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Reviews in Environmental Science and Bio/Technology

, Volume 16, Issue 3, pp 395–424 | Cite as

Monitoring biological wastewater treatment processes: recent advances in spectroscopy applications

  • Daniela P. Mesquita
  • Cristina Quintelas
  • A. Luís Amaral
  • Eugénio C. Ferreira
review paper

Abstract

Biological processes based on aerobic and anaerobic technologies have been continuously developed to wastewater treatment and are currently routinely employed to reduce the contaminants discharge levels in the environment. However, most methodologies commonly applied for monitoring key parameters are labor intensive, time-consuming and just provide a snapshot of the process. Thus, spectroscopy applications in biological processes are, nowadays, considered a rapid and effective alternative technology for real-time monitoring though still lacking implementation in full-scale plants. In this review, the application of spectroscopic techniques to aerobic and anaerobic systems is addressed focusing on UV–Vis, infrared, and fluorescence spectroscopy. Furthermore, chemometric techniques, valuable tools to extract the relevant data, are also referred. To that effect, a detailed analysis is performed for aerobic and anaerobic systems to summarize the findings that have been obtained since 2000. Future prospects for the application of spectroscopic techniques in biological wastewater treatment processes are further discussed.

Keywords

Wastewater treatment Ultraviolet–visible spectroscopy Infrared spectroscopy Fluorescence spectroscopy 

Abbreviations

3D-EEM

Three-dimensional excitation-emission matrix

AD

Anaerobic digestion

AGS

Aerobic granular sludge

ALE

Alginate-like exopolysaccharides

AMPTS

Automatic methane potential test system II

AnDMBR

Anaerobic dynamic membrane bioreactor

ANN

Artificial neural networks

BA

Bicarbonate alkalinity

BMP

Biochemical methane potential

BOD5

Biochemical oxygen demand

CA

Cluster analysis

CAS

Conventional activated sludge

CNOM

Colored natural organic matter

COD

Chemical oxygen demand

DCOD

Dissolved chemical oxygen demand

DM

Dry matter

DOC

Dissolved organic carbon

DOM

Dissolved organic matter

EBPR

Enhanced biological phosphorus removal

EDAN

N-(1-naphthyl)ethylenediamine

EDTA

Ethylenediamine tetraacetic acid

EEM

Excitation-emission matrix

EPS

Extracellular polymeric substances

Ex/Em

Excitation/emission

FIA

Flow injection analysis

FIR

Far-infrared

FLC

Fluorescence

FRI

Fluorescence regional integration

FT

Fourier-transform

FTIR

Fourier-transform infrared

FT-NIR

Fourier transform near-infrared

GC

Gas chromatography

GC-MS

Gas chromatography-mass spectrometry

GDA

Generalized discriminant analysis

H2S

Hydrogen sulfide

HS

Bisulfide ion

IR

Infrared

KPLS

Kernel partial least squares

LC-MS

Liquid chromatography-mass spectrometry

LDA

Linear discriminant analysis

LWR

Locally weighted regression

MBR

Membrane bioreactors

MIR

Mid-infrared

ML-PLS

Multi-layer partial least squares

MLVSS

Mixed liquor volatile suspended solids

MMC

Mixed microbial cultures

MWPLS

Moving window partial least squares

NH4–N

Ammonia nitrogen

NIR

Near-infrared

NMR

Nuclear magnetic resonance

NNPCR

Nonlinear principal components regression

OLR

Organic loading rate

OM

Organic matter

PARAFAC

Parallel factor analysis

PCA

Principal component analysis

PHA

Polyhydroxyacanoates

PHB

Polyhydroxybutyrates

PLS

Partial least squares

RF

Random forest

RVM

Relevance vector machines

SBR

Sequencing batch reactor

SG

Savitzky–Golay

SVM

Support vector machines

SW-NIR

Short-wave near-infrared

SWR

Step-wise regression

TC

Total carbon

TIC

Total inorganic carbon

TKN

Total Kjeldahl nitrogen

TOC

Total organic carbon

TS

Total solids

TSS

Total suspended solids

UV–Vis

Ultraviolet-visible

VNIR

Visible-near-infrared

VSS

Volatile suspended solids

WAS

Waste activated sludge

WWT

Wastewater treatment

WWTPs

Wastewater treatment plants

Notes

Acknowledgements

The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, COMPETE 2020 (POCI-01-0145-FEDER-006684) and the project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte. The authors also acknowledge the financial support to Daniela P. Mesquita and Cristina Quintelas through the postdoctoral Grants (SFRH/BPD/82558/2011 and SFRH/BPD/101338/2014) provided by FCT—Portugal.

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© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Centre of Biological Engineering (CEB)Universidade do MinhoBragaPortugal
  2. 2.Instituto Politécnico de Coimbra, ISEC, DEQBCoimbraPortugal

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