Introduction

Sewage sludge management is a well-known critical step in the operation of biological wastewater treatment plants (WWTPs) because sludge treatment and disposal often account for one half of the plant’s operating cost (Lue-Hing et al. 1996; Wei et al. 2003; Neyens et al. 2004; Mahmood and Elliott 2006; Pérez-Elvira et al. 2006; Saveyn et al. 2008; Ruiz-Hernando et al. 2010; Ozdemir and Yenigun 2013), so that wastewater treatment processes may convert a water pollution control problem into a solid waste disposal problem (Weemaes and Verstraete 1998).

Sludge production has been unceasingly growing, as a consequence of both the increase of collected and treated wastewaters and the application of progressively more restrictive standards for WWTPs effluent quality (Neyens et al. 2004; Kouloumbos et al. 2008; Fytili and Zabaniotou 2008; Kelessidis and Stasinakis 2012). Furthermore, increasing difficulties in finding appropriate recovery/disposal systems push towards management strategies which should focus on the reduction of the amount of the produced sludge (Mahmood and Elliott 2006). A critical point in dealing with sludge management is that in many cases, the greater the water treatment efficiency, the higher the production and level of contamination of the sludge. Several technologies and management strategies are proposed to minimize sludge production and contamination (Liu and Tay 2001; Wei et al. 2003; Foladori et al. 2010). Nevertheless their techno-economic feasibility has to be carefully evaluated, because the suitability of a technological solution depends on numerous variables, most of which are remarkably site specific. Unfortunately, the lack of reliable and science-based evaluation criteria often leads decision makers to keep conservative positions (i.e. nothing changed), on the basis of personal thoughts, views and/or experiences or in consideration of the scarce public acceptance (Achillas et al. 2013). This is, for instance, the case of sludge agricultural reuse and incineration, which are perceived as a risk to human health and environment.

Several EU research funding programmes have been issued on sludge management strategies during the last decade: among the latest, ROUTES (Novel processing routes for effective sewage sludge management, www.eu-routes.org) and END-O-SLUDG (Wastewater transformed for good, www.end-o-sludg.eu) projects are included in the Seventh Framework Programme.

Within the ROUTES project, an integrated sustainability assessment of conventional and innovative solutions was developed, which is based on both techno-economic and environmental aspects (Life Cycle Assessment (LCA)). This procedure is intended to overcome the limitations of commonly used multi-criteria decision analysis (MCDA) techniques that, as pointed out in the review by Achillas et al. (2013), are usually focused on cost and environmental impacts assessment and do not consider technical aspects and social acceptability. The novel tool can be adopted by WWTP managers as well as by administrative authorities in charge of planning sludge management strategies at the regional level.

In this paper, the new methodology for techno-economic assessment is presented. It is intended for assessing a given strategy for the upgrading of an existing plant that requires a more efficient sludge management. The solution under evaluation may either consist of a simple correction of the operative parameters or can imply more complex modifications of the process configuration including several complementary units and new technologies. The input data for the evaluation procedure consist of the specific features of the existing plant, such as process configuration, size, sludge production and operative issues (e.g. overloading of anaerobic digester, poor quality of the sludge for agriculture application, high nutrient concentration in the reject water from the sludge line, etc.), as well as site-specific boundary conditions, such as wastewater characteristics, effluent standards to be complied with, cost details (labour, energy and materials), etc. Beside describing the whole procedure, the paper includes a full set of reference values and assumptions for design and mass balance calculation with reference to a generic plant layout, as well as examples of the results from the evaluation of an innovative solution selected among those studied within the ROUTES project, where several case studies were outlined: each case study consisted of a model reference WWTP considered to experience different types of common problems and at least one upgraded plant in which different new technologies and designs had been introduced to solve these problems (for a complete list and description of all the studied solutions, see the factsheets in project website and Mininni et al. 2014).

Description of the methodology

This section provides a description of the methodology developed for the evaluation of a generic plant and situation. The procedure consists of three main steps as described below and illustrated in Fig. 1:

Fig. 1
figure 1

The three main steps of techno-economic assessment procedure

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  1. 1.

    Mass and energy balances calculation;

  2. 2.

    Technical assessment;

  3. 3.

    Economic assessment.

Mass and energy balances

Data set

In case the assessment procedure is being applied to an existing WWTP, required data, such as the influent and effluent wastewater characteristics, thermal and electric energy consumption, sludge production etc., is known, as well as the main plant features (configuration, reactor size, recirculation flow rates, etc.). Average conditions have to be selected, taking into consideration that the aim is to perform an evaluation based on a yearly balance.

On the contrary, when direct measurements cannot be performed, essential data must be assumed or calculated. As an example, the following assumptions were made by the authors within the ROUTES project:

  • Raw wastewater characteristics: defined according to the literature (e.g. Metcalf and Eddy 2003);

  • Effluent characteristics: defined taking into account the final destination of the effluent (i.e. sensitive/less sensitive area) and the plant size (accordingly with Directive 91/271/EEC of the 21th May 1991 concerning urban waste water treatment);

  • Wastewater temperature, 15 ° C;

  • Average performance (removal efficiency) of primary sedimentation: total suspended solids (TSS) 60 %, chemical oxygen demand (COD) 30 %, BOD5 35 %, Ntot 10 %, Ptot 10 %.

Based on these assumptions, the biological section was designed with the support of the Activated Sludge Computer Aided Modelling (ASCAM) software (Tomei et al. 1990; Carucci et al. 1994), implementing a rigorous model including the kinetic, stoichiometric and mass balance equations for all the components (substrates, biomass, oxygen, etc.) in the system. Carbonaceous substrate is characterized in terms of soluble and particulate fractions while for the biomass, the active fraction is calculated as function of the sludge retention time. This is a simpler approach in comparison with the more complex approaches (i.e. AQUASIM, WEST, etc.) but has the advantage of requiring a reduced number of parameters. In fact, the parameter evaluation is the bottleneck of complex models especially in the design phase (as in this case) when the influent characteristics are known but the kinetics and stoichiometric parameters which have to be evaluated by specific experimental tests are simply assumed. In addition, the more detailed and complex models are structured for “validation” and not for “design” that is they require, as input data, the volumes of the operation units and give, as results, the effluent characteristics. Differently, the ASCAM software has the two options “validation” and “design”, and in this ROUTES methodology, it was utilized to design the plants for the different layouts: influent data and desired effluent characteristics are the input data, and the software gives, as results, the reactor volumes, the sludge production, the oxygen consumption, the biomass and substrates concentrations in all the plant units and all other relevant operating parameters characterizing the plant (i.e. recycle and mixed liquor flow rates, settler surface, etc.) The ASCAM software gives also, as output data, the actual process kinetics which (by comparison with the maximum rates reported in the specialised literature for the considered process) allows an estimation of the safety factors of the designed units of the biological section. Designed WWTPs include nitrogen removal realized with an integrated system denitrification-nitrification utilizing the influent COD as internal carbon source for denitrification and operated with internal nitrate recycle. For one case, biological phosphorus removal has been also considered by adding an anaerobic stage to the nitrogen removal plant. Outputs from the design were utilized to build the mass balance for the relevant variables as better highlighted in the section of “Mass balance calculation”.

Mass balance calculation

Plant-wide mass balance calculations (under steady state conditions) have been implemented for both the innovative solution and for the reference plant (in the latter case, to be used when direct measurements are not available).

The pattern of following interrelated parameters has been modelled:

  • Flow rate (Q);

  • Total suspended solid (TSS);

  • Volatile suspended solids (VSS);

  • Chemical oxygen demand (COD), soluble and particulate;

  • Total nitrogen (TN), soluble and particulate.

Mass balance procedure for the different plant layouts, including water and sludge treatment lines, has been implemented on spreadsheets. Depending on the treatment scheme complexity and the number interrelating factors, a variable number of consecutive iterations is required for the mass balance to converge to the final solution.

The following set of data and assumptions were used for mass balance calculations estimated from specialized literature data:

  1. 1.

    The amount of waste activated sludge (WAS) was estimated according to the following equations (Metcalf and Eddy 2003; Ekama and Wentzel 2004; Ekama and Wentzel MC Sotemann 2006):

    $$ \begin{array}{c}\hfill {\mathrm{VSS}}_{\mathrm{WAS}}= Px+{f}_i*{\mathrm{VSS}}_{\mathrm{influent}}-{\mathrm{VSS}}_{\mathrm{effluent}}\hfill \\ {}\hfill {\mathrm{TSS}}_{\mathrm{WAS}}=\frac{ Px}{0.85}+{\mathrm{ISS}}_{\mathrm{influent}}+{f}_i*{\mathrm{VSS}}_{\mathrm{influent}}-{\mathrm{TSS}}_{\mathrm{effluent}}\hfill \end{array} $$

    where

    Px :

    Secondary biomass production (in VSS) evaluated with the ASCAM model.

    $$ {\mathrm{ISS}}_{\mathrm{influent}}={\mathrm{TSS}}_{\mathrm{influent}}-{\mathrm{VSS}}_{\mathrm{influent}} $$
    f i :

    Fraction of inert VSS in the influent, assumed to be 0.2 or 0.4 in presence or absence of primary settling, respectively.

  2. 2.

    In case of discharge in sensitive areas, a simultaneous chemical P removal with ferric chloride was included. The additional sludge production has been assumed 6 kg TSS/kg Premoved (i.e. excluding the amount associated with effluent and dewatered sludge).

  3. 3.

    A simple non-reactive model was assumed for thickeners, with removal efficiencies of the influent suspended solids (SS) and thickened sludge concentrations as specified in the following:

    • 90 % and 20 g/L, respectively, for gravity thickeners treating secondary sludge;

    • 90 % and 35 g/L, respectively, for gravity thickeners treating mixed primary and secondary sludge.

  4. 4.

    VSS removal rates in conventional aerobic and anaerobic digestion processes were assumed in the range of 20–50 %, depending on the presence/absence of primary sludge and the degree of stabilization of the secondary sludge.

  5. 5.

    Dewatering performances, in terms of SS removal efficiency and dewatered sludge concentration were assumed 95 and 20 % dry matter (DM), respectively.

  6. 6.

    The ratio COD/VSS was assumed to be 1.7 for primary sludge, 1.48 for secondary sludge and aerobically stabilized sludge, 1.42 for anaerobically stabilized sludge (Canziani et al. 1995; Wentzel et al. 2006; Ekama 2009);

  7. 7.

    Residual soluble COD concentration was assumed to be 50 mg/L in aerobic digester supernatant (Sotemann et al. 2006) and 200 mg/L in mesophilic anaerobic digester supernatant (Ekama 2009).

  8. 8.

    Release of soluble N during sludge stabilization was assumed to be equivalent to the N content in the portion of destroyed VSS during the anaerobic sludge digestion. In case of aerobic stabilization, only 20 % of the released N was assumed to be left in the supernatant by hypothesizing the presence of simultaneous nitrification/denitrification typically associated to this process due to the high mass transfer resistances in the sludge matrix and the consequent partial penetration of oxygen into the bioflocs.

  9. 9.

    The P/VSS ratio was assumed to be 0.02 for secondary sludge and both aerobically or anaerobically stabilized sludge.

    In the application of the methodology to the ROUTES plant layouts, some data included in the mass balance for the upgraded-WWTP scenario have been directly obtained from experimental activities.

Energy balance calculation

Power consumption is a relevant item of operating costs: the contribution of different devices (under average loading conditions) should be measured (in the existing plant) or estimated. Specific equations (either theoretical or empirical) for the following treatment stages/devices can be found in the scientific literature (e.g. Wesner et al. 1977; Annesini et al. 1982; Masotti 2011; Metcalf and Eddy 2003; Sigmund 2008; Lazarova and Choo 2012; Bertanza and Canato 2013; Bertanza and Papa 2014):

  • Wastewater and sludge pumping stations;

  • Bar racks and screens;

  • Grit/oil chambers;

  • Primary and secondary sedimentation tanks;

  • Biological reactors (denitrification and oxidation-nitrification processes);

  • Sludge thickening (gravity and dynamic);

  • Sludge stabilization (aerobic and anaerobic);

  • Mechanical dewatering.

It has to be pointed out that the contribution to total energy consumption of some of the above reported items is negligible (e.g. bar racks and screens, grit/oil chambers, primary and secondary settlers and thickeners). On the contrary, power requirements related to water and sludge pumping, denitrification tank mixing, air supply (in both water and sludge line) and sludge dewatering can account for 70–75 % of global energy requirement.

In case of innovative technologies, power requirement of specific devices/processes has to be evaluated from the experimental data or estimated from similar applications.

Based on detailed calculations, it is possible to have a reliable comparison and highlight the difference in power consumption between the upgraded (with the new solution/technology) and the reference WWTP; an example is represented by the calculation of energy requirement for biological process, which takes into account the increase of COD and nitrogen load derived by the return streams from the sludge line.

Thermal energy balance has been performed considering, in case of anaerobic digestion, the possibility of using the produced biogas for satisfying the process heat requirements (e.g. for anaerobic digesters and pasteurization stage) and eventually utilizing the surplus amount for other purposes (e.g. electric energy production). Obviously, where available, excess heat deriving from other equipment must be considered in the balance and the use of biogas in combined heat and power systems (CHP) instead of a boiler may be preferable. In case biogas production is not enough to satisfy thermal energy balance, methane is supplied from the grid.

Theoretical energy balance

In order to get further information for the final assessment, the theoretical energy balance has been calculated. This parameter represents the exploitation level of sewage chemical energy referred to the amount of energy needed for biological process only. The calculation procedure is widely documented in scientific literature (Nowak et al. 2011; Svardal and Kroiss 2011). Based on this approach, the higher is this ratio, the more a process is optimized: chemical energy exploitation could seldom be even higher than energy needed for the whole treatment.

Input data for theoretical energy balance calculation are the COD balance (originating from mass balances of the whole process) and the energy balance. The latter takes into account the energy consumption for sewage treatment (COD and nitrogen removal) and sludge aerobic stabilization (if present), as well as the theoretical energy production from exploitation of biogas produced during anaerobic sludge digestion.

Technical assessment

The technical items which were considered to be crucial for the assessment of upgrading solutions are listed in Table 1. Main aspects (categories) consist of subcategories which should be separately evaluated. It is noted that some of the subcategories should be assessed based on the results of research activities or plant monitoring (they are marked with “R” in Table 1); other items (marked with “L”) are site specific and depend on local conditions and circumstances (i.e. the implementation of a new technology impacts on each plant, depending on several site-specific issues, such as its original configuration, as well as public sensitivity, etc.). Some items are marked with both “R” and “L”; in these cases, the process performance is also dependent on local circumstances.

Table 1 Factors to be considered for the technical assessment along with data sources
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As stated above, the proposed procedure was developed for evaluating the application of a new technology/solution for upgrading an existing plant; therefore, each comparison is always referred to a reference scenario. The new tool was aimed at enabling a quick and clear representation of advantages and disadvantages of the assessed innovative solution. Thus, the final results are expressed by a traffic light-type colour code, as defined in the following:

  • Green, not relevant impact on the WWTP;

  • Yellow, potentially moderate impact on the WWTP;

  • Red, potentially crucial aspect. Specific evaluations are mandatory, because final judgement depends on site-specific conditions.

The colour attribution to a given item under evaluation depends on the nature of the item itself, i.e. if it is expressed either as a numerical value (e.g. additional footprint needed for new equipment installation, number of full-scale plants in EU, etc.) or a synthetic statement (e.g. complexity of authorization procedure, public acceptance, etc.). Accordingly, colour attribution is done based on the following criteria:

  • Numerical values (e.g. power consumption): the ratio between the values of innovative and reference scenario is calculated, and two tolerance thresholds are set (minimum and maximum); therefore, three ranges originate: lower than minimum value (green colour is attributed), greater than maximum value (red) and falling in between the extremes (yellow).

  • Synthetic statement (e.g. authorization procedure complexity): the colour is attributed based on a qualitative evaluation (e.g. green is attributed when the authorization procedure for installing the new equipment is not relevant, while red is used for those solutions which require specific authorizations, as in case of air emissions, high-pressure units, risk of explosion, etc.).

As an example, in Table 2, the colour code attribution to the different subitems of the category “Complexity and integration into existing structures” is reported.

Table 2 Complexity and integration into existing structures: single items and colour code
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It is noted that in case of valuable (recoverable) material production, a negative impact (red colour) has to be assigned, since personnel have to manage (displacing, bagging, monitoring, etc.) additional material flows and this represents a drawback from the operative point of view. Of course, advantages will be accounted for in the economic and environmental evaluation. Similarly, although recovering energy from wastes is a positive aspect from many points of view (environmental, economic, etc.), a red colour is assigned when considering the technical point of view, in order to highlight additional operation constraints and duties with respect to current plant management.

For defining the final colour assigned to each category, based on the evaluation of single subitems, a specific algorithm is implemented: firstly, colours are converted into numerical values (conversion factor 1), so that a mean value can be calculated; then, the mean value is reconverted into a colour (conversion factor 2), so as to express the score according to the traffic light-type colour code, which is easy to visualize and gives an immediate meaning of the final outcome. In Table 3, the conversion factors used within the aforementioned algorithm are reported.

Table 3 Conversion factors between colours and numerical values
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Economic assessment

In case of economic assessment, the operation cost/income items listed below can be used for the comparison between reference and the upgraded WWTPs:

  • Personnel;

  • Electric energy consumption;

  • Raw materials and reagents consumption;

  • Disposal of solid/slurry residues;

  • Transportation of solid/slurry residues to the recovery/disposal site;

  • Ordinary maintenance;

  • Income from recovered materials;

  • Income from electric energy sale;

  • Income from thermal energy sale;

  • Income from treatment of MSW organic fraction.

Cost items must be calculated based on data derived from mass balance and energy balance.

The following values can be used for calculation of depreciation:

  • Long service life for concrete structures, pipelines etc., 30 years;

  • Short service life for electro-mechanical device, 8 years;

  • Medium service life for miscellaneous, 15 years.

The economic comparison is carried out by calculating the difference (gap) of operating cost between the new and the reference solution. Thus, a positive gap means that an additional cost must be paid in case the new solution is applied to an existing WWTP.

All items are site specific and depend on local conditions and circumstances. For instance, whenever electric energy to be fed in grid is available, relative income may be strongly increased, in case subsidies for electric energy self-production are recognized.

For this reason, a sensitivity analysis can be performed in order to reveal critical factors. This can be done by calculating variations in the final result due to the assumption of either most favourable or worst economic conditions for all cost items. Their variability range can be defined based on literature data, market conditions, etc.

The sensitivity analysis emphasizes those factors which have the greatest effect on the final result, and this is very helpful when comparing different strategies within a specific context: a careful evaluation of those parameters should therefore be mandatory, so as to obtain reliable results.

In Table 4, as an example, the numerical values (range of variation) of some parameters used for economic calculations in the ROUTES project are reported.

Table 4 Numerical values of some economic items adopted for the economic evaluation in the ROUTES project (sensitivity analysis)
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Both capital and operation costs are calculated based on the average loading conditions, which have been considered as correspondent to actual (design) loading conditions. In case they are expected to change appreciably all along the year, an extra cost has to be considered for equipment and devices oversizing and for taking into account performance loss due to working periods under suboptimal conditions.

Presentation of results: an example

As an example of application of the proposed procedure, the case study of a WWTP with nominal capacity of 70,000 PE and not located in a sensitive area is presented here. The plant is provided with primary sedimentation and sludge anaerobic digestion. This treatment stage is supposed to be overloaded, so that sludge stabilization is poor and requirements for agriculture recovery are not complied with. The proposed upgrading solution consists in installing: (a) a dynamic thickening unit so as to increase the sludge retention time (SRT) in the anaerobic digester, (b) a pasteurization unit for sludge hygienization aimed at allowing agriculture use, (c) a post-aerobic digestion for improving sludge stabilization and (d) a CHP unit for electric energy production. Figure 2 shows the mass balances of both the reference (a) and upgraded (b) plants. The mass balance includes Flow, suspended solids (SS), volatile suspended solids (VSS), COD and total nitrogen (TN). Average daily flows and loadings are calculated. Achieved sludge reduction (56 % on VSS) is clear.

Fig. 2
figure 2

Example of mass balance scheme for the reference (a) and upgraded (b) plants

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In order to give a view of COD transformation pathways all along the process, the overall COD balance can also be represented as in Fig. 3. It shows, respectively, the influent load fraction either oxidized or converted into biogas and the residual amount in effluent and sludge. In the example, it is clear that sludge COD reduction is obtained, thanks to a greater conversion to biogas and to the oxidation in the sludge line.

Fig. 3
figure 3

Example of COD balance

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The different contributions to the overall power consumption are reported in a graph highlighting the main differences between the reference and the innovative scenarios (Fig. 4). In the example, it can be seen that, notwithstanding the greater power requirement of the new solution, the net consumption is reduced, thanks to the amount of electric energy produced in the CHP unit. It has to be noted that the reference plant is assumed not to be provided with a CHP unit.

Fig. 4
figure 4

Example of energy consumption inventory

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The Theoretical Process Energy Balance is represented in Fig. 5: the best performance corresponds to the lowest value of the “Global balance”. In this example, both plants have an advantageous global balance (theoretical power production exceeds aeration power need); the new solution is even more favorable, thanks to the increased efficiency of anaerobic digestion.

Fig. 5
figure 5

Example of graph showing the Theoretical Process Energy Balance

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Table 5 illustrates synthetically the results of technical assessment. As described above, each of the shown aspects is the combination of several items: the short comments reported close to critical factors explain the main associated problems. It can be seen that the global evaluation is rather positive.

Table 5 Example of result presentation of technical assessment
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As concerns the economic assessment, the main result presentation is given by a bar graph (see Fig. 6), which depicts the cost gap between the new and the reference scenario. It is expressed in Euro/(PE y) and represents the difference between the cost of the innovative solution and that of the reference one. A positive value, therefore, means that the new solution is more expensive. The cost gap is calculated for each cost item (depreciation, maintenance, personnel, etc.), and the “total cost gap” is the sum of all items. The results are given as a range of values rather than a single number, because each item is calculated according to both the most favorable and the worst economic conditions so as to highlight the possible range of variability depending on the local circumstances (sensitivity analysis).

Fig. 6
figure 6

Example of bar graph showing the result of an economic assessment

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It can be seen that the total cost gap ranges between a strongly negative value (the new solution is cheaper) and a slightly positive value (the new solution is more expensive). This means that economic sustainability depends on the local conditions, but it is more likely that it is satisfied.

The two items which have the greatest impact on the final economic outcome are the following:

  • Sludge disposal cost;

  • Power feed-in income.

The main conclusions of the techno-economic assessment can be finally reported in a summary table, as in the example of Table 6, where cost gap is expressed as a percentage with respect to operating cost of the corresponding reference scenario.

Table 6 Example of summary of relevant aspects
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Results uncertainty and interpretation

In order to give a proper interpretation to the results of the proposed assessment procedure, some points must be noted:

  1. 1.

    It is very important to assess the data reliability. In particular for the upgraded plant, the reliability of the experimental results depends on both the experiment scale (i.e. bench-, pilot- or full scale), and the substrates characteristics (i.e. real or simulated wastewater).

  2. 2.

    Results are only valid for the assessed plant, which has specific characteristics of process configuration, influent quality and load, required effluent standards, and unique operative issues (e.g. overloading of anaerobic digester, poor quality of the sludge for agriculture application, high nutrient concentration in the reject water from the sludge line, etc.). As the specific circumstances and constraints can be very different for different sites and can modify the role of considered parameters, leading to different final results, the latter cannot be extended to other case studies.

  3. 3.

    The assessment procedure requires many calculations (biological process design, mass balance, energy balance, cost estimation, etc.). A certain degree of uncertainty is therefore inherent in the procedure. This has to be taken into account when comparing the reference and the innovative solutions: slight differences are not relevant.

  4. 4.

    Capital cost for upgrading can vary remarkably in real situations depending on many factor and constraints.

  5. 5.

    Both capital and operation costs are calculated based on the average loading conditions, which have been considered as correspondent to actual (design) loading conditions. In case these are expected to change appreciably all along the year, an extra cost has to be considered for equipment and devices oversizing and for performance loss due to working periods under suboptimal conditions. In other words, the ratio between plant capacity and actual loading has a great influence on final result. This kind of evaluation must be included when comparing different solutions in real applications.

Conclusions

The results of techno-economic-environmental evaluations of complex systems (like those adopted in water and waste management) are always site-specific dependent. Therefore, novel tools for the evaluation of potential technologies and management strategies are always helpful and welcome.

A new integrated assessment methodology was proposed within the ROUTES project for evaluating the level of feasibility of innovative solutions aimed at improving sewage sludge management in municipal WWTPs. The methodology revealed to be flexible and detailed enough to describe situations which can differ in terms of plant size and configuration and in terms of complexity of the upgrading intervention. It could be an effective tool for helping stakeholders in the challenge of finding the proper sludge management solutions in real situations.

One strength of the procedure is that its application emphasizes not only the economic aspects but also relevant technical features, including public acceptance, reliability and complexity of integration and authorization, which have been rarely captured in other approaches.

As in all modeling processes, the reliability of results depends strictly on the reliability of input data. Consequently, data should undergo a careful preliminary selection by the user, particularly when new technologies or solutions are assessed. In addition, the proposed procedure includes an extended sensitivity analysis that allows to evidence critical technical or economic aspects, thus suggesting where to focus and concentrate resources for deeper evaluation of the proposed plant upgrade.

The environmental impact assessment is another important factor for deciding about the plant upgrading and should be always performed, in conjunction with the technical-economic assessment, for a global overview of benefits and drawbacks of the examined solution. The methodology proposed in this paper also provides a suitable set of input data for the subsequent LCA evaluation, for a full technical, economic and environmental assessment.