Diapositiva 1

1
Physicochemical and microbiological parameters to
monitor wastewater treatment plant
A. MUELA1, M. ORRUÑO1, M.L. ALONSO2, M. PAZOS4,
I. ARANA1, R.M. ALONSO2, R. JIMENEZ2, M.I.
MAGUREGUI3 I. BARCINA1
1 Dpto. Inmunología, Microbiología y
Parasitología. Fac. Ciencia y Tecnología, 2
Dpto. Química Analítica. Fac. Ciencia y
Tecnología, 3 Dpto. Pintura. Fac. Bellas Artes,
(UPV/EHU, E-48080 Bilbao, Spain) 4 UTE
Crispijana (Crispijana s/n, E-01195
Vitoria-Gasteiz, Spain)
isabel.barcina_at_ehu.es
2
INTRODUCTION
Effluent quality of wastewater treatment plants
(WWTP)
Directive 91/271/EEC (1)
YES
NO analyzed
Physicochemical parameters Automation Less
time-consuming
Microbiological parameters (growth) NO
Automation Time-consuming
FLOW CYTOMETRY? (2)
Automation Immediate results Information about
viable but nonculturable cells (3)
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INTRODUCTION

• Wastewater treatment plants with activated sludge
  purification method are complex systems where
  different physicochemical and microbiological
  phenomena take place simultaneously. However,
  Spanish legislation establishes the effluent
  quality based exclusively on physicochemical
  parameters, skipping the microbiological
  characterization.

• A correct evaluation of risk implies analyzing
  not only bacterial density, but also the
  permanence of bacteria of sanitary concern after
  wastewater treatment.

4
AIM OF THE WORK
In this work, microbiological and physicochemical
parameters were comparatively analyzed in a
wastewater treatment plant. Moreover, the
suitability of flow cytometry for monitoring the
bacterial content was checked.
5
MATERIAL AND METHODS
Sampling

• Water samples were collected during the 2006 warm
  season (June-October) and the 2007 cold season
  (January February) in Crispijana
  (Vitoria-Spain) wastewater treatment plant
  (WWTP).
• This plant is stated close to an urban area
  (229.080 habitants) and collects both industrial
  and municipal wastewaters.

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MATERIAL AND METHODS
Sampling
Samples were taken just before the entry into
aeration tanks (raw water) and after secondary
treatment (effluent).
Samples were collected daily with an autosampler
(300ml h-1)
Analysis before 24 h.
Aliquots of 2.5 l were stored at 4ºC. (For metal
analysis, samples were acidified to pH 2 with
HNO3 )
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Physicochemical characterization

• Physicochemical parameters were measured using
  the methodologies recommended by the current
  Spanish legislation (4, 5).
• Final effluent characteristics were established
  according to Directive 91/271/CEE (1).

• pH
• Conductivity
• Oil and fatties
• Sedimentable solids (SedS) and non-sedimentable
  solids (No SedS)
• Suspended solids (SS)
• Chemical and biological oxygen demand (COD)(BOD)
• Total Kjehldahl nitrogen (TKN)
• Ammonium (NH4)
• Heavy metals (Cd, Cu, Pb, Ni, Zn, Cr ) analyzed
  by ICP-OES

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Microbiological parameters

• Total bacterial counts (TBC) by microscopy (6).
• Total bacterial cytometric counts (TCC) were
  enumerated with a FACSCalibur flow cytometer
  (FCM) (Becton Dickinson, San Jose, CA, USA).
• Viable bacteria were estimated as bacteria with
  intact cytoplasmic membranes (MEMB) with the aid
  of the Live/Dead BacLightTM kit (Molecular
  Probes) (7).
• Heterotrophic bacterial counts (HBC) in
  Yeast-Extract Agar plates were counted after 72h
  at 20ºC and 36ºC (ISO 62221999).
• Escherichia coli (EC) and coliform bacteria (ISO
  9308-3), as well as intestinal enterococci (EF)
  (ISO 7899-11998), were enumerated using a
  miniaturized method.
• Percentages of viable but nonculturable cells
  (VBNC) and non-culturable (NC) were calculated as
  (MEMB - HBC)/TBC and (TBC HBC)/TBC,
  respectively.

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Physicochemical characterization of raw water and
effluent
Fig. 1. Box and Whisker plot. Physicochemical
parameters in raw water (RW) and effluent (E).
Threshold values are shown in dotted line for SS
(20 mg l-1), BOD (14 mg l-1), COD (70 mg l-1),
NH4 (8.8 mg l-1) and NO3- (22 mg l-1).
Good WWTP working
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Physicochemical characterization of raw water and
effluent
Table 1. Means of metal concentrations in raw
water and effluent samples
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Relation between physicochemical and
microbiological parameters
While Atlas Bartha (8) have stated BOD5 as the
only obligate parameter of wastewater quality
after treatment which could be related with
microbiological characteristics, Howard et al.
(9) have indicated the null correlation between
BOD5 and density of faecal indicator bacteria.
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Table 2. Correlation analysis between
physicochemical and microbiological parameters
No correlation between physicochemical and
microbiological parameters, with the exceptions
of SS and TNK concentration which were connected
with TCC.
13
Fig 2. Principal component analysis plot. 85 of
the total variance. PC1/PC2 for physicochemical
and microbiological parameters.
Raw water and effluent can be differentiated (due
to WWTP work 10, 11), as well as, the two
season studied warm (dry) and cold (wet). Raw
water samples belonging to cold season, are
closer to samples from effluent, due to the
dilution effect of rain during cold season (10).
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RESULTS and DISCUSSION
Table 3. Means of the values of microbiological
parameters from raw water and effluent samples
collected during the cold and warm season.
For each season, cold or warm

• No significative differences between TBC and TCC
  counts were detected.
• Total (TBC, TCC) and viable (MEMB) counts were
  higher than culturable bacteria counts (EC, EF or
  HBC) indicating the prevalence of non-culturable
  bacteria (95-99). Moreover, a bacterial
  population fraction was in the VBNC state
  (12-40).

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Microbiological parameters
FCM provides a rapid and suitable method to
enumerate bacterial populations in wastewater
(12, 13) and to estimate the viable fraction (14,
15). A great variation in viable counts and so
in VBNC estimations has been reported (14-16).
16
During this study, some industrial pollutants in
the municipal drainage net were detected by the
Environment Control Service from Vitoria-Gasteiz.
This unusual situation took place from 26/06/06
to 05/07/06.
10
A
8
log cells ml-1
6
4
2
0
TBC
EC
HBC
Fig 3. Comparison in the number of cells in a
normal (light bars) and unusual (dark bars)
situation during the warm season, in both raw
water (A) and effluent (B).

• All bacterial subpopulations studied reflected
  this unusual fact in the WWTP.
• In both, raw water and effluent, there were
  decreases in bacterial counts, so activated
  sludge process should have been affected.

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Viable cells
Viable cells
Fig 4. Example of flow cytometric dot plot using
Live/Dead BacLightTM kit (A) normal situation,
(B) unusual situation and (C) percentages of
viable cells in samples from normal (light bars)
and unusual situation (dark bars).

• Sharp decrease in viability was related to spill
  of industrial pollutants.
• FCM was a good tool for detecting unusual
  situations.

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Table 4. Mean values of samples from normal and
unusual situation during warm season
No significative differences between analyzed
situations were obtained for the physicochemical
parameters tested. Exception, NH4 content in
effluent samples during the spill of industrial
pollutants.
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• Physicochemical as well as microbiological
  parameters confirm the good WWTP working,
  however, no significative correlation between
  both groups of parameters were found.
• When changes occur in WWTP (flow rate or quality
  of influent), microbiological parameters were
  more sensitive than physicochemical ones.
• Standardization by means of culturability
  underestimates the bacterial density.
• FCM is a useful method to monitor WWTP.

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• Directive 91/271/EEC
• Shapiro H (2000) J Microbiol Methods 42 3-16
• Xu HS, Roberts N, Singleton FL, Attwell RW,
  Grimes DJ Colwell RR (1982) Microb Ecol
  8313-323
• Real Decreto 2.116/98 from 1998, October 2nd
• Standard Methods for the examination of Waste and
  Wastewater, 20th ed. (2006) APHA/AWWA/ECF.
  Washington DC, USA
• Hobbie JE, Daley RJ Jasper S (1977) Appl
  Environ Microbiol 33 1225-1228
• Joux F, Lebaron P Troussellier M (1997) Appl
  Environ Microbiol 632686-2694
• Atlas RM Bartha R (1998) Microbial Ecology.
  Fundamentals and Applications. 4th ed.
  Benjamin/Cummings Science Publishing, Menlo Park,
  California
• Howard I, Espigares E, Lardelli P, Martín JL
  Espigares M (2004) Environ Toxicol 18 241-249.
• Kay P, Crowther J, Stapleton CM, Wyer MD,
  Fewtrell L, Edwards A, Francis CA, McDonald AT,
  Watkins J Wilkinson J (2007) Water Res
  doi10.1016/j.watres.2007.07.036
• Zhang K Farahbakhsh K (2007) Water Res
  412816-2824
• Ziglio G, Andreotola G, Barbesti S, Boschetti G,
  Bruni L, Foladoi P Villa R (2002) Water Res 36
  460-468
• Forster S, Lappin-Scott HM, Snape JR Porter J
  (2003) J. Microbiol Methods 55859-864
• Mezzanotte V, Prato N, Sgorlati S Citterio S
  (2004) Water Environ Res 76 463-467
• Li CS, Chia WC Chen PS (2007) J Environ Sci
  Health Part A 42 195-203
• Forster S, Snape JR, Lappin-Scott HM Porter J
  (2002) Appl Environ Microbiol 68 4772-4779

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• This study was funded by the research projects
• CTM2006-09532/TECNO from the Science and
  Technology Ministry of Spain
• SA-2005/00190 from the Basque Government
• UPV05/121 from the Basque Country University.
• Authors thank to AQUALIA Gestión Integral del
  Agua-Salagunketa S.A. UTE (UTE Crispijana) for
  their collaboration.