 20% gravel, 40% gravel, and 40% coarse to medium dirty sand, poorly consolidated. Geodynamic Risk: The lower area of the town is exposed to landslides and erosion by the action of the Rio Seco River. Deficient construction of houses is observed, which would additionally be prone to suffer damage in an earthquake. The purpose of the study of the floods is to determine the probable maximum discharges for return periods of 100 and 500 years, useful for the design and implementation of debris flow containment. On the other hand, the return periods of 500 years according to the Ministry of Transport and Communications Hydrology Manual are used to calculate scour in projects to build bridges. For this, information was taken on maximum rainfall of 24 h with a worst of 32 years, recorded by the Matucana station and obtained from the SENAMHI (National Service of Meteorology and Hydrology of Peru) databases. In [15] he talks about regulating development and avoiding flood damage and loss of life. In addition, the risk of flooding in a specific area is a function of the intensity and probability of the flood. Where the intensity of the flood is comprised by the velocity of the flow and the probability of flooding is inversely dependent on the magnitude of the flood. In other words, large floods are not recurring. The flood risk of an event is defined as a combined function of intensity (event intensity) and return period (frequency). Risk map criteria initially presented in two dejection cones in Caracas are taken, where they were later adopted in different urbanized basins. It should be noted that the approach is governed by Swiss and Austrian standards, where when delineating flood risk levels, three zones are established that are expressed in Table 3 and Table 4.

Debris Flow Modeling Using FLO-2D for Hazard Identification

57

Table 3. Table of hazard degree

Intensity

High

-

-

-

-

Average

-

-

-

-

Low

-

-

-

-

High

Medium

Low

Very low

10

100

500

>>500

10%

1%

0.20%