Study of an eco-efficiency index for pollutant emission projects using AHP method in decision making

Authors

DOI:

https://doi.org/10.33448/rsd-v11i12.34362

Keywords:

Environmental; Industrial; Judgment Matrix; Matlab.

Abstract

The eco-efficiency index must be measured based on environmental, energy and material parameters, among others, where it will help in the fight against waste and should contribute to monitoring the implementation of a sustainable project. In this work, an algorithm based on the AHP method was developed aiming to help people in decision-making in projects that simulate real combustion situations; the MATLAB software was used for this. The steps used were: Definition of criteria (SOx, NOx, PM, and VOC emissions), creation of the judgment matrix, and simulation of the values assigned to the projects (using CONAMA resolution 436/2011 as a parameter). The results showed that project 3 had the best eco-efficiency index since its decision vector has the lowest impact compared to other projects; likewise, project 2 proved to be the most harmful under the conditions evaluated. It is expected that from this work new more complex solutions can be created using new criteria, scenarios, and other methods and programming logic.

References

Bian, Y., Dong, L., Liu, Z., & Zhang, L. (2020). A sectoral eco-efficiency analysis on urban-industrial symbiosis. Sustainability, 12(9), 3650.

Brandão, Y. F. F., de Vasconcelos, W. E., & Sales, I. T. (2022). Estudo De Caso Da Matriz Elétrica Brasileira: Escolha De Fontes Não Emissoras De Co2 Com Auxílio Do Método Ahp: Case Study Of Brazilian Electric Matrix: Choice Of Sources Not Emitters Co2 Assisted By Ahp Method. Brazilian Journal of Production Engineering, 01-11.

Brandão, Y. F. F., & Dos Santos, V. A. (2020). Desenvolvimento de um algoritmo para integrar um sistema de gestão de combustão em usinas termelétricas a carvão. Avaliação, Diagnóstico e Solução de Problemas Ambientais e Sanitários p. 27-35. https://www.atenaeditora.com.br/post-artigo/38829

Brasil (2011). Conselho Nacional do Meio Ambiente (CONAMA). Resolução Nº 436, de 22 de Dezembro De 2011.

Brasil (2018). Conselho Nacional do Meio Ambiente (CONAMA). Resolução Nº 491, de 19 de Novembro De 2018.

Buonomo, I., Benevene, P., Barbieri, B., & Cortini, M. (2020). Intangible assets and performance in nonprofit organizations: a systematic literature review. Frontiers in Psychology, 11, 729.

Calabrese, A., Costa, R., Levialdi, N., & Menichini, T. (2019). Integrating sustainability into strategic decision-making: A fuzzy AHP method for the selection of relevant sustainability issues. Technological Forecasting and Social Change. V. 139, p.155-168.

Caravaggio, N., Caravella, S., Ishizaka, A., & Resce, G. (2019). Beyond CO2: A multi-criteria analysis of air pollution in Europe, Journal of Cleaner Production.

Çevik, M., & Tabaru-Örnek, G. (2020). Comparison of MATLAB and SPSS Software in the Prediction of Academic Achievement with Artificial Neural Networks: Modeling for Elementary School Students. International Online Journal of Education and Teaching, 7(4), 1689-1707.

De Araujo, J. M., & Do Rosário, N. M. É. (2020). Poluição atmosférica associada ao material particulado no estado de São Paulo: análise baseada em dados de satélite. Brazilian Journal of Environmental Sciences (Online), 55(1), 32-47.

Ferla, R., Muller, S. H., & Klann, R. C. (2019). Influência dos ativos intangíveis no desempenho econômico de empresas latino-americanas. Brazilian Review of Finance, 17(1), 35-50.

Gioda, A. (2018). Comparação dos níveis de poluentes emitidos pelos diferentes combustíveis utilizados para cocção e sua influência no aquecimento global. Química Nova, 41, 839-848.

Jalalvand, A. R., Roushani, M., Goicoechea, H. C., Rutledge, D. N., & Gu, H. W. (2019). MATLAB in electrochemistry: A review. Talanta, 194, 205-225.

Liang, H., Ren, J., Lin, R., & Liu, Y. (2019). Alternative-fuel based vehicles for sustainable transportation: A fuzzy group decision supporting framework for sustainability prioritization. Technological Forecasting and Social Change, v. 140, p.33–016.

Liao, H., Wu, X., Mi, X., & Herrera, F. (2020). An integrated method for cognitive complex multiple experts multiple criteria decision making based on ELECTRE III with weighted Borda rule. Omega, 93, 102052.

Lim, W. M., Ciasullo, M. V., Douglas, A., & Kumar, S. (2022). Environmental social governance (ESG) and total quality management (TQM): a multi-study meta-systematic review. Total Quality Management & Business Excellence, 1-23.

Medeiros, J. F., Ribeiro J. L. D., & Cortimiglia, M. N. (2014). Success factors for environmentally sustainable product innovation: a systematic literature review. Journal of Cleaner Production. V. 65, p.76-86.

Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International journal of services sciences, v. 1, n. 1, p. 83-98.

Souza, P. A., Francisco, K. C., & Cardoso, A. A. (2017). Desenvolvimento de amostrador passivo sensível para monitoramento de poluição atmosférica por dióxido de nitrogênio. Química Nova, 40, 1233-1237.

Sun, B., Tang, J., Yu, D., Song, Z., & Wang, P. (2019). Ecosystem health assessment: A PSR analysis combining AHP and FCE methods for Jiaozhou Bay, China. Ocean & Coastal Management, V. 168, p.41–50.

Vergnhanini Filho, R. (2020). Emissão De Óxidos De Enxofre (Sox) Na Combustão Industrial. Revista IPT: Tecnologia e Inovação, 4(14).

Zou, W., Gao, B., Ok, Y. S., & Dong, L. (2019). Integrated adsorption and photocatalytic degradation of volatile organic compounds (VOCs) using carbon-based nanocomposites: A critical review. Chemosphere, 218, 845-859.

Published

11/09/2022

How to Cite

BRANDÃO, Y. F. F.; VASCONCELOS, W. E. de . Study of an eco-efficiency index for pollutant emission projects using AHP method in decision making. Research, Society and Development, [S. l.], v. 11, n. 12, p. e199111234362, 2022. DOI: 10.33448/rsd-v11i12.34362. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/34362. Acesso em: 13 nov. 2024.

Issue

Section

Engineerings