v. 35 n. 2 (2022): Revista ION
Artigos

Avaliação técnico-econômica de uma proposta de estação de tratamento de efluentes de cromo

Amaury Pérez Sánchez
University of Camagüey
Marisabel Sánchez González
University of Camagüey

Publicado 2022-12-02

Palavras-chave

  • Chromium,
  • Avaliação econômica,
  • Simulação de processos,
  • Tratamento de águas residuais

Como Citar

Pérez Sánchez, A., & Sánchez González, M. . (2022). Avaliação técnico-econômica de uma proposta de estação de tratamento de efluentes de cromo. REVISTA ION, 35(2), 33–48. https://doi.org/10.18273/revion.v35n2-2022003

Resumo

As estações de tratamento de águas residuais são sistemas que, se operados corretamente, podem ajudar a saúde da indústria e do meio ambiente. No presente trabalho, foi realizada a avaliação técnico-econômica de uma proposta de estação de tratamento de efluentes de cromo com capacidade de processamento de 9 t de efluente por lote, a fim de determinar seus principais parâmetros de rentabilidade, utilizando o simulador SuperPro Designer® v. 10. Cerca de 6.959,90 L/lote de água tratada são gerados, enquanto um investimento de capital total de US $ 3.549 milhões e um capital fixo direto de US $ 3.222 milhões são necessários. O item que mais influencia nos custos operacionais anuais é o dos custos dependentes da instalação (US $ 345.000/ano) enquanto o reagente que mais influencia nos custos anuais de consumo de materiais é o cloreto férrico (US $ 56.805/ano). Houve um custo unitário de processamento de US $ 0,22/kg, um lucro líquido anual de US $ 486.000 e um retorno sobre o investimento de 22,16%. Os valores obtidos a partir dos indicadores Valor Presente Líquido (US $ 3.361.000), Taxa Interna de Retorno (29,61%) e Período de Retorno do Investimento (4,51 anos) permitem estabelecer que a proposta é rentável nas condições econômicas atuais em Cuba.

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Referências

  1. Rajasulochana P, Preethy V. Comparison on efficiency of various techniques in treatment of waste and sewage water – A comprehensive review. Resource-Efficient Technologies. 2016;2(4):175-84. https://doi.org/10.1016/j.reffit.2016.09.004
  2. Zakharov Y, Bondareva L. Simulation of Domestic and Industrial Wastewater Disposal in Flooded Mine Workings. Procedia Engineering. 2015;117:389-96. doi.org/10.1016/j.proeng.2015.08.183
  3. Chandraseagar S, Abdulrazik AH, Abdulrahman SN, Abdaziz, MA. Aspen Plus simulation and optimization of industrial spent caustic wastewater treatment by wet oxidation method. IOP Conf. Series: Materials Science and Engineering. 2019;702:012011. doi.org/10.1088/1757-899X/702/1/012011
  4. Jeon C, Nah IW, Hwang KY. Adsorption of heavy metals using magnetically modified alginic acid. Hydrometallurgy. 2007;86(3):140-46. doi.org/10.1016/j.hydromet.2006.11.010
  5. Gupta VK, Chandra R, Tyagi I, Verma M. Removal of hexavalent chromium ions using CuO nanoparticles for water purification applications. Journal of Colloid and Interface Science. 2016;478:54-62. doi.org/10.1016/j.jcis.2016.05.064
  6. Wang X, Wei Y, Wang S, Chen L. Red-to-blue colorimetric detection of chromium via Cr (III)-citrate chelating based on Tween 20-stabilized gold nanoparticles. Colloids and Surfaces A: Physicochemical and Engineering Aspects. 2015;472:57-62. doi.org/10.1016/j.colsurfa.2015.02.033
  7. Ai T, Jiang X, Liu Q. Chromium removal from industrial wastewater using Phyllostachys pubescens biomass loaded Cu-S nanospheres. Open Chem. 2018;16:842-52. doi.org/10.1515/chem-2018-0073
  8. Jasim NA. The design for wastewater treatment plant (WWTP) with GPS X modelling. Cogent Engineering. 2020; 7(1): 1723782. doi.org/10.1080/23311916.2020.1723782
  9. Janssen PMJ, Meinema K, Roest HF. Biological Phosphorus Removal: Manual for Design and Operation. United Kingdom: STOWA; 2002.
  10. Davis ML, Cornwell DA. Introduction to environmental engineering. USA: McGraw-Hill; 2008.
  11. Asami H, Golabi M, Albaji M. Simulation of the biochemical and chemical oxygen demand and total suspended solids in wastewater treatment plants: Data-mining approach. Journal of Cleaner Production, 2021;296:126533. doi.org/10.1016/j.jclepro.2021.126533
  12. Gontarski CA, Rodrigues PR, Mori M, Prenem LF. Simulation of an industrial wastewater treatment plant using artificial neural networks. Computers and Chemical Engineering. 2000;24:1719-23. doi.org/10.1016/S0098-1354(00)00449-X
  13. Oliveira-Esquerre KP, Mori M, Bruns RE. Simulation of an industrial wastewater treatment plant using Artificial Neural Networks and Principal Components Analysis. Brazilian Journal of Chemical Engineering. 2002;19(4):365-70. doi.org/10.1590/S0104-66322002000400002
  14. Banaei FK, Zinatizadeh AAL, Mesgara M, Salari Z. Dynamic Performance Analysis and Simulation of a Full Scale Activated Sludge System Treating an Industrial Wastewater Using Artificial Neural Network. International Journal of Engineering. (2013);26(5):465-72. doi.org/10.5829/idosi.ije.2013.26.05b.02
  15. Moragaspitiya C, Rajapakse J, Senadeera W, Ali I. Simulation of Dynamic Behaviour of a Biological Wastewater Treatment Plant in South East Queensland, Australia using Bio-Win Software. Engineering Journal. 2017;21(3):1-22. doi.org/10.4186/ej.2017.21.3.1
  16. Młynski D, Bugajski P, Młynska A. Application of the Mathematical Simulation Methods for the Assessment of the Wastewater Treatment Plant Operation Work Reliability. Water. 2019;11:873. doi.org/10.3390/w11050873
  17. Viswanathan MB, Raman DR, Rosentrater KA, Shanks BH. A Technoeconomic Platform for Early-Stage Process Design and Cost Estimation of Joint Fermentative-Catalytic Bioprocessing. Processes. 2020;8:229. doi.org/10.3390/pr8020229
  18. Canizales L, Rojas F, Pizarro CA, Caicedo-Ortega NH, Villegas-Torres MF. SuperPro Designer®, User-Oriented Software Used for Analyzing the Techno-Economic Feasibility of Electrical Energy Generation from Sugarcane Vinasse in Colombia. Processes. 2020;8:1180. doi.org/10.3390/pr8091180
  19. Ernst S, Garro OA, Winkler S, Venkataraman G, Langer R, Cooney CL, Sasisekharan R. Process Simulation for Recombinant Protein Production: Cost Estimation and Sensitivity Analysis for Heparinase I Expressed in Escherichia coli. Biotechnology and Bioengineering. 1997; 53(6): 575-82. doi.org/10.1002(SICI)1097-0290(19970320)53:6<575::AIDBIT5>3.0.CO;2-J
  20. Flora JRV, McAnally AS, Petrides D. Treatment plant instructional modules based on SuperPro Designer® v.2.7. Environmental Modelling & Software. 1999; 14: 69-80. doi.org/10.1016/S1364-8152(98)00059-0
  21. Kotoupas A, Rigas F, Chalaris M. Computer-aided process design, economic evaluation and environmental impact assessment for treatment of cheese whey wastewater. Desalination. 2007; 213: 238-52. doi.org/10.1016/j.desal.2006.03.611
  22. Lisichkov K, Kuvendziev S, Ljatifi M, Zhezhov G, Marinkovski M. Analysis of the actuivated sludge wastewater treatment process by application of a process simulator. Natura Montenegrina. 2013; 13(3-4): 995-1002.
  23. Singureanu C, Woinaroschy A. Simulation of Bardenpho wastewater treatment process for nitrogen removal using SuperPro Designer simulator. U.P.B. Sci. Bull., Series B. 2017; 79(4): 41-50.
  24. Barreto SI. Uso de la simulación con SuperPro Designer en las prácticas de laboratorio de tratamiento de agua y residuales. Transformación. 2017; 13(1): 130-38.
  25. Broberg K. Modelling of a sulfate reducing and metal recovery process, for application within treatment of industrial wastewater Simulation in SuperPro Designer v. 10.1 and Matlab R2014b (Master Thesis). Lund, Sweden: Lund University; 2019.
  26. Lok X, Chan YJ, Foo DCY. Simulation and optimisation of full-scale palm oil mill effluent (POME) treatment plant with biogas production. Journal of Water Process Engineering. 2020;38:101558. doi.org/10.1016/j.jwpe.2020.101558
  27. Ma R, Chong CH, Foo DCY. Design and Optimisation of Wastewater Treatment Plant for the Poultry Industry. MATEC Web of Conferences. 2021;333:12003. doi.org/10.1051/matecconf/202133312003
  28. Inayat A, Ahmed SF, Djavanroodi F, Al-Ali F, Alsallani M, Mangoosh S. Process Simulation and Optimization of Anaerobic Co-Digestion. Frontiers in Energy Research. 2021;9:764463. doi.org/10.3389/fenrg.2021.764463
  29. Chong JWR, Chan YJ, Chong S, Ho YC, Mohamad M, Tan WN, et al. Simulation and Optimisation of Integrated Anaerobic-Aerobic Bioreactor (IAAB) for the Treatment of Palm Oil Mill Effluent. Processes. 2021;9:1124. doi.org/10.3390/pr9071124
  30. Innocenzi V, Celso GM, Prisciandaro M. Techno-economic analysis of olive wastewater treatment with a closed water approach by integrated membrane processes and advanced oxidation processes. Water Reuse. 2021; 11(1): 122-35. doi.org/10.2166/wrd.2020.066
  31. Chemicalaid. Chemical Equation Balancer (online). Available from: https://es.intl.chemicalaid.com/tools/equationbalancer.php?equation=CrO3+%2B+Na2S2O5+%2B+H2SO4+%3D+Cr2%28SO4%293+%2B+NaSO4+%2B+H2O. Accessed on 25 oct 2021.
  32. Petkov K, Stefanova V, Stamenov L, Iliev P. An analytical study of the neutralization process of solutions with high concentration of Fe(III) ions. Journal of Chemical Technology and Metallurgy. 2017;52(2):242-51.
  33. Anco PM. Procedimiento para la separación del cromo hexavalente de efluentes mineros (undergraduate thesis). Lima, Perú: Universidad Nacional Mayor de San Marcos; 2004.
  34. Chemicalaid. Chemical Equation Balancer (online). Available from: https://es.intl.chemicalaid.com/tools/equationbalancer.php?equation=NaOH+%2B+H2SO4+%3D+Na2SO4+%2B+H2O. Accessed on 25 oct 2021.
  35. Chemicalaid. Chemical Equation Balancer (online). Available from: https://en.intl.chemicalaid.com/tools/equationbalancer.php?equation=FeCl3+%2B+Cr%28OH%293+%3D+Fe%28OH%293+%2B+CrCl3. Accessed on 25 oct 2021.
  36. Lee CS, Chong MF, Binner E, Gomes R, Robinson J. Techno-economic assessment of scale-up ofbio-flocculant extraction and production by usingokra as biomass feedstock. Chemical Engineering Research and Design. 2018; 132: 358-69. doi.org/10.1016/j.cherd.2018.01.050
  37. Chemanalyst. Pricing Data (online). Available from: https://www.chemanalyst.com/Pricing-data/. Accessed on 30 oct 2021. https://www.chemanalyst.com/Pricingdata/
  38. ICIS. (2021). Chemicals Cost (online). Available from: https://www.icis.com/explore/chemicals/channel-info-chemicals-a-z/. Accessed on 30 oct 2021.
  39. Brown T. Engineering Economics and Economic Design for Process Engineers. USA: CRC Press; 2006.
  40. Green DW, Southard MZ. Perry's Chemical Engineers' Handbook. 9 ed. USA: McGraw-Hill; 2019.
  41. Sinnott R, Towler G. Chemical Engineering Design. 6 ed. United Kingdom: Butterworth-Heinemann; 2020.
  42. MATCHE. Chemical Equipment Cost (online). Available from: www.matche.com. Accessed on 12 nov 2021.
  43. Jenkins S. Economic Indicators. Chemical Engineering. 2021; 18(12): 112.
  44. Baca G. Evaluación de proyectos. 6ta ed. Mexico: McGraw-Hill/Interamericana Editores S.A. de C.V.; 2010.
  45. Meza JJ. Evaluación financiera de proyectos. 3 ed. Colombia: Ecoe Ediciones; 2013.