techniques for detecting nanoparticles in wastewater

Process for Detection of Metal-Containing Nanoparticles in

Wastewater Treatment

Centre for Nano Science & Technology Institute of Science and Technology

Jawaharlal Nehru Technological University Hyderabad

Kukatpally, Hyderabad-85, Telangana, India.E-mail: [email protected]

G. Alekhya, CH. Ashok, K. Venkateswara Rao*, CH. Shilpa Chakra

CONTENTS Objective

Introduction

Prediction of ENM concentrations in environment through PEC modelling .

Need of analytical techniques.

Flow-Field- flow fractionation (FlFFF)

Symmetric FlFFF (SFlFFF)

Asymmetric FlFFF (AF4)

Hydrodynamic chromatography (HDC)

Inductively coupled plasma –mass spectroscopy (ICP-MS)

Hyphenated techniques

AF4-ICPMS

HDC-ICPMS

Conclusion.

OBJECTIVE Studies on adverse effects of ENM on environment and human health

increased concern about their fate, behaviour and release into

environment. Hence researchers developed modelling techniques for

quantitative risk assessment of ENM.

Predicted environmental concentration modelling: overview,

conclusions, limitations are briefly discussed. Thus we conclude

necessity of robust and sensitive analytical techniques for detection and

characterization of ENM in natural matrices.

Techniques for separation of NPs like FFF and HDC, ICP-MS for

quantification are discussed and finally conclusions are made to justify

my title.

Source: Project on emerging nanotechnologies (PEN) report The 2014 PEN report lists 1628 products having nanomaterials this represents an increase of 24% since

2010.

INTRODUCTION

Life-Cycle Perspective :

Overview of PEC Modelling

Substance flow analysisi.e) Flow from products to

STP, WIP, Landfills

Ecotoxicological data like NOEC for assesment

factor of 1000

( RE & HE Scenario )

PEC

PNEC

Estimated worldwide production volume

Allocation of product volume to product categories

Pathways of particle release from products

Flow coefficients within the environmental compartments

Risk Quotient = PEC

PNEC

Reference

Environment Human

Muller & Nowack, 2008

TiO2 > Ag > CNT

Tervonen et al., 2009

cdse > Ag > MWCNT > C60 > Ad

D’Brien & Cummins, 2010

TiO2 > Ag > CeO2

Gottschalk et al., 2009

Ag > ZnO > TiO2 > CNT = C60

Zuin et al., 2011 QD >> C60 > SWCNT > CB

Aschberger et al., 2011

ZnO >> Ag > TiO2 > MWCNT = C60

AG > MWCNT > C60 > TiO2

Gottschalk et al., 2013

Ag>TiO2>ZnO

Relative Risk Rankings for ENM :

(Environmental Pollution 185 (2014) 69-76)

Limitations of Modelling Techniques

Fast development of engineered nanomaterials (ENM) production and

applications.

The availability and quality of published information on fate and

behaviour have increased enormously.

Uncertainty of input parameters.

PEC values are calculated based on case studies and scenarios but not

globally considerable.

Hence there is a need for robust methods to quantify the presence of

ENM in environmental samples known as Analytical techniques.

Field- Flow Fractionation

Prog Polym Sci, 2009

Flow- Field Flow Fractionation Principle :

Source: Analytical and Bioanalytical chemistry (2008), vol 392, pp 1447-1457

SFlFFF and AF4

(a) schematic representation of Symmetric (FlFFF) and (b) Asymmetric (AF4) channel structures. (Prog Polym Sci, 2009)

Hydrodynamic Chromatography (HDC)

(Source: Dissertation of Ammanda Kimberly Brewer)

doi:10.1371/journal.pone.0090559.g001

Retention factor =

Inductively Coupled Plasma-Mass Spectroscopy (ICP-MS)

(www.cco.caltech.edu)

AF4-ICPMS for Separation of Ag NPs in STP Influents

Important parameters

Retention: The retarding of analyte zones through their confinement to flow streamlines with velocities less than the average velocity of the carrier liquid.

Retention time: The ratio of length of the channel to the velocity of the cloud molecules distributed exponentially in a parabolic flow profile.

Recovery :

Where S is the signal (peak area) obtained from AF4-ICP-MS/HDC-ICP-MS and is the signal (peak) obtained with flow injection into ICP-MS system.

HDC-ICPMS for Separation of Ag NPs from STP Sludge

CONCLUSIONAF4-ICP-MS is the reliable technique used to separate mixtures of

NPs with significantly great resolution than HDC-ICP-MS.

large recovery ranges are observed for HDC-ICP-MS compared to AF4-ICP-MS. HDC-ICP-MS provides an additional benefit over AF4-ICP-MS by proving capable of separating dissolved signal from NP sample.

Hence HDC-ICP-MS is advantageous over all hyphenated techniques to characterize nanomaterials analytically in environmental matrices.

Hence this technique may be adopted to remove ENMs in wastewater treatment from activated sludge, and STP influents. However there is a need for research on practical implications to establish this technique for the wastewater treatment.

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