Determination of Trace Lead, Cadmium, and Arsenic (III) in ...Determination of Trace Lead, Cadmium, and Arsenic (III) in Municipal Wastewater by Anodic Stripping Voltammetry Shengcun

Determination of Trace Lead, Cadmium, and Arsenic (III) in Municipal

Wastewater by Anodic Stripping Voltammetry

Shengcun Ma, Guo Zhao, Xingyu Chen, Ashok Mulchandani*, David Jassby**

May 10, 2021

University of California, Los Angeles (UCLA)University of California, Riverside (UCR)

UCR

Award number : FE0030456

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Outline

o Introduction

o Methods

o Results & Discussion

o Conclusion

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Water-Energy Nexus

o 83% of electricity in the USA is produced by thermoelectric power plants.

• Fossil-fuel power plant

• Nuclear power plant

o Water is a critical component of thermoelectrical plants

• Electricity generation

• Cooling

Introduction | Methods | Results & Discussion | Conclusions

U.S. Electricity generation by major energy source(2019)

Source: The U.S. Energy Information Administration (EIA)

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Alternative Water Resource

o Water scarcity

• Related to Climate change

• Caused a drop in electricity production

oMunicipal wastewater (MWW)

• Widespread availability

• Relatively uniform quality

(Van Vliet et al., 2012)Introduction | Methods | Results & Discussion | Conclusions

Projected decreased water resources for thermoelectrical plants

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Challenges with MWW

o Metal Pollutions in Cooling water

• Metals introduced from pipe corrosion

• Metals existing in MWW

Introduction | Methods | Results & Discussion | Conclusions

Metal pollutions introduced from the pipes

(Li, Chien, Hsieh, Dzombak, & Vidic, 2011)

There is a strong imperative to frequentlymonitor heavy metals.

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Challenges with Metal Detection

o Limitations of mature metal detection techniques

• Expensive

• Dedicated staff required

• Grab-sampling required

• Lengthy processing

Introduction | Methods | Results & Discussion | Conclusions

The device that could autonomously conduct metal measurements is desirable.

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Anodic Stripping Voltammetry (ASV)

o Advantages

• Low-cost

• High sensitivity

• Easy to be miniaturized

• Easy to be automated

o Limitation

• Only ionic metals are ready for ASV detections

Introduction | Methods | Results & Discussion | Conclusions

Pb2+ Pb

2.Preconcentration

3.Stripping

Cd2+ Cd

Cd

Cd2+

Pb

Pb2+

1.Cleaning

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Metals in MWW

Introduction | Methods | Results & Discussion | Conclusions

• Complex with natural organic substances

• Bind with inorganic substances

• Absorbed by various components

Important to develop pre-treatment methods which couldrelease metal ions

Pb2+

Cd2+

Large organic or inorganic substanceSmall organicmolecules

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MethodsØ Electrode synthesisØ Pretreatment Method Investigations

Introduction | Methods | Results & Discussion | Conclusions

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Electrode Fabricationo Arsenic detection

• Au-Fe3O4 modified glassy carbon electrode (GCE)• Increase conductivity and arsenic sorption ability

o Pb and Cd detection

• (BiO)2CO3-rGO-Nafion modified GCE• (BiO)2CO3 facilitates the preconcentration of Pb and Cd

• rGO increases the conductivity

• Nafion enhances structural stability

Introduction | Methods | Results & Discussion | Conclusions

Composite material modified GCE

GCE Au-Fe3O4nano particles

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Pretreatment

o Acidification

• Dissolve inorganic substances

• Precipitate humic acid

o Ultraviolet (UV)/H2O2

• Produce hydroxyl radicals (*OH)

Introduction | Methods | Results & Discussion | Conclusions

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Results & DiscussionØ Performances of electrodeØ Automation

Introduction | Methods | Results & Discussion | Conclusions

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ASV Performances in DI watero The response peaks increased linearly with

increasing concentrations, with well-defined

stripping peaks observed.

o The limit of detection is very low (i.e., we

could achieve a high sensitivity)

• Pb: 0.24 ppb << (Discharge limit: 2.5 ppb )

• Cd:0.16 ppb << (Discharge limit: 0.7 ppb )

• As: 0.22 ppb << (Discharge limit: 150 ppb )

Introduction | Methods | Results & Discussion | Conclusions

0-100 ppb As(III)

0-60 ppb Cd(II)

0-60 ppb Pb(II)

Cd

Pb

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ASV Performances in MWWAs detections

o ASV could directly detect ~900 ppb As(III) in

MWW without any pretreatment

• As(III) has a high pKa (9.23), which makes it

very mobile.

Introduction | Methods | Results & Discussion | Conclusions

Left y axial

right y axial

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ASV Performances in MWWAcidification for Pb detections

o Acidification treatment enabled 12.5 ppb Pb

in MWW detected by ASV, while

acidification failed to make Cd detectable.

Introduction | Methods | Results & Discussion | Conclusions

Pb in synthetic wastewater Pb in real wastewater

Cd in synthetic wastewater Cd in real wastewater

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ASV Performances in MWWUV/H2O2 for Cd detection

o UV/H2O2 treatment made ASV successfully

detect most of 3.5 ppb Cd, while it failed to

make 12.5 ppb Pb detectable.

Introduction | Methods | Results & Discussion | Conclusions

Cd in synthetic wastewater Cd in real wastewater

Pb in synthetic wastewater Pb in real wastewater

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Automation

Introduction | Methods | Results & Discussion | Conclusions

Arduino-based hardwater Python-based software

Conclusions

Introduction | Methods | Results & Discussion | Conclusions

Introduction | Methods | Results & Discussion | Conclusions

1.Our nano-material based ASV methods successfully detected all trace As(III)(i.e., ~900 ppb) in wastewater without pretreatment.

2. Acidification (i.e., adjust pH to 1) pre-treatment methods enabled the detection oftrace Pb (~12.5 ppb) by ASV in wastewater.

3.A UV/H2O2 pre-treatment process enabled the detection of trace Cd (~3.5 ppb)by ASV in synthetic wastewater. However, ASV only measured 78% of Cd in realwastewater, and a systematic error was observed. We will solve it via using glassreactors.

4.The whole process could be automated by integration of open-sourcesoftware (Python) and open-source hardware (Arduino).

Acknowledgementso Advisor: Prof. David Jassby

Prof. Ashok Mulchandani

o Funding sources:

o Lab members

This material is based upon work supported by the Department of Energy Award Number DE-FE0030456.

Shengcun Ma ([email protected])David Jassby ([email protected])

Ashok Mulchandani ([email protected])

UCR

Award number : FE0030456

DisclaimerThis report was prepared as an account of work sponsored by anagency of the United States Government. Neither the UnitedStates Government nor any agency thereof, nor any of theiremployees, makes any warranty, express or implied, or assumesany legal liability or responsibility for the accuracy, completeness,or usefulness of any information, apparatus, product, or processdisclosed, or represents that its use would not infringe privatelyowned rights. Reference herein to any specific commercialproduct, process, or service by trade name, trademark,manufacturer, or otherwise does not necessarily constitute or implyits endorsement, recommendation, or favoring by the United StatesGovernment or any agency thereof. The views and opinions ofauthors expressed herein do not necessarily state or reflect thoseof the United States Government or any agency thereof