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Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy
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Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy

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The aim of the study is to describe the activities carried out in Italy by the ENEA Agency in order to define a new performance indicator for wastewater treatment service taking into account the …

The aim of the study is to describe the activities carried out in Italy by the ENEA Agency in order to define a new performance indicator for wastewater treatment service taking into account the appropriateness and efficiency of existing plants equipment and, consequently, evaluating economic incentives. The activity was carried out under the ENEA-MiSE (Italian Ministry of Economic Development) agreement.

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  • 1. Towards new urban wastewater treatment Performance Indicators for life quality improvement: experiences from Italy S. De Gisi, L. Petta, P. Mulargia, R. Farina The 7th IWA Specialist Conference on Efficient Use and Management of Water “Water Efficient Strategies for Difficult Times”, October 22th 2013, Paris, France
  • 2. Framework • Introduction • Incentive mechanisms for efficiency • The « Service Objectives » System • The aim of the study • Materials and methods • Framework of the proposed methodology • Results and discussions • Assessment of the municipal WWTPs quality for each District of Southern and Islands of Italy • Evaluation of the wastewater treatment plants quality coefficient (β) • Mid-term incentives for S.11 indicator • Conclusions • References
  • 3. Introduction An Incentive mechanisms … An incentive mechanism is aimed at motivating individuals or government institutions in order to encourage better performances in any specific service supply sector. Water Energy Solid waste
  • 4. Introduction … and its characteristics An incentive mechanism: • must be based on appropriate indicators able to evaluate the quality of sector/service investigated; • should be publically accepted by stakeholders in order to have a policy efficient (Kallbekken, 2013); • should have transparency of the method and the ability to earmark eventually revenues (Kallbekken and Aasen, 2010).
  • 5. Introduction Public acceptability of the incentive • Kallbekken (2013) highlights a trade-off between acceptability of the incentive (or in general, other price instruments) and efficiency of the policy. • Generally, the most efficient policies are often the least acceptable. Acceptability of incentive mechanism Efficiency of the policy A new proposal for an incentive should consider the success level of the current mechanism. Where the mechanism is publicly accepted, a new procedure should change as little as possible the current procedure architecture.
  • 6. The “Service Objectives” system Thematic areas • Education Care for the elderly and children The “Service Objectives” system Integrated water service Management of municipal solid wastes Introduced in Italy by the National Strategic Framework 2007-2013 (Italian Law 296, 2006) in compliance with the EC Council Regulation 1083/2006, the “Service Objectives” system is an innovative results-oriented programme related to 4 thematic areas: education, care for the elderly and children, management of municipal solid wastes and integrated water service.
  • 7. The “Service Objectives” system Partnerships Southern Italy and Islands districts
  • 8. The “Service Objectives” system The aim of the mechanism THE SYSTEM GOAL The system aims at improving the quality of life of Southern Italy and Islands citizens by means of an incentive mechanism providing subsides for a total amount of EUR 3 billion … INDICATORS Intermediate verification in 2009 Evaluation of the intermediate incentive A B C Publication of results A = base value B = intermediate value 2005 2007 2008 2009 2010 ISTAT data aquisition for the S.11 indicator 2013 C = target … according to the achievement in 2013 of specific targets set for 11 service indicators related to as many essential services. An intermediate verification in 2009 was also expected in order to provide a first incentive advance.
  • 9. The “Service Objectives” system The “Service Objectives” system indicators S.01 400 350 300 250 200 150 100 50 0 S.11 S.10 S.02 S.03 S.09 S.04 S.08 S.05 S.07 The S.11 indicator S.06 (Values in Million of Euro) The amount of potential reward resources at 2013 for each indicator (Values in Millions of euro) S.11 = PEeff/PEtot [%]
  • 10. The “Service Objectives” system The current procedure for intermediate incentives evaluation (1) (2) (3) (4) α coefficient = f (coverage degree of the sewage system)
  • 11. The aim of the study • The aim of the work is to define a new methodology for the evaluation of the intermediate incentive in the wastewater sector that takes into account (i) the urban wastewater treatment demand as well as (ii) the quality of wastewater treatment service. • A simulation on the basis of data provided by ISTAT (with reference to the time horizon 2005-2008-2013) for Southern Italy and Islands districts was carried out in order to achieve this goal.
  • 12. Materials and methods Framework of the proposed methodology Phase 1 Definition of alternatives (Municipal WWTPs) Phase 2 Application of MCA Data input Criteria Criteria definition definition Data validation Weights definition Alternative definition Application of MCA Phase 3 Wastewater quality evaluation for each District Phase 4 Evaluation of β coefficient Phase 5 Evaluation of α coefficient (quality) (coverege degree of sewage system) Evaluation of β coefficient Evaluation of α coefficient Phase 6 Evaluation of intermediate incentives Definition of the WWTPs indices for each District Evaluation of WWTPs quality (IPDISTRICT) Evaluation of intermediate incentives
  • 13. Materials and methods Proposed methodology: data input Outlet WW Flow-rate, BOD5, COD, Ntot, TSS, Ptot WWTP Performance Flow-rate, BOD5, COD, Ntot, TSS, Ptot Influent WW WWTP Flow-chart water line 1 2 3 4 5 ISTAT survey (2008) Large WWTPs (PE > 50,000) Values for each month of sampling, on annual basis 9 Bar Screens Grit Chamber Primary Settling Tank Denitrification 7 8 6 10 Oxidation / Nitrification Tank Secondary Settling Tank Biofiltration (BFs) Disinfection 11 Primary Sludge Return Activated Sludge Secondary Sludge
  • 14. Materials and methods Proposed methodology: data validation Data acquired (concentrations, flow-rate, Population equivalent, Industrial percentage…) with the ISTAT questionnaire are true? The WWTP’s flow-chart is in line with that present in the system? Open questions ….
  • 15. Example of use of aerial photos to validate the WWTP’s flow-chart Secondary sedimentation processes Primary treatment Disinfection Effluent Inlet WW Secondary treatment for the removal of organic matter Pre-treatment
  • 16. Materials and methods Proposed methodology: evaluation criteria N. C1 Criteria N. Parameter Technological C11 Primary and equipment secondary treatment C12 C13 C14 C2 Environmenta C211 l performance of the plant C212 C213 C214 C215 Part 1 Description and attribution of value to the parameter/sub-parameter With reference to the current technological equipment installed in the WWTP, are there primary and secondary treatments units (for the removal of the organic substance)? Three classes were considered with correspondent qualitative and quantitative judgments: Class 1: Yes, with primary and secondary treatment (0.666); Class 2: Yes, with only primary treatment (0.500); Class 3: No, there is neither a primary nor a secondary treatment (0.166). TO MAXIMIZE Treatments for With reference to the current technological equipment installed in the WWTP, are there treatments units for nutrients removal Nutrients removal (nitrogen and phosphorous)? Four classes were considered: Class 1: Yes, with nitrogen and phosphorus removal (0.875); Class 2: Yes, (Nitrogen and only with nitrogen removal (0.625); Class 3: Yes, only with phosphorus removal (0.375); Class 4: No treatment unit is installed Phosphorus) (0.125). TO MAXIMIZE Tertiary With reference to the current technological equipment installed in the WWTP, are there tertiary treatment units? Four classes were treatments considered with correspondent qualitative and quantitative judgments: Class 1: Yes, with sand filtration and microfiltration (0.875); Class 2: Yes, with only microfiltration (0.625); Class 3: Yes, with only sand filtration (0.375); Class 4: No treatment unit is installed (0.125). TO MAXIMIZE Disinfection With reference to the current technological equipment installed in the WWTP, are there disinfection treatment units? Four classes were considered: Class 1: Yes, with the use of technologies (UV, filter membranes, per acetic acid) more suitable with reference to the minimization of the formation of DBPs (0.875); Class 2: Yes, with the use of ozone (0.625); Class 3: Yes, with the use of chlorine compounds (chlorine gas, sodium hypochlorite) (0.375); Class 4: No treatment unit is installed (0.125). TO MAXIMIZE BOD5 With reference to the nitrogen concentration values in the effluent, according to the Italian and European legislation, how many cases of non-compliant samples of BOD5 have been observed for each month of sampling, on annual basis? Four classes were considered with correspondent qualitative and quantitative judgments: Class 1: number of non-compliant samples between 0-25% (inclusive), (0.875); Class 2: number of non-compliant samples between 25-50% (inclusive), (0.625); Class 3: number of non-compliant samples between 50-75% (inclusive), (0.375); Class 4: Number of non-compliant samples between 75-100% (inclusive), (0.125). TO MAXIMIZE COD As for parameter C211, how many cases of non-compliant samples with respect to COD have been observed? TO MAXIMIZE TSS As for parameter C211, how many cases of non-compliant samples with respect to TSS have been observed? TO MAXIMIZE Total Nitrogen As for parameter C211, how many cases of non-compliant samples with respect to Total Nitrogen have been observed? TO MAXIMIZE Total Phosphorus As for parameter C211, how many cases of non-compliant samples with respect to Total Phosphorous have been observed? TO MAXIMIZE
  • 17. Materials and methods Proposed methodology: evaluation criteria N. Criteria N. C221 C222 C223 C224 C225 C3 Treatment capacity C31 C32 C33 Part 2 Parameter Description and attribution of value to the parameter/sub-parameter Percentage removal With reference to the percentage removal of Total Nitrogen (% NTOT), according to the Italian and European legislation, how many of total nitrogen (%N) cases of non-compliant samples have been observed for each month of sampling on annual basis? Four classes were considered with correspondent qualitative and quantitative judgments: Class 1: number of non-compliant samples between 0-25% (inclusive), (0.875); Class 2: number of non-compliant samples between 25-50% (included), (0.625); Class 3: number of non-compliant samples between 50-75% (inclusive), (0.375); Class 4: Number of non-compliant samples between 75-100% (inclusive), (0.125). TO MAXIMIZE (a) Percentage removal As in the criteria C221, how many cases of non-compliant samples have been observed with reference to the percentage removal of of total phosphorus Total Phosphorous (% PTOT)? TO MAXIMIZE (a) (%P) Percentage removal As in the criteria C221, how many cases of non-compliant samples have been observed with reference to the percentage removal of of BOD5 (%BOD5) BOD5 (% BOD5)? TO MAXIMIZE (b) Percentage removal As in the criteria C221, how many cases of non-compliant samples have been observed with reference to the percentage removal of of COD (%COD) the COD (% COD)? TO MAXIMIZE (b) Percentage removal As in the criteria C221, how many cases of non-compliant samples have been observed with reference to the percentage removal of of TSS (%TSS) TSS (% TSS)? TO MAXIMIZE (b) Domestic wastewater With reference to the rate of domestic influent wastewater, the treatment capacity of the plant is defined as the ratio of the Total Effective Domestic Population Equivalent (PEtot, eff) and Total Design Domestic Population Equivalent (PEtot, design). The lower is the value the greater is the residual capacity of treatment of the plant. In this way the costs for possible future interventions relating to structural adjustment are reduced. TO MINIMIZE Industrial wastewater As in the case of C31 criteria, but considering the rate of industrial influent wastewater. TO MINIMIZE Treatment of tanker Treatment of tanker wastewater means the treatment of septic tanks or industrial plants, generally transported by tankers and then wastewater processed in the system (i.e. via a special section) before being mixed into the influent wastewater or sludge line. The purpose of such pre-treatment is to avoid overloads and alterations of plant operation. With reference to the current technological equipment, the plant is able to treat the tanker wastewater? YES = 0.75; NO = 0.25. TO MAXIMIZE
  • 18. Materials and methods Proposed methodology: weights vector Criteria’s level with the PCT method S-WWTPs priorities(a) NS-WWTPs priorities(b) 1st Local Global Local Global 2nd 3rd C1 0.333 0.333 0.333 0.333 C11 0.100 0.033 0.350 0.117 C12 0.350 0.117 0.350 0.117 C13 0.200 0.067 0.100 0.033 C14 0.350 0.117 0.200 0.067 0.500 0.500 0.500 0.500 0.667 0.334 0.667 0.334 C211 0.167 0.056 0.300 0.100 C212 0.167 0.056 0.300 0.100 C213 0.067 0.022 0.167 0.056 C214 0.300 0.100 0.167 0.056 C215 0.300 0.100 0.067 0.022 0.333 0.167 0.333 0.167 C221 0.500 0.083 C222 0.500 0.083 - - C223 - 0.069 - 0.417 0.069 C225 - - 0.417 C224 0.167 0.028 0.167 0.167 0.167 0.167 C31 0.417 0.070 0.417 0.070 C32 0.417 0.070 0.417 0.070 C33 0.167 0.028 0.167 0.028 C2 C21 C22 C3 S-WWTPS NS-WWTPS SENSITIVE - WWTPS C2 > C1 > C3; C12 = C14 > C13 > C11; C21 > C22; C214 = C215 > C211 = C212 > C213; C221 = C222; C31 = C32 > C33; ( NOT - SENSITIVE – WWTPS C2 > C1 > C3; C11 = C12 > C14 > C13; C21 > C22; C211 = C212 > C214 = C213 > C215; C223 = C224 > C225; C31 = C32 > C33.
  • 19. Materials and methods Proposed methodology: WWTPs performance indices
  • 20. Materials and methods Proposed methodology: β coefficient IPDISTRICT quality classes Definition of the wastewater treatment quality coefficient (β) classes for municipal WWTPs. β • The evaluation of the wastewater treatment quality coefficient (β) is carried out on the basis of the values reported in Table as a function of the IPDISTRICT Quality class Class 1 Class 2 Class 3 Class 4 Class 5 (IPDISTRICT) Range values 0.800 – 1.000 0.600 – 0.800 0.400 – 0.600 0.200 – 0.400 0.000 – 0.200 (β) Values β 1.0 0.9 0.8 0.7 0.6
  • 21. Results and discussion Mid-term incentives for S.11 indicator 3 GOAL Evaluation of the β coefficient Assessment of the municipal WWTPs quality for each District of Southern and Islands of Italy 2 1
  • 22. Results and discussion 1) Assessment of the municipal WWTPs quality for each District of Southern and Islands of Italy
  • 23. Results and discussion 2) Evaluation of the β coefficient • It can be observed how Sardinia (1.000) can be considered like the best district in terms of municipal WWTPs quality, but has to be underlined the advantage of the limited number of WWTPs assessed (only one plant > 50,000 PE). • Whereas, the worst performances are related to the following districts: Abruzzo, Basilicata and Molise (0.600).
  • 24. Results and discussion 3) Mid-term incentives for S.11 indicator: comparison between the current procedure and the proposal
  • 25. Results and discussion 3) Mid-term incentives for S.11 indicator: the management of the surplus • With reference to the amount of resources provided at the moment of the intermediate verification (187.5 M€), the overall mid-term incentives at 2009 are of 166.10 M€ and 138.92 M€ respectively using the current method and the new proposal. The surplus is of 27.18 M€. • The management of the surplus is an interesting element of this proposal as it should be used to balance a potential decrease of acceptability by stakeholders due to the introduction of the new mechanism. Consequently, in order to increase the acceptability of the method as well as the competitiveness of the districts, a re-distribution of such surplus has been expected in the proposed methodology according to the following relation: PDISTRICT = intermediate incentive at 2009 for the single district after the surplus re-distribution = intermediate incentive at 2009 for the single district evaluated with the proposed procedure; = intermediate incentives at 2009 evaluated with the proposed procedure; = intermediate incentives at 2009 evaluated with the current procedure.
  • 26. Results and discussion 3) Mid-term incentives for S.11 indicator after surplus re-distribution
  • 27. Policy Implications Policy implications • The “Service Objectives” system presented in this study involves the use of appropriate indicators aimed at monitoring the achievement of specific objectives in a temporal period of about 10 years. • Its policy falls within the medium-term actions aimed at encouraging each district in completing those infrastructures necessary for the development of the territories. • Therefore, the “Service Objectives” mechanism is linked to the policies of the individual regions and as such it could potentially affect the programming of structural interventions in the field of public works. This aspect is important and should be properly managed. • Potential conflicts could generate vertical fragmentations with reference to the decision chain and as such the failure of the mechanism. • Consequently, it is essential that all those actions that could encourage the stakeholder’s acceptability are implemented.
  • 28. Conclusions The following outcomes can be pointed out: • data without uncertainty are required, such as those provided by an official survey (as ISTAT in the case of Italy); • the lowest possible number of indices should be selected, so as to adequately describe the wastewater treatment plants under study; • a proper wastewater treatment plants quality assessment at district-scale (or other geopolitical area) necessarily requires a large number of plants to be taken into account, also with reference to the small wastewater treatment systems (<2000 PE); • in order to set an effective incentive mechanism, districts that do not communicate data according to the fixed deadlines have to be penalized, so as to force their commitment in providing the required information as well; • in order to increase the public acceptability and consequently the success of the policies, high importance must be given to the following aspects: understanding of the method, budgetary transparency, public resources allocation, more information about how revenues are spent.
  • 29. References • Council Directive 91/271/EEC of 21 May 1991 concerning urban waste-water treatment. • Council Regulation (EC) n. 1083/2006 of 11 July 2006 laying down general provisions on the European Regional Development Fund, the European Social Fund and the Cohesion Fund and repealing Regulation (EC) No 1260/1999. • D.Lgs. 152/2006. Decreto Legislativo 3 Aprile 2006, n. 152. “Norme in materia ambientale”, Gazzetta Ufficiale n. 88 del 14 Aprile 2006 – Supplemento Ordinario n. 96 (in Italian). • Delibera CIPE 82/2007, Regole di attuazione del meccanismo di incentivazione legato agli obiettivi di servizio del QSN 2007-2013, Gazzetta Ufficiale n. 301 del 29/12/2007 (in Italian). • Hutchinson E., Kennedy P.W., Martinez C. 2010. Subsidies for the production of cleaner energy: When do they cause emissions to rise?. B E J Econ Anal Pol. 10(1), 1-9. • ISTAT, 2008. Il Sistema delle Indagini sulle Acque. Anno 2008. ISTAT, Rome, Italy (in italian). • Kallbekken S. 2013. Public Acceptability of Incentive-Based Mechanisms. In: Shogren, J. (Ed.), Encyclopedia of Energy, Natural Resource and Environmental Economics. Elsevier Inc., ISBN: 978-0-08-096452-2, pp. 306-312. • Legge 27 dicembre 2006, n. 296. “Disposizioni per la formazione del bilancio annuale e pluriennale dello Stato (legge finanziaria 2007)”, Gazzetta Ufficiale n. 299 del 27 dicembre 2006 - Supplemento ordinario n. 244 (in Italian). • Lienert J., Schnetzer F., Ingold K. 2013. Stakeholder analysis combined with social network analysis provides fine-grained insights into water infrastructure planning processes. J Environ Manage. 125, 134-148. • MiSE (Italian Ministry of Economic Development) 2010. Stato di avanzamento degli Obiettivi di Servizio, Istruttoria per l’attribuizione dei premi intermedi – Prima relazione al Comitato Nazionale per il Coordinamento e la Sorveglianza della Politica Regionale Unitaria (in Italian). • Perotto E., Canziani R., Marchesi R., Butelli P. 2008. Environmental performance, indicators and measurement uncertainty in EMS context: a case study. J Clean Prod. 16, 517-530. • Segerson K. 2013. Price Instruments. In: Shogren, J. (Ed.), Encyclopedia of Energy, Natural Resource and Environmental Economics. Elsevier Inc., ISBN: 978-0-08-096452-2, pp. 185-192.
  • 30. Sabino DE GISI, Ph.D. sabino.degisi@enea.it Luigi PETTA, Ph.D. luigi.petta@enea.it Pierpaolo MULARGIA, MSc Pierpaolo.mulargia@enea.it Roberto FARINA, MSc roberto.farina@enea.it Italian National Agency for the New Technology, Energy and Sustainable Economic Development, Water Resource Management Lab. Via Martiri di Monte Sole 4, 40129, Bologna (ITALY)

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