Results of ‘PASt21’ – the Portuguese initiative for performance assessment of water and...

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372 © IWA Publishing 2012 Water Science & Technology: Water Supply | 12.3 | 2012

Results of ‘PASt21’ – the Portuguese initiative

for performance assessment of water and wastewater

treatment plants

C. Silva, P. Ramalho, S. Quadros, H. Alegre and M. J. Rosa

ABSTRACT

Performance assessment of water supply and wastewater services is today a major issue. Over the

past six years, the National Civil Engineering Laboratory (Portugal) has been developing performance

assessment systems for drinking water treatment plants (WTPs) and wastewater treatment plants

(WWTPs). In 2009, a national field-test was launched in Portugal, ‘PASt21’, involving 27 plants (10

WTPs and 17 WWTPs). This paper presents an overview of the second generation of the performance

indicator (PI) systems for the overall performance assessment of WTPs and WWTPs, the extent to

which the systems were applied in the 5-year study period (2006–2010), and the aggregated results

(average, median, percentiles 25 and 75, maximum and minimum) of representative PIs in each

assessment group. It was concluded that all indicators are relevant, and the results show the ability

of the proposed PI systems to assess the overall performance of a given treatment plant. The

aggregated results are very important for the continuous improvement of the plant performance

through benchmarking and periodic reassessment of targets.

doi: 10.2166/ws.2012.004

C. Silva (corresponding author)P. RamalhoH. AlegreM. J. RosaUrban Water Division,Hydraulics and Environment Department,LNEC – National Civil Engineering Laboratory,Av. Brasil 101,1700-066 Lisboa,PortugalE-mail: [email protected]

S. QuadrosAzores University,Campus de Angra do Heroísmo,9701-851 Angra do Heroísmo,Portugal

Key words | performance assessment, performance indicators, wastewater treatment plants,

water treatment plants

INTRODUCTION

Performance assessment of water supply and wastewater

services is today a major issue. However, most performance

assessment systems (PASs) do not specifically apply to treat-

ment plants, which are core elements of these services

(Alegre et al. , ; Stahre & Adamsson ; Matos

et al. ; Ofwat ; World Bank ; Stahre et al.

). To our knowledge, exceptions to this situation are

the German initiative ‘Benchmarking water industry’

(DWA ) and the ‘Portuguese initiative for performance

assessment of water and wastewater treatment plants –

PASt21’ (http://past21.lnec.pt/).

Over the past 6 years, LNEC – the National Civil Engin-

eering Laboratory (Portugal) has been developing PASs for

water treatment plants (WTPs) and wastewater treatment

plants (WWTPs) (Vieira et al. , , ; Quadros

et al. ).

These systems comprise two main components, the

Overall Performance Assessment and the Operational Per-

formance Assessment. The former, the subject of this

paper, is based on performance indicators (PIs), which

use historical data and the information produced is aggre-

gated at plant level. The Operational Performance

Assessment is based on performance indices and addresses

the daily performance of each unit operation or process of

the plant.

In 2009, a national field-test was launched, ‘PASt21’,

coordinated by LNEC and involving 27 plants operated by

12 water utilities, publicly owned (10 companies of the

Águas de Portugal holding), private (AGS, S.A.) or munici-

pal (SMAS Almada). The PASt21 project also involves the

Portuguese Water and Waste Services Regulation Authority

and has the support of the Portuguese Association for

mailto:[email protected]

http://past21.lnec.pt/

http://past21.lnec.pt/

373 C. Silva et al. | Results of ‘PASt21’ Water Science & Technology: Water Supply | 12.3 | 2012

Sanitary and Environmental Engineering and the Portu-

guese Water Resources Association.

This paper presents: (i) an overview of the second

generation of the PI systems for the overall performance

assessment of WTPs and WWTPs, (ii) the characterisation

of the 27 case-studies, (iii) the extent to which the

systems were applied in the 5-year study period (2006–

2010), and (iv) the formulation and aggregated results

(average, median, percentiles 25 and 75, maximum and

minimum) of representative indicators in each assessment

group.

THE PI SYSTEM FOR OVERALL PERFORMANCEASSESSMENT OF WTPS AND WWTPS

The developed PASs assumed two general objectives for any

undertaking with regard to a WTP or WWTP performance:

(1) its effectiveness and reliability, i.e. the compliance over

time with the quality requirements of the treated water

and (2) its efficiency (in terms of resources utilisation) and

sustainability (economic and environmental).

These objectives determined the following assessment

groups: Treated water/wastewater quality; Removal effi-

ciency and reliability; Use of natural resources and raw

materials; By-product management; Safety; Personnel;

Economic and financial resources; Planning and design

(the latter only for WWTP) (Vieira et al. , , ;

Quadros et al. ).

Analogous portfolios of PIs for WTP and WWTP were

formulated in these assessment groups according to the

IWA approach (Alegre et al. , ; Matos et al. )

and to the principles established in ISO 24510:2007,

24511:2007, 24512:2007.

The developed PIs are defined as ratios between variables

(of the same or of different nature), and may be therefore

dimensionless (e.g. %, –) or intensive (e.g. kWh/m3). In

the latter case, to allow for comparisons, the denominator

represents one dimension of the system (Alegre et al. ),

e.g. the volume of treated water. The PIs are calculated for

a reference assessment period, preferably a year. PIs

expressed in terms of time are formulated to accommodate

other reference assessment periods. In order to ensure unit

coherence and allow for PI comparison, for these PIs, the

values calculated for other reference assessment periods are

converted into annual values, multiplying by ‘365 (day/

year)/Assessment period (day)’.

The work undertaken in the scope of PASt21 resulted in

the second generation of PI systems for WTP and urban

WWTP. The second generation systems include 94 PIs for

WTPs and 121 PIs for WWTPs, involving 141 and 204 vari-

ables, respectively, i.e. overall ratios of 1.5 and 1.7 variables/

PI. The PI code includes six or eight fields (the last two are

optional) identifying the system (t for WTP and wt for

WWTP), the assessment group and the PI number – e.g.

wtWQ01 is the first indicator (01) of the Treated Wastewater

Quality (WQ) assessment group. Whenever necessary, an

optional numerical field may be used to identify an alterna-

tive processing rule, e.g. wtER35.1 for Pump inspection,

expressed in No./(pump.year), and wtER35.2 for Inspected

pumps, %/year. An optional alphabetical character may be

used for PI speciation. For instance, the consumption of

reagents is assessed for each reagent (or type of reagent)

used in the plant, e.g. wtRU05.0a – Consumption of alu-

minium coagulants, expressed in g Al/m3 of treated

wastewater.

The detailed characterisation of each PI (code

and designation, assessment group, objective, processing

rule, units, data required, results analysis and observations –

for clarification of variables and other relevant aspects to

the PI calculation) is presented in Rosa et al. (a, b).

The proposed PASs deal with a high volume of data, and

an automatic tool for data processing and results visualisa-

tion was therefore developed. PAStool was implemented

in Microsoft Excel® with VBA programming and also

allows for the statistical analysis of results. Whenever stat-

istically feasible, PAStool automatically aggregates in a box

plot (Figure 1) the values obtained for each PI and for

each year, as well as for the overall period under study (to

a maximum of 5 years).

The box plot includes the average, median, percentiles

25 and 75, maximum, minimum and extreme outliers

(values below or above three times the P75-P25 difference).

The percentage of calculation, i.e. the percentage of case-

studies entering the calculation of a given PI, is also

shown. Whenever the latter varies from year to year,

interpretation of PI variations and box plots for the overall

5-year period should be considered with reservation.

Figure 1 | Box plot automatically produced by PAStool.


The number of PIs proposed in each assessment group

and the degree of application of the PI systems in PASt21

case-studies (characterised in ‘The PASt21 Case-studies’,

below) are then presented under the heading ‘Degree of

application of the PI systems during the field test’. The for-

mulation and the aggregated results of representative PIs

are then presented and discussed by assessment group in

sections below headed ‘Treated (waste)water quality’

(WQ), ‘Removal efficiency and reliability’ (ER), ‘Use of natu-

ral resources and raw materials’ (RU), ‘By-product

management’ (BP), ‘Safety’ (Sa), ‘Personnel’ (Pe), ‘Economic

and financial resources’ (Fi) and ‘Planning and design’ (PD).

The PIs shown were selected for their interest, variation

throughout the 5-year period under study and/or higher per-

centage of calculation.

THE PASt21 CASE-STUDIES

The 27 PASt21 case-studies (10 WTPs and 17 WWTPs) are

spread throughout Portugal (Figure 2) and cover a wide

range of treatment capacities and conventional sequences

(Figures 3 and 4), representative of the national situation

and as commonly found worldwide.

The 10 WTPs range from 3,000 to 400,000 m3/d (yield-

ing a total treatment capacity of 1,160,000 m3/d), have

different raw water sources – surface water only (dam or

river) or surface and groundwater – and different unit oper-

ations or processes for conventional water treatment and

solids processing (Figure 3), typically found worldwide.

The 17 WWTPs cover different capacities (360–

54,500 m3/d) and final disposal of the treated water

(discharge in sensitive, non-sensitive or bathing areas and/

or reuse), involving different unit operations and chemical

and biological processes for wastewater treatment and

solids and biosolids (sludge) processing (Figure 4). Seven

WWTPs are designed for carbon removal, five for biological

carbon and nitrogen removal, and five for carbon, nitrogen

and phosphorus removal by conventional processes –

suspended growth (activated sludge variants) and attached

growth (trickling filters and other biofilters). Twelve

WWTPs include UV disinfection, two have microscreening

and six (mono or dual) filtration prior to water discharge

and/or water reuse (three for 100% of treated flowrate and

three for the water to be reused).

PI RESULTS OF PASt21

Degree of application of the PI systems during the field

test

Figure 5 presents the number of indicators proposed in each

assessment group and the percentage of calculated PIs

during the 5-year (2006–2010) study period – the average

values of the consortium and the maximum percentages

obtained in one (W)WTP.

PAStool was designed for a 5-year period of analysis and

therefore data from 2006 to 2010 were included, even

though the data input is not yet complete for 2010.

All PIs were considered relevant by the consortium

depending on the assessment objectives, although in some

treatment plants the lack of reliable data may limit (for the

time being) the use of a few PIs, e.g. wtBP19 – Greenhouse

gases emission.

The percentage of calculated PIs shown in Figure 5

demonstrates the utilities’ major concern with plant effec-

tiveness and efficiency in terms of personnel and use of

water, energy and raw materials.

The highest percentage of calculation was found for the

assessment groups Treated (waste)water quality and Person-

nel, which were closely followed by the Use of natural

resources and raw materials in the WTPs (Figure 5). In the

WTPs, 39–89% of the PIs of the Treated water quality

group were calculated, on average. In the WWTPs, 23–54%

of the Treated wastewater quality PIs were calculated, the

Figure 2 | Location of PASt21 case-studies in Portugal.


value of 54% corresponding to the total number of the PIs

relating to plant compliance with discharge permits. The

average percentage of calculation for the Personnel indi-

cators ranged from 30 to 90% in the WTPs and from 31 to

85% in the WWTPs, during 2006–2010, whereas the calcu-

lated PIs of Use of natural resources and raw materials in

the WTPs varied from 41 to 80%.

The maximum percentage of PI calculation (also shown

in Figure 5) indicates that for at least one WTP, every PI pro-

posed in the WQ, RU and Pe assessment groups were

calculated, and the same happened for at least one WWTP

in the WQ, Sa, Pe, Fi and PD groups.

The accounting systems of many utilities in the con-

sortium did not allow a reliable and accurate allocation of

the Economic and financial resources (Fi) to a single

plant, and this constraint resulted in low average percen-

tages of PI calculation in this assessment group, in

addition to low data reliability and accuracy. The following

results of Fi indicators should therefore be analysed with

reservation.

The formulation and the results of the selected PIs for

each assessment group are presented in Tables 1–7 (from sec-

tions Treated (waste)water quality, Removal efficiency and

reliability, Use of natural resources and raw materials, By-

product management, Safety, Personnel, Economic and

financial resources, and Planning and design). The results

are aggregated in box plots, which include the average,

median, percentiles 25 and 75,maximum,minimum, extreme

outliers and the percentage of calculation, i.e. the percentage

of case-studies entering this aggregation (Figure 1). A brief

interpretation of the results is also enclosed in the tables.

Treated (waste)water quality

The assessment group Treated water quality evaluates WTP

performance in terms of compliance with water quality cri-

teria established by the utility for the finished water

leaving the plant and at different consumption points. It

also considers the parameters analysed compared to those

established by national legislation for drinking water at the

Figure 3 | Treatment capacities, raw water sources and unit operations or processes of the 10 WTPs studied.

Figure 4 | Treatment capacities, final disposals and unit operations or processes of the 17 WWTPs studied.


Figure 5 | PI systems for WTP and WWTP – overview and degree of application during the 5-year study period (♦ average and ▪ maximum values of ‘Calculated PIs/Proposed PIs × 100’).


consumption point. The consortium agreed on a common

frame of water quality criteria, i.e. water quality parameters

and their limit-values.

The compliance of test results has been evaluated for all

parameters defined by the water supplier and for a set of

key-parameters (tWQ02, Table 1), inspired by Ofwat’s

Operational Performance Index, which reflects how well

treatment works and distribution systems are operated

and maintained (Ofwat ). The proposed set of key-

parameters includes metals (in raw water and added during

treatment, i.e. Fe, Mn, Al), turbidity (water clarity, NTU), oxi-

dation by-products of chlorine (THM) and ozone (BrO3�),

and coliform bacteria. The values of tWQ02 reveal high

levels of compliance for these seven key-parameters (results

for 2010 are less significant since they correspond to only

40% of data input).

The ability of the WTP to produce water that has an ade-

quate quality at the delivery/consumption point(s) is also

assessed by the chlorine residual (minimum and maximum

residual, tWQ06 in Table 1), THM concentration and micro-

biological quality. PI tWQ06 shows that for some WTPs

the residual chlorine exceeded the maximum value

recommended by the Portuguese legislation (1 mg/L).

Although no problems of excessive THM formation

occurred, this situation recommends further analysis of dis-

infection processes.

For WWTP, Treated wastewater quality compliance

with discharge permit regulation is evaluated in three

aspects: quality tests carried out, parameters analysed

and compliance with wastewater quality established in dis-

charge permits. Table 1 shows the results for the first and

third aspects (PI wtWQ1.2 and wtWQ3.2, Table 1). These

Table 1 | PI results for treated (waste)water quality

tWQ02 – Compliance with key-parameters of water quality [%] (Fe, Mn, Al, NTU, THM,BrO3, coliform bacteria)¼ (Tests of key-parameters complying with criteria defined bywater supplier (no.)/Tests carried out to key-parameters (no.)) × 100

All values were above 88%. The average ranged from 97.2% (in 2010) to 99.9% (in 2008)and the median varied from 98.8% (2010) to 100% (2008). P25-P75 for 2006–2010 was99.7–100%. Some values were considered extreme outliers.

tWQ06 – Maximum chlorine residual at delivery/consumption point(s) [%]¼ (Averageof the 10% highest values of free chlorine recorded in the distribution network (mg/L)/Maximum allowable value of free chlorine (mg/L)) × 100

The lowest median was obtained in 2008 (90.8%). Although there were some values below100%, in 2006–2010 the average was 102.6%, the median 98.9% and P25-P75 88.1–110.8%.

wtWQ01.2 – Quality tests carried out [–] ¼Tests carried out (discharge permit regulation) (no.)/Tests required (discharge permitregulation) (no.)

On average, in 2006–2010, the tests performed were 3 to 4 times the tests required, with adecreasing tendency. This tendency represents an improvement in (the economic)performance since the minimum was 1 for every year, which corresponds to compliancewith the number of tests required.

wtWQ03.2a – Compliance with wastewater quality established in dischargepermits [%] ¼Pm

i¼1Ji

m × 100 m¼ total of required parameters analysedJi¼ compliance with parameter ‘i’ (0¼ no compliance; 1¼ compliance)

Improved performance during 2006–2010: the average increased from 56 to 81%, themedian from 73 to 92%; P25 also increased, resulting in a tighter P25-P75 in 2010. Dueto the increasing performance, the box plot for the overall period should not beconsidered.


results, particularly P25 and the median, showed a signifi-

cant improvement in performance during 2006–2010.

Nevertheless, concerning the quality, in 2010 there are

still parameters for which the treated wastewaters studied

do not comply with the respective discharge permits. An

analogous set of PIs was proposed for assessing the com-

pliance of treated wastewater (used internally or externally

to the WWTP) with water reuse requirements (Quadros

et al. ). While every plant calculated for every year

the three PIs relative to plant compliance with discharge

permits, the majority (13 WWTPs) did not select the

PIs relating to water reuse since the use of treated waste-

water is planned although not in practice for the time

being.

Removal efficiency and reliability

The Removal efficiency and reliability assessment group

evaluates the plant performance in terms of plant robust-

ness, flexibility, removal efficiency and reliability.

Table 2 | PI results for removal efficiency and reliability

tER01 – Water source utilisation [%/year] ¼(Raw water (m3) × 365(day/year)/Assessmentperiod (day)/Annual abstraction capacity of the source (m3)) × 100

Wide range of results. Some case-studies presented values close to 100%. In 2006–2010 theaverage was 38%, the median 27% and P25-P75 was 13–66%.

tER04 – Adequacy of plant capacity [%] ¼

1�Pn

d¼1 Qtd × JdþPn

d¼1 Qtd ×KdPnd¼1 Qtd

� �× 100

Qtd¼ Plant capacity (daily average flowrate)at day ‘d’ (m3/day)Qrd¼ Daily average flowrate recorded at day‘d’ (m3/day)

n¼ assessment period (day)Jd¼ 1, if Qrd >0.95 Qtd in day ‘d’¼ 0, if Qrd� 0.95 Qtd in day ‘d’

Kd¼ 1, if Qrd >0.7/fs Qtd in day ‘d’¼ 0, if Qrd �0.7/fs Qtd in day ‘d’

fs¼ correction factor for seasonal variationof the flowrate through the assessmentperiod

Increase during the studied period, with a very wide range of results. On average, the values were below 70%, indicating a poorperformance. Case-studies with poor performance correspond to over sized plants.

wtER03 – BOD5 mass removal efficiency[%]¼ ((Inflow BOD5 mass – Outflow BOD5

mass (effluentþ by-pass))/Inflow BOD5 mass(kg)) × 100

P25 was above 90%. In 2009, P25-P75 was94.1–97.8% and the median 96.3%.

tER19 – Possibility of dosing alternative chemicals [%] ¼(Chemicals not used on a regular basis (no.)/Chemicals used regularly during WTPoperation (no.)) × 100

Similar values throughout the analysed period. In 2008 and 2009 the median was 25%.In 2008–2009, P25-P75 was 10–37%.

wtER35.1 – Pump inspection [no./(pump.year)] ¼(Pump inspections (no.) × 365 (day/year)/Assessment period (day))/Pumps (no.)

Significant increase in PI during the analysed period, ranging on average from 2 inspections/pump in 2007 to 6 inspections/pump in 2009. In 2009, the median was 4 inspections/pump. These results (higher than one) do not mean that all pumps were inspected duringthe period, aspect assessed by PI wtER35.2.

(continued)


Table 2 | continued

wtER35.2 – Inspected pumps [%/year]¼(Inspected pumps (no./year)/Pumps (no.)) ×100

This processing rule option also shows an increase in the practice of inspection, althoughthere were values lower than 100%/year. Comparing the two PI options (wtER35.1 andwtER35.2), it is concluded that the inspection effort was directed to certain pumps.

wtER54 – Interruptions of pump operation(>30 min) [no./(pump.year)] ¼(Interruptions of pump operation (>30 min)(no.) × 365 (day/year)/Assessment period(day))/Pumps (no.)

PI decreased on average from 0.98 to 0.24 no./(pump.year) in 2006–2009. No data availablefor 2010.

tER34 – Chemical dispenser calibration [no./(dispenser.year)] ¼(Chemical dispenser calibrations (no.) × 365 (day/year)/Assessment period (day))/Chemicaldispensers (no.)

Wide range of results, from 0 to 1.1 calibrations per dispenser per year. In 2006–2010, P25-P75 was 0.27–1 no./(dispenser.year). Extreme outliers (24 no./(dispenser.year) are notshown.


Water source utilisationwas assessed by tER01 (Table 2)

and allowed to identify, in some WTPs, situations of full

resources utilisation. In terms of adequacy of treatment

capacity, tER04 (Table 2) showed that most of the WTPs

are over sized.

For WWTP, mass removal/stabilisation efficiency is

evaluated by a set of five indicators, concerning biological

oxygen demand (BOD) stabilisation, and BOD, chemical

oxygen demand, total suspended solids and nutrients

(N and/or P) removal. The results of wtER03 (Table 2)

show that, every year, P25-P75 lies within the typical litera-

ture range for conventional secondary treatment, i.e. 86–

91% (Qasim ) and 85–97% (Metcalf & Eddy ),

and over the range of the Portuguese legislation regarding

treated wastewater discharge (70–90%). This indicator

shows a direct relationship with wtWQ3.2a, with removal

efficiencies below 90% being associated with lower values

of compliance, due to highly concentrated raw wastewater

(Table 2).

As the reliability of a treatment plant is higher if the

Possibility of dosing alternative chemicals is planned, this

performance aspect was evaluated through tER19 (Table 2).

This PI showed that, on average, the studied WTPs may

use a number of alternative chemicals which is equal to

about one quarter of the number of chemicals used in regular

operation.

Equipment inspection may be assessed by the total

number of inspections and/or by the percentage of

inspected equipment. These two options were tested for

pumps (wtER35.1 and wtER35.2, Table 2) and aerators.

For other equipment (valves, signal transmission equipment,

flow meters, water/sludge level meters, pressure meters,

online water/sludge quality meters, bed filters, dewatering

equipments and other key-equipment) only the second

option (percentage of inspected equipment) was proposed.

In 2006–2009 (data input is very low for 2010) these PIs

show an increase in the practice of inspection, a procedure

that reduces the risk of equipment failure. These failures are


evaluated by PIs of interruption of the operation (>30 min)

of equipment, such as pumps (wtER54, Table 2), valves,

aerators, dewatering equipment and other key-equipment.

As expected, there is an inverse correlation between

wtER35 and wtER54 (Table 2).

Equipment calibration must be verified periodically to

validate the results of the measurements. PIs tER34

to tER38 evaluate the periodic calibration (or verification

of calibration) procedures for chemical dispensers,

flow meters, water/sludge level meters, pressure meters

Table 3 | PI results for use of natural resources and raw materials

tRU01 – Efficiency of raw water use at the WTP [%] ¼(Treated water (m3)/Raw water (m3)) × 100

Most of the results were above 90%. In 2006–2010, themedian was high (98.3%) and P25-P75 was 95.7–99.8%.Values above 100% were due to flow measuring errors.

wtRU01 – Fresh water consumption [m3/(103 m3)] ¼(Fresh water (m3)/Treated wastewater (m3)) × 103

P25-P75 decreased from 1.3 to 6.9 m3/(103 m3) in 2007to 1.1–2.1 m3/(103 m3) in 2009. There were extremeoutliers (some not shown), particularly in 2006(17.8 m3/(103 m3)), 2008 (31 m3/(103 m3)) and 2009(5.8, 7.5 and 68.9 m3/(103 m3)).

tRU03, wtRU03 – Energy consumption [kWh/m3]¼Energy consumption (kWh)/Treated (waste)water (m3)

In 2006–2010, P25-P75 was 0.05–0.96 kWh/m3 for theWTPs and 0.34–1.29 kWh/m3 for the WWTPs.

tRU05, wtRU04 – Consumption of acids and bases[eq/m3] ¼ Acids and bases consumed (eq)/Treated(waste)water (m3)

In 2006–2010, the average was 2.2 eq/m3and the median1.17 eq/m3 for the studied WTPs; for the WWTPs,P25-P75 was 0.01–0.07 eq/m3.

and online water/sludge quality meters. The results show

that some equipment was not calibrated in 2006–2010, as

illustrated by tER34, for which the average is less than

one calibration per dispenser (Table 2).

Use of natural resources and raw materials

This assessment group evaluates the plant performance in

terms of efficiency of use of the most important inputs:

water, energy, chemicals and filter media.


The Efficiency of raw water use, assessed by tRU01

(Table 3), shows high performance of the studied WTPs.

The Energy consumption in the studied WWTPs

(wtRU03) increased slightly during the studied period

(2006–2010) and the median was four times higher than

the median energy consumption in the WTPs (tRU03).

The median Consumption of acids and bases in the

studied WTPs (tRU05, Table 3) was 1.17 eq/m3, 10 times

higher than in the WWTPs (wtRU04).

By-product management

The By-product management assessment group evaluates

the plant performance in terms of production and disposal/

beneficial use of by-products, including: sludge, filter

media, screenings, grit, skimmings and biogas, and green-

house gases emission.

Sludge production in the studied WWTPs (wtBP01.1,

Table 4) increased from 2006 to 2010. The increase in

Table 4 | PI results for by-product management

tBP01.1, wtBP01.1 – Sludge production [g/m3; kg/m3] ¼Sludge produced (g or kg)/Treated (waste)water (m3)

Production slightly increased during 2006–2010. P25-P75 was0.66–1.12 kg/m3 for the WWTPs and 36–101 g/m3 for theWTPs.

tBP02, wtBP08 – Sludge dry weight [% (w/w)] ¼Dry weight of sludge produced (%)

For the WTPs, sludge dry weight decreased, on average from30% in 2006 to 25% in 2009. The sludge produced in theWWTPs during 2006–2010 was, on average, 20%. Themedian was similar to the average.

tBP05, wtBP04 – Beneficial use of sludge [%] ¼(Sludge with beneficial use (kg)/Sludge outflow (kg)) × 100

The beneficial use of WWTP sludge was high in the analysedperiod, with an average value of 100%.

sludge production may be due to the production of less con-

centrated sludge (wtBP08) and/or to lower BOD

stabilisation efficiency (wtER02). Sludge dry weight

(wtBP08) shows high and constant values during 2006–

2010 and wtER02 was not possible to calculate, so the

cause for sludge increase was not identified.

Sludge dry weight produced in the WTPs (tBP02,

Table 4) was also high but decreased during the analysed

period (2006–2010). In the WTPs, less concentrated

sludge corresponded to higher sludge production (tBP01.1,

Table 4).

The wtBP04 indicator (Table 4) shows a median (and an

average) of 100% Beneficial use of sludge.

Safety

The Safety PIs evaluate the plant performance in terms of

environmental, plant and personnel safety.

Table 5 | PI results for safety

tSa01, wtSa01 – Spills and/or leakages of chemicals,by-products (or wastewater) [kg/(106 m3)]¼ (Chemicals,by-products (or wastewater) accidentally released (kg)/Treated(waste)water (m3)) × 106

This PI presented mostly null values.

tSa02, wtSa02 – Incidents at work (injuries and professionalillnesses) [no./(10 employee.year)]¼ (Incidents at work (no.) ×365 (day/year)/Assessment period (day)/Full time equivalentemployees (no.)) × 10

In the WTPs the median was zero. In the WWTPs, P25-P75 was0.0–0.7 incidents per 10 employee per year.


The indicator of Spills and/or leakages of chemicals, by-

products (or wastewater) ((w)tSa01) was zero for most case-

studies, corresponding to very good performance. Incidents

at work (injuries and professional illnesses) occurred in the

WTPs in 2008 and 2010 and almost every year in the

WWTPs (Table 5).

Personnel

This assessment group evaluates plant performance in

terms of availability of personnel, their qualifications and

training, absenteeism and overtime work.

In terms of personnel availability ((w)tPe01, Table 6), the

studiedWTPs present a median of 1.7 employees/(106 m3) of

treated water, while the WWTPs have a median of 4.7

employees/(106 m3) of treated wastewater, half of which

have basic education and one sixth with a university degree

((w)tPe02, Table 6). Absenteeism ((w)tPe06.1, Table 6)

increased in 2009, and this increase was mostly due to inci-

dents at work (injuries and professional illnesses) ((w)

tPe07). For theWWTPs, the highestAbsenteeismby incidents

at work in 2009 is consistent with the PI relative to Incidents

at work (wtSa02), which was also higher in 2009. Overtime

work ((w)tPe08, Table 6) decreased, showing a better ade-

quacy of (W)WTP personnel utilisation.

Economic and financial resources

The Economic and financial resources indicators evaluate

the plant performance in terms of revenues, costs and econ-

omic sustainability. Unit capital costs and unit running

costs, taken as a whole and specifying the major contri-

butions (i.e. personnel, electrical energy, chemicals and

bed media, by-product disposal, external services for analyti-

cal control and maintenance), are considered in this

assessment group.

For the studied WWTPs, the Unit revenue (wtFi01,

Table 7) and the Unit running costs were both higher in

2009, particularly the revenues, so the Running cost cover-

age ratio (wtFi10, Table 7) was also higher in this year. In

some WWTPs the unit revenues did not cover the unit run-

ning costs. In addition, the higher the costs were, the lower

the coverage ratio was.

Personnel costs and Electrical energy costs account for a

major contribution (one fourth each) of the Unit running

costs. Similarly to Energy consumption, the Electrical

energy cost also slightly increased during the studied

period, and these PIs are, as expected, directly related

(Table 7). The results shown must, however, be analysed

with reservation due to the low data reliability and accuracy,

as mentioned earlier.

Table 6 | PI results for personnel

(w)tPe01 – (W)WTP personnel [no./(106 m3.year)] ¼(Full time equivalent employees (no.) × 365 (day/year)/Assessmentperiod (day)/Treated (waste)water (m3))× 106

The median was 1.7 and 4.7 no./(106 m3.year) for the WTPs andWWTPs, respectively.

(w)tPe02 – Personnel with higher education [%] ¼((W)WTP employees with higher education (no.)/Full timeequivalent employees (no.)) × 100

This PI shows that in 2006–2010, on average, ca. 20% of theemployees have higher education. The median was slightly lowerthan the average, 18.5% for WTP and 14.3% for WWTP.

(w)tPe06.1 – Absenteeism [%]¼(Absenteeism (hour) × 365 (day/year)/Assessment period (day)/Maximum potential workload (hour/year)) × 100

The absenteeism increased from 2006 to 2009, particularly forWTP. WWTPs showed higher values than WTPs, but theoverall box plot was similar.

(w)tPe08 – Overtime work [%] ¼(Overtime work (hour) × 365 (day/year)/Assessment period (day)/Maximum potential workload (hour/year)) × 100

The WTPs and the WWTPs presented a slightly decrease ofovertime work. WWTPs showed higher values than WTPs.


Planning and design

Planning and design indicators evaluate other aspects

that are not directly related to short- and medium-term tech-

nical management decisions but influence the WWTP

environmental and economic performance. PIs of this

group include Planning and design personnel (wtPD01),

Land occupation by treatment system (wtPD02), Land occu-

pation by landscape and other valuable elements (wtPD03)

and Current land valuation (wtPD04).

In 59% of the studied WWTPs, wtPD02 shows constant

values during 2006–2010, P25-P75 is 0.30–0.80 m2/(m3/d)

and the median is 0.46 m2/(m3/d).

FINAL REMARKS

The work undertaken in the scope of the PASt21 field test

allowed opportunities to be identified for improving the

clarity and formulation of the first generation indicators

and their variables, and new indicators were developed,

giving rise to the second generation of the PI systems for

WTPand urbanWWTP. This field test involving 27 treatment

plants and a 5-year study period (2006–2010) also allowed

selecting, from the developed portfolio of PIs, those associ-

ated with the specific objectives of each case-study.

It was concluded that all indicators of the second gener-

ation systems are relevant depending on the assessment

Table 7 | PI results for economic and financial resources

(w)tFi01 – Unit revenue [Eur/m3] ¼(Operating revenues (Eur) –Capitalised costs of self-constructed assets (Eur))/Raw (waste)water (m3)

On average, there was an increase during the analysed period. In2009, the range P25-P75 was wider (0.17–0.50 Eur/m3) and themedian was 0.42 Eur/m3.

(w)tFi03 – Unit running costs [Eur/m3]¼ (Operating costs (Eur) –Capitalised costs of self constructed assets (Eur))/Treated (waste)water (m3)

As in the previous PI, there was an increase during the analysedperiod. In 2009, P25-P75 was 0.14–0.40 Eur/m3 and the medianwas 0.25 Eur/m3.

(w)tFi05.1 – Electrical energy costs [Eur/m3] ¼Electrical energy costs (Eur)/Treated (waste)water (m3)

The overall median was 0.04 Eur/m3 and P25-P75 was0.02–0.12 Eur/m3.

(w)tFi10 – Running cost coverage ratio [–]¼ Total revenues (Eur)/Running costs (Eur)

In 2006–2010, P25-P75 was 0.82–2.4 and the median 1.31. SomeWWTPs presented values below 1.


objectives, although in some treatment plants the lack of

reliable data may limit the use of a few PIs. The results

show the ability of these PI systems to assess the overall per-

formance of a given treatment plant. Whenever statistically

feasible, box plots which aggregate the results of several

case-studies for each PI and for each year (to a maximum

of 5 years) are automatically produced by PAStool and

include the average, median, percentiles 25 and 75, maxi-

mum, minimum, extreme outliers and the percentage of

cases entering this aggregation. The aggregated results of

an indicator may be used as reference values whenever

these are not included in the PI form, provided that the

aggregation is made for a group of similar undertakings in

terms of the performance criterion assessed by that particu-

lar PI. The aggregated results are ultimately very important

for the continuous improvement of the plant performance

through benchmarking and periodic reassessment of targets.

This requires the systems to be used on an annual basis, and

the calendar year is recommended as the reference assess-

ment period.


ACKNOWLEDGEMENTS

The authors acknowledge the PASt21 consortium for the

valuable contribution to this second generation of

performance indicators and their variables, and for

providing the data for testing and implementing the

performance assessment systems.

REFERENCES

Alegre, H., Hirner, W., Melo Baptista, J. & Parena, R. Performance Indicators for Water Supply Services, 1st edition.Manual of Best Practices Series. IWA Publishing, London.

Alegre, H., Melo Baptista, J., Cabrera Jr, E., Cubillo, F., Duarte, P.,Hirner, W., Merkel, W. & Parena, R. PerformanceIndicators for Water Supply Services, 2nd edition. Manual ofBest Practices Series. IWA Publishing, London.

DWA Corporate Benchmarking – Metric Benchmarking asComponent of the Modernisation Strategy – PerformanceIndicators and Evaluation Principles. DWA GermanAssociation for Water, Wastewater and Waste (A. Schulzas Spokesperson of the working group), Germany.

Matos, R., Cardoso, A., Ashley, R., Duarte, P., Molinari, A. &Schulz, A. Performance Indicators for WastewaterServices. Manual of Best Practices Series. IWA Publishing,London.

Metcalf & Eddy Wastewater Engineering – Treatment andReuse, 4th edition (revised by G. Tchobanoglous, F. L.Burton & H. D. Stensel). McGraw-Hill, Inc., New York.

Ofwat Updating the Overall Performance Assessment (OPA)– Conclusions and Methodology for 2004–05 Onwards. UKOffice of Water Services, Birmingham, UK.

Ofwat Levels of service for water industry in England &Wales, 2005–2006 report. UK Office of Water Services.

Qasim, S. R. Wastewater Treatment Plants – Planning,Design and Operation, 2nd edition. Technomic PublishingCo., Lancaster, PA.

Quadros, S., Rosa, M. J., Alegre, H. & Silva, C. Aperformance indicators system for urban wastewatertreatment plants. Water Science and Technology 62 (10),2398–2407.

Rosa, M. J., Quadros, S., Silva, C., Vieira, P., Ramalho, P. &Alegre, H. a Fichas de Indicadores de DesempenhoGlobal de ETAR. Nota Técnica 6/2011_NES(Annex to Final Report of The Portuguese initiativefor performance assessment of water and wastewatertreatment plants). LNEC. Lisbon, June, 126 pp(in Portuguese).

Rosa, M. J., Vieira, P., Silva, C., Quadros, S., Ramalho, P. &Alegre, H. b Fichas de Indicadores de DesempenhoGlobal de ETA. Nota Técnica 5/2011_NES (Annex toFinal Report of The Portuguese initiative for performanceassessment of water and wastewater treatment plants).LNEC. Lisbon, June, 73 pp (in Portuguese).

Stahre, P. & Adamsson, J. Performance benchmarking: Apowerful management instrument for water and wastewaterutilities. Water Technology 12, 47–77.

Stahre, P., Adamsson, J. & Mellstrom, G. A newapproach for assessment of the performance of waterdistribution and sewerage networks. In: InternationalConference on Performance Assessment of UrbanInfrastructure Services. Drinking water, wastewater andsolid waste (E. Cabrera, & M. A. Pardo Jr, eds). IWAPublishing, London. pp. 5–24.

Vieira, P., Alegre, H., Rosa, M. J. & Lucas, H. Drinkingwater treatment plants assessment through performanceindicators. Water Science and Technology – Water Supply8 (3), 245–253.

Vieira, P., Rosa, M. J., Alegre, H., Ramalho, P., Silva, C. & Lucas,H. Avaliação de desempenho de estações de tratamentode água. Águas & Resíduos, série III. No. 9, January/April,pp. 4–17 (in Portuguese).

Vieira, P., Rosa, M. J., Alegre, H. & Lucas, H. Assessing theoperational performance of water treatment plants – focus onwater quality and treatment efficiency. In Proceedings of IWAWorld Water Congress. Montréal.

World Bank IBNET indicator definitions. World Bank,Washington, DC.

First received 8 July 2011; accepted in revised form 5 January 2012

http://dx.doi.org/10.2166/wst.2010.526



http://dx.doi.org/10.2166/ws.2008.068

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http://dx.doi.org/10.2166/ws.2008.068

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