Multi criteria evaluation of a sustainable alkali

XXIV Summer School “Francesco Turco” – Industrial Systems Engineering

Multi criteria evaluation of a sustainable alkali-activated concrete

Sciortino R.*, Micale R.*, Saeli M.**, La Scalia G.*

* Department of Engineering, University of Palermo ,Viale delle scienze, Bld 8, 90128, Palermo, Italy ([email protected], [email protected], [email protected])

** Department of Materials and Ceramics Engineering, Aveiro Institute of Materials, University of Aveiro, Campus Universitario de Santiago, 3810-193, Aveiro, Portugal ([email protected])

** Department of Materials and Ceramics Engineering, Aveiro Institute of Materials, University of Aveiro, Campus

Abstract: The construction industry is one of the most polluting sectors worldwide. In order to reduce the environmental footprint, novel green materials and processes are being considered by valorising and reusing wastes. This work investigates the production of a novel and sustainable geopolymeric concrete reusing biomass fly ash from kraft paper-pulp industry. In particular, this paper aims to evaluate the best combination of the aggregate granulometry used in the material production. For this purpose, the multicriteria method TOPSIS has been implemented in order to obtain a rank of the concrete specimens. In this approach only mechanical aspects have been considered and future developments will include criteria related on the buildings environmental conditions. The environmental conditions during in site exposure could in fact vary the performance achieved by the materials in laboratory test and GIS software could be a useful tool to combine information about quality material components and environmental condition.

Keywords: Sustainability; Topsis Method; Biomass fly ash; Geopolymer.

1. Introduction

The massive exploitation of non-renewable raw materials and the enormous generation of solid wastes and greenhouse gases make the present industrial system highly unsustainable. Therefore, a worldwide increasing pressure to adopt proper industrial waste management is generating a growing interest in looking for efficient alternatives to traditional disposal systems, such as landfill (European Parliament, 1999). Among the others, construction is recognized to be one of the most unsustainable industrial sector, especially in the developing countries. In this scenario, particularly critical is the cement manufacture, comprising the associated materials (i.e. the aggregates) that yearly release around 0.7–1.1 ton of CO2 for every produced ton of Ordinary Portland Cement (OPC) (Schneider et al., 2011). Nevertheless, cement use is unavoidable due to the unequivocal need of new structures and infrastructures. Consequently, there is an extraordinary necessity to develop alternative materials and cost-effective manufacture processes that can reduce the unsustainability associated with construction. The worldwide large amount of industrial solid wastes maybe be valorised and reused in many by-products and system. Many have been investigated so far, demonstrating interesting recycling potentials. Also the construction industry is recently employed a

lot of energy in developing novel greener materials and systems to overcome the unsustainability associated with its massive activity. For instance, fly and bottom ash, blast furnace slag, silica fume, and other solid wastes can be recycled as partial replacement for OPC (Berndt, 2009). Also biomass wastes could find interesting recycling potentials. The reuse of biomass waste such as wood fibre or rice husk ash were investigated to produce lightweight concrete blocks as a sustainable building material (Torkaman et al., 2014). Also food wastes were under consideration for high-functionalised building materials (Saeli et al., 2018-a). Several studies have been conducted in the last decade on the use of fly ash, i.e. coal fly ash, to manufacture more sustainable and performing concretes (Ondova et al., 2013; Oliveira et al., 2017). Among the recently most popular green materials, geopolymers (GP) are playing a leading role worldwide. GP are inorganic alkali-activated binders made of a reactive solid alumina-silicate source, commonly metakaolin (MK), that interacts with an alkaline solution to form a stable gel (Davidovits, 1979). GP are considered a valid and sustainable alternative to OPC showing properties suitable for many applications in construction. Biomass fly ash (BFA) from the paper-pulp industry arose recent interest for the manufacture of GP-binders to

314


partially substitute the MK for greener construction materials (Saeli et al., 2017 and 2019). In this study, we analysed eight different samples of GP-concrete manufactured using the developed GP- binder and stone as aggregate in different grain sizes (EN 933-2:1995). The produced concretes were fully characterized, with a particular focus on the mechanical properties, namely uniaxial compressive test (UCS). Subsequently, a Multi Criteria Decision Making (MCDM) technique was performed basing on a set of quantitative criteria. In particular, this paper aims at evaluating the best combination of the aggregate grain size. Environmental conditions during in site exposure could be included in future developments using GIS (Geographic Information System) software that could be a useful tool to predict the real material service life (Sanchez-Silva & Rosowsky, 2008 Lacasse & Sjostrom, 2004; Hovde, 2005; Mastrucci et al., 2017). Several multi-criteria models and approaches are available in literature. In particular, Velasquez and Hester (2013) presented a literature review of the most common MCDM methods, highlighting their strengths and weaknesses. However, the selection of the most suitable method is not easy and depends on several factors (Simanaviciene & Ustinovicius, 2012) such as, for example, the specific considered problem, the objectives of the decision maker, the uncertainty and vagueness of data and information, the accessibility of the approach for users, etc. (Micale et al., 2017). Technique Ordered Preference by Similarity to the Ideal Solution (TOPSIS), one of the most widely used MCDM methods in decision support systems (Lai et al., 1994), was here implemented as the rank obtained with this methodology strongly depends on the relative importance of the used evaluation criteria. The remainder of this paper is organized as follows: Section 2 describes the materials and methods implemented in this study; Section 3 shows the results obtained by an experimental test and proposes a ranking of the different samples. Lastly, Section 4 concludes the paper with a short discussion on the proposed methodology and an outlook into on-going research work.

2. Materials and methods

2.1 Materials

In this study, the GP-binder was designed using a mixture of BFA (70 wt.%) and MK, Argical™ by Univar®, (30 wt.%) as a solid source of alumina and silica. The used BFA is produced by a Portuguese paper-pulp industry exploiting the Kraft digestion.

More particularly, BFA are produced in the biomass boiler employed for energy production at mill site and collected at the electrostatic precipitator as waste. The alkaline activation was achieved by using a solution of commercial sodium silicate and sodium hydroxide (10 M). The GP-binder was manufactured in accordance to previous studies (Saeli et al., 2017 and 2019). Commercial round gravel stones were only mechanically sieved to set the desired granulometries according to EN 933-2:2015. 2.2 Manufacture process GP-concrete specimens were prepared according to EN 998-2:2016 adapting the common procedure for traditional construction materials to the novel nature of the GP-products. The material manufacture consisted in: a) dry hand mixing to ensure a uniform blend of MK and BFA; b) homogenization of sodium hydroxide and silicate; c) mixture of the alkaline solution with the solid precursors; d) addition of the aggregate and mix to ensure homogeneity; e) pouring the fresh slurry into standard metallic moulds (40x40x160 mm) and vibrating for 2 mins on a vibrating table to grant compactness and remove any entrained air; f) seal the moulds with a plastic film and let the specimens harden for 24 hrs at ambient conditions (20°C, 65% RH), and g) unsealed and demould the hardened samples, and curing at ambient conditions until testing. In figure 1 the flow chart of mortar production is reported.

Figure 1: Concrete production process

Eight samples using five gravel stone aggregates of different granulometry (figure 2) were produced to evaluate the material properties. The granulometric range for the considered samples is shown in table 1.

Table 1: Granulometric range

Samples a1 a2 a3 a4 a5 a6 a7 a8

metakaolin BFA alkaline activator

geopolymeric binder coarse aggregate

geopolymeric concrete

315


Range [mm]

1-2 2-4 4-8 8-12,5 1-12,5 2-4 + 1-

2 4-8 + 1-

2 8-12,5 + 1-2

Figure 2: Used stone gravels: 1-2 mm, 2-4 mm, 4-8 mm, 8-12.5 mm, 1-12.5 mm(from left to right).

Figure 3 shows some samples section.

Figure 3: Sections of selected concrete specimens.

2.3 Evaluation criteria

The evaluation criteria for mortar characterization are described below: Workability (W) [cm], estimated by flow table test, according to EN 1015-3:1999. This criterion score can be represented by means of a trapezoidal membership function in which the maximum score (1) is achieved in the range of value 16-22 cm. While in the intervals [10-16[ and ]22-30] the score is calculated with the following equations:

(1)

(2) For external values of the above-mentioned intervals, the score is equal to 0. Bulk Density (BD) [kg/m3], calculated as the average from three samples. This criterion score has to be maximized and thus there is an increasing preference versus. Water Absorption by immersion (WA) [%], determined by the Archimedes principle (weight

variation, 'P/P %) by immersing the samples in distilled water for 24 h after being dried to constant mass at 60°C in a conventional oven. Water absorption has to be minimized and thus it is characterized by a decreasing preference versus. Uniaxial Compressive Strength (UCS) [MPa] has been determined according to EN 998-2:2016 and EN 1015-11:1999. A universal testing machine (Shimadzu, AG-25TA), provided with a 250 kN load cell, running at 0.5 mm/min displacement rate, was used. The mean values are obtained from three tests randomly taken from the sample batch. This criterion score has to be maximized and thus there is an increasing preference versus. Axial Strain (AS) [%], quotient of the displacement at maximum strength and the original sample's length. This criterion has to be minimized and thus it is characterized by a decreasing preference versus. 2.4 Topsis techniques

The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a MCDM method developed by Hwang and Yoon (1981) in order to choose the alternative characterized by the shortest/longest geometric distance from a positive/negative ideal solution. TOPSIS method is a useful tool in dealing problems in different application areas such as supply chain management (Li et al., 2019), logistic (Govindan et al., 2019), energy management (Perera et al., 2018), transportation (de Aquino et al., 2019), manufacturing systems (Tigane et al., 2019), health management (Araujo et al., 2018), etc.. This method presents different advantages: simplicity, rationality, compressibility, intuitive and clear logic that represent the rationale of human choice, good computational efficiency and ability to measure the relative performance for each alternative in a simple mathematical form (Zadeh Sarraf et al., 2013; Govindan et al., 2012). Based on this consideration (because of these advantage) the TOPSIS method was chosen in order to rank the different alternatives. The input data necessary to implement the method is a decision matrix Gij = [gij]nm in which the n rows are the alternatives ai, (i = 1, …, n) and the m columns are the evaluation criteria cj (j = 1, …, m). The generic element gij of this matrix represents the score of the alternative ai with respect to the cj criterion. The decision matrix of the case study considered is shown in table 2:

Table 2: Decision matrix

Gij CS BD W WA AS

316


a1 20.30 1999 1.00 10.38 3.45 a2 18.89 1913 0.97 11.30 4.02 a3 24.24 1973 1.00 11.34 3.12 a4 13.57 2011 0.81 10.78 3.53 a5 23.86 1998 0.72 11.81 2.98 a6 21.39 1926 0.90 12.14 3.47 a7 26.62 1967 0.69 12.32 3.21 a8 22.09 1941 0.83 11.27 4.40

The TOPSIS method is deployed by means of the following steps:

step 1 - calculation of the normalized decision matrix, in which the generic element zij is obtained by means of the following equation (3):

(3)

step 2 - calculation of the weighted normalized decision matrix, in which the generic element uij is obtained multiplying each element of the normalized decision matrix by the weights of the corresponding criteria wj (j = 1, …, m) according to the following equation (4):

(4) step 3 - calculation of the positive ideal solution Azimuth (A*) and negative ideal solution Nadir (A-):

(5)

(6)

Where I’ and I” are associated with benefit and cost criteria respectively.

step 4 – calculation of the geometric distance between the alternatives and the positive/negative ideal solution:

(7)

(8)

step 5 – evaluation of the relative closeness coefficient obtained combining the two distances:

(9)

step 6 – ranking of the alternatives according to Ci* in descending order.

2.5 The Delphi method

In this work the weights of the criteria were assessed by a panel of three experts thought the Delphi technique (Delbecq, 1975). The weights obtained are reported in table 3:

Table 3: Criteria weights

Criteria CS BD W WA AS Weights 0.3 0.1 0.2 0.1 0.3

The aim of the Delphi method is to combine the opinion of a group of experts in order to obtain their consensus on a complex problem (Chan et al., 2001). Since its development by U.S. Rand Corporation in 1950-1960, the Delphi method has been broadly utilized in various fields of study (dee Jesus et al. 2019; Giallanza et al., 2017; Jahanshahi et al., 2019). The classical Delphi method uses a series of anonymous questionnaires to reach a consensus and involves a series of rounds. The anonymity of responses to questionnaires is a fundamental pre-requisite that avoids prejudices due to dominant positions, status or personality. The panel of experts has to be composed of people competent within the specialized area of knowledge related to the problem considered. In this study three experts were selected (a material scientist, expert in the area of materials processing; a construction technologist, expert in novel materials and technologies; an architectural engineer, expert in the application of novel materials) that have the appropriate knowledge and the expertise in the field of innovative materials for constructions. This panel of experts has been iteratively queried by means of questionnaires until the agreement was achieved. The questionnaires were sent by e-mail to all experts. The first questionnaire comprised general questions to give to the experts the opportunity to reflect on the topics of the questionnaire itself. The answers were

317


expressed in a qualitative way and the experts had the possibility to add comments on the treated topic. After this round a second questionnaire was structured in which an anonymous summary of the experts’ judgment and the comments they provided were reported. The experts were encouraged to revise their answers considering the replies of the other members of the panel. In this second step the answers were expressed in a quantitative way. A third questionnaire was formulated in which the experts gave a quantitative judgment on the basis of the results of the second questionnaire. In this last questionnaire a stabilization of judgments was reached then this was the finally step of the method.

3. Results and discussion

Afterwards the weighted normalized decision matrix and the Azimuth and Nadir values were calculated as shown in table 4: Table 4: Weighted normalized decision matrix, A* and A-

CS BD W WA AS a1 0.099 0.036 0.081 0.032 0.103 a2 0.092 0.034 0.079 0.035 0.120 a3 0.119 0.035 0.081 0.035 0.093 a4 0,066 0.036 0.066 0.033 0.105 a5 0.117 0.036 0.058 0.037 0.089 a6 0.105 0.035 0.073 0.038 0.104 a7 0.130 0.035 0.056 0.038 0.096 a8 0.108 0.035 0.067 0.035 0.131 A* 0.130 0.036 0.081 0.032 0.089 A- 0.066 0.034 0.056 0.038 0.131

Finally, the geometric distance between the alternatives and the positive/negative ideal solutions were determined though the equation (7) and (8) and the relative closeness coefficient was evaluated with the equation (9). The final ranking is reported in table 5:

Table 5: Final ranking

Ranking C*

a3 0.845 a7 0.730 a5 0.710 a6 0.618 a1 0.599 a8 0.464 a2 0.427 a4 0.295

Results show that the best solution is the mortar in which the aggregate used has a granulometry range [4-8] mm. The samples a7 and a5 have obtained almost equivalent score. The worst solution is characterized by the highest aggregate size.

4. Conclusions

This work investigated the theoretical implementation of novel sustainable GP-concrete designed for applications in constructions, such as masonry. Eight samples containing stone gravel aggregate with different granulometries were produced and their characteristics were evaluated by means of a set of established criteria. The relative importance of each criterion was assessed by means of the Delphi technique. Finally, the rank of the considered specimens has been obtained using the multi criteria approach TOPSIS.

Results showed that the best solution is the mortar in which the used aggregate has a median granulometry range whereas the worst solution is characterized by the largest aggregate size. Future researches could consider the intrinsic uncertainty of the score measurements through the implementation of the fuzzy approach. Finally, an economic analysis is mandatory in order to establish the feasibility of the sustainable mortars production process.

ISO 15686 provides a methodology for forecasting service life of materials based on factors that could be easily available through the use of the GIS systems for data management. Future developments could include the implementation of a GIS System for the evaluation of the durability of materials and components in existing building contexts and the characterization of environmental degradation factors, which could be added in the multi-criteria evaluation. Verification of the actual state of the building material against empirical data from a sample of buildings will be addressed in a future step.

References

Araujo, C.A.S, Wanke, P. and Siqueira, M.M., (2018). A performance analysis of Brazilian public health: TOPSIS and neural networks application, International Journal of Productivity and Performance Management, 67(9), pp. 1526-1549.

Berndt M.L., (2009). Properties of sustainable concrete containing fly ash, slag and recycled concrete aggregate, Construction and Building Materials, 23 2606–2613.

318


Chan, A. P. C., Yung, E. H. K., Lam, P. T. I., Tam, C. M. and Cheung, S. O. (2001). Application of Delphi method in selection of procurement systems for construction projects, Construction Management and Economics, 19(7): 699– 718

CEN TC 350 – Sustainability of construction works

de Aquino, J.T., de Melo, F.J.C., Jeronimo, T.B. and de Medeiros, D.D. (2019). Evaluation of Quality in Public Transport Services: The Use of Quality Dimensions as an Input for Fuzzy TOPSIS, International Journal of fuzzy systems, 21(1), pp. 176-193.

de Jesus, A., Antunes, P. Santos, R., Mendonca, S. (2019). Eco-innovation pathways to a circular economy: Envisioning priorities through a Delphi approach, Journal of Cleaner Production, 228, pp. 1494-1513.

EN 933-2:1995, Tests for geometrical properties of aggregates - Part 2: Determination of particle size distribution - Test sieves, nominal size of apertures, 1995. European Committee for Standardization.

EN 1015-11:1999, Methods of Test for Mortar for Masonary - Part 11: Determination of Flexural and Compressive Strength of Hardened Mortar, 1999. European Committee for Standardization.

EN 1015-18:2002, Methods of Test for Mortar for Masonry - Part 18: Determination of Water Absorption Coefficient Due to Capillary Action of Hardened Mortar, 2002. European Committee for Standardization.

EN 1015-3:1999, 1999. Methods of Test for Mortar for Masonry. Determination of Consistence of Fresh Mortar (By Flow Table). European Committee for Standardization.

EN 998-2:2016, Specification for Mortar for Masonry - Part 2: Masonry Mortar, 2016. European Committee for Standardization.

European Parliament, Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste.

de la Villa, R. V., Fri ́as, M., de Rojas, M. I. S., Vegas, I. and Garci ́a, R. (2007). Mineralogical and morphological changes of calcined paper sludge at different temperatures and retention in furnace, Applied Clay Science, 36(4), 279-286.

Delbecq, A.L., Van de Ven, A.H., and Gustafson, D.H. (1975). Group techniques for program planning: a guide to nominal group and Delphi processes. Scott, Foresmann, Glenview, IL.

Davidovits, J., (1979). Synthesis of new high temperature geo-polymers for reinforced plastics/composites, Society of Plastic Engineers, Brookfield Center, 151–54.

Giallanza, A., Enea, M., Micale, R., La Scalia, G., (2017). Evaluation of new functional pasta using TOPSIS methodology, Proceedings of XXII Summer School “Francesco Turco”, 13-15 September, Palermo, Italy, 2017, pp. 341-347.

Govindan, K., Khodaverdi, R. and Jafarian, A. (2012). A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach, Journal of Cleaner Production, pp. 1-10.

Govindan, K., Agarwal, V., Darbari, J.D. and Jha, P.C., (2019). An integrated decision making model for the selection of sustainable forward and reverse logistic providers, Annals of Operations research, 273 (1-2), pp. 607-650.

Hovde, P.J. (2005). The Factor Method – a simple tool to service life estimation. 10th DBMC International Conference on Durability of Building Materials and Components, Lyon, France, pp. 522-529

Hwang, C.L. and Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Berlin Heidelberg: Springer.

ISO 15686 Buildings and constructed assets - Service life planning.

Jahanshahi, A., Kamali, M., Khalaj, M. and Khodaparast, Z., (2019). Delphi-based prioritization of economic criteria for development of wave and tidal energy technologies, Energy, pp 819-827.

Lacasse, M. and Sjöström, C (2004). Recent advances in methods for service life prediction of building materials and components – an overview. Proceedings, CIB World Building Congress, Toronto, Canada.

Lai, Y.J., Liu, T.Y. and Hwang, C.L. (1994). TOPSIS for MODM, Eur J Oper Res, 76(3):486– 500.

Li, J., Fang, H. and Song, W. (2019). Sustainable supplier selection based on SSCM practices: A rough cloud TOPSIS approach, Journal of Cleaner Production, 222, 606-621.

Kylili, A., Fokaides, P.A., (2017). Policy trends for the sustainability assessment of construction materials: a review. Sustain. Cities Soc. 35, 280-288.

Martin Hirschnitz-Garbers, A.R.T., Gradmann, A. and Srebotnjak, T., (2016). Key drivers for unsustainable resource use - categories, effects and policy pointers, J. Clean. Prod., 132, 15-31.

Mastrucci A., Marvuglia A., Popovici E., Leopold U., Benetto E., 2017. Geospatial characterization of building material stocks for the life cycle assessment of end-of-life scenarios at the urban scale, Resources, Conservation and Recycling, Volume 123, Pages 54-66.

Micale, R., Giallanza, A., Russo, G. and La Scalia, G. (2017). Selection of a Sustainable Functional Pasta Enriched with Opuntia Using ELECTRE III Methodology, Sustainability, 9 (6), Article Number 885.

Oliveiraa, K.A., Naza ́riob, B.I., Novaes de Oliveiraa A.P., Hotzaa, D. and Raupp-Pereiraa, F., (2017). Industrial Wastes as Alternative Mineral Addition in Portland

319


Cement and as Aggregate in Coating Mortars, Materials Research, 20(Suppl. 2): 358-364.

Ondova, M., Stevulova, N. and Meciarova, L., (2013). The Potential of Higher Share of Fly Ash as Cement Replacement in the Concrete Pavement, Procedia Engineering, Volume 65, Pages 45-50.

Perera, P., Hewage, K., Alam, M.S., Mèrida, W. and Sadiq, R. (2018). Scenario-based economic and environmental analysis of clean energy incentives for households in Canada: Multi criteria decision making approach, Journal of Cleaner Production, 198, pp. 170-186.

Saeli, M., Novais, R.M., Seabra, M.P. and Labrincha, J.A., (2017). Mix design and mechanical performance of geopolymer binder for sustainable construction and building material, IOP Conf. Ser. Mater. Sci. Eng. 264, 012002.

Saeli, M., Piccirillo C., Tobaldi DM., Binions R., Castro P. and Pullar RC., (2018a). A sustainable replacement for TiO2 in photocatalyst construction materials: hydroxyapatite-based photocatalytic additives from the valorisation of food wastes of marine origin, Journal of Cleaner Production, 193, pp. 115-127.

Saeli, M., Novais, R.M., Seabra, M.P. and Labrincha, J.A., (2018b). Green geopolymeric concrete using grits for applications in construction, Materials Letters, Volume 233, Pages 94-97.

Saeli, M., Tobaldi, D.M., Seabra, M.P. and Labrincha JA., (2019). Mix design and mechanical performance of geopolymeric binders and mortars using biomass fly ash and alkaline effluent from paper-pulp industry, Journal of Cleaner Production ,208, 1188-1197.

Seyyedalipour, S.F., Yousefi Kebria. D. and Dehestani M., (2015). Effects of recycled paperboard mill wastes on the properties of non-load-bearing concrete, Int. J. Environ. Sci. Technol., 12, 3627–3634.

Schneider, M., Romer, M., Tschudin, M. and Bolio H., (2011). Sustainable cement production – present and future, Cement and Concrete Research, 41(7), 642–50.

Tigane, M., Dahane, M. and Boudhar, M. (2019). Multiobjective approach for deteriorating jobs scheduling for a sustainable manufacturing system, International Journal of Advanced Manufacturing Technology, 101(5-8), pp. 1939-1957.

Torkaman, J., Ashori, A. and Momtazi, S.A. (2014). Using wood fiber waste, rice husk ash, and limestone powder waste as cement replacement materials for lightweight concrete blocks, Constr Build Mater, 50, 432–436 .

Qian, C., (2017). Sustainable construction methods and processes. Encyclopedia of sustainable technologies. In: Reference Module in Earth Systems and Environmental Sciences, pp. 321-329, 2017.

Sanchez-Silva, M. and Rosowsky, D. (2008). Biodeterioration of construction materials: state of

the art and future challenges, J Mater Civil Eng., 20, 352–365.

Simanaviciene, R. and Ustinovicius, L. A. (2012). New Approach to Assessing the Biases of Decisions Based on Multiple Attribute Decision Making Methods, Electron. Electr. Eng., 117, 29–32.

Velasquez, M. and Hester, T. (2013). An Analysis of Multi-Criteria Decision Making Methods, Int. J. Oper. Res., 10, 56–66.

Zadeh Sarraf, A., Mohaghar, A. and Bazargani, H. (2013). Developing TOPSIS method using statistical normalization for selecting Knowledge management strategies, Journal of Industrial Engineering and Management, 6(4), 860-875.

320

Documents

Multi criteria evaluation of a sustainable alkali