Abstract
A large portion of urban emissions in developing countries come from old gasoline vehicles driven in metropolitan areas. The present study aimed to develop models to estimate the environmental impact of different contents of gasoline and ethanol mixtures (pure gasoline; 25, 50, 75% ethanol blended to gasoline; and 100% ethanol) in a flex-fuel engine. We tested the blended fuel using three different speeds and recorded the GHG emissions and engine output data. The data mining approach was used to develop environmental impact predictive models. The ethanol content in gasoline; the engine rotational speed 900, 2000, and 3000 rpm; and λ were used as attributes. The classification target was the environmental impact concerning the CO2 emission (“low,” “average,” and “high”). We employed the Random forest algorithm to develop predictive models. The mean values of CO2 concentrations for all studied fuel content were above 2.47% of the volume. The trees’ models (accuracy 73%, κ =0.61) showed three alternatives for predicting the environmental impact based on the ethanol blend, the engine rotation, λ, and the air-fuel ratio. Such models might help policymakers develop educational campaigns to reduce short- and medium-term urban commuter traffic pollution in countries that lack suitable urban transportation.
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Change history
23 April 2021
A Correction to this paper has been published: https://doi.org/10.1007/s11356-021-13920-8
References
ANP (2015). Agência Nacional do Petróleo, Gás Natural e Biocombustíveis, n 19. http://nxt.anp.gov.br/NXT/gateway.dll/leg/resolucoes_anp/2015/abril/ranp%2019%20-%202015.xml?f=templates&fn=document-frameset.htm. Accessed 30 Dec 2019.
ANP (2017). Agência Nacional do Petróleo, Gás Natural e Biocombustíveis, n.9. http://www.anp.gov.br/images/Consultas_publicas/Concluidas/2018/n_4/4-NT009SPC2017_Minuta_Resolucao_Biocombustiveis.pdf. Accessed 20 Dec 2019.
Barakat Y, Awad EN, Ibrahim V (2016) Fuel consumption of gasoline ethanol blends at different engine rotational speeds. Egypt J Pet 25:309–315. https://doi.org/10.1016/j.ejpe.2015.07.019
Beer T, Grant T (2007) Life-cycle analysis of emissions from fuel ethanol and blends in Australian heavy and light vehicles. J Clean Prod 15:833–837. https://doi.org/10.1016/j.jclepro.2006.07.003
Cahyono B, Abu Bakar R (2011) Effect of ethanol addition in the combustion process during warm-UPS and half open throttle on port-injection gasoline engine. Am J Eng Appl Sci 4:66–69. https://doi.org/10.3844/ajeassp.2011.66.69
Canakci M, Ozsezen AN, Alptekin E, Eyidogan M (2013) Impact of alcohol–gasoline fuel blends on the exhaust emission of an SI engine. Renew Energy 52:111–117
Cataluna R, Silva R, Menezes EW et al (2008) Specific consumption of liquid biofuels in gasoline fueled engines. Fuel 87:3362–3368. https://doi.org/10.1016/j.fuel.2008.04.041
CONAMA (2019) Resolution n. 493/2019. Programa de Controle da Poluição do Ar por Motociclos e Veículos similares - PROMOT para controle de emissões de gases poluentes e de ruído por ciclomotores, motociclos e veículos similares novos. http://www2.mma.gov.br/port/conama/legiabre.cfm?codlegi=743 Accessed 11 Mar 2020.
Currie J, Zivin JG, Mullins J, Neidell M (2014) What do we know about short- and long-term effects of early-life exposure to pollution? Ann Rev Resour Econ 6:217–247. https://doi.org/10.1146/annurev-resource-100913-012610
Delgado RC, Araujo AS, Fernandes VJ Jr (2007) Properties of Brazilian gasoline mixed with hydrated ethanol for flex-fuel technology. Fuel Process Technol 88:365–368. https://doi.org/10.1016/j.fuproc.2006.10.010
Doğan B, Erol D, Yaman H, Kodanli E (2017) The effect of ethanol-gasoline blends on performance and exhaust emissions of a spark-ignition engine through exergy analysis. Appl Therm Eng 120:433–443. https://doi.org/10.1016/j.applthermaleng.2017.04.012
Elfasakhany A (2015) Investigations on the effects of ethanol-methanol-gasoline blends in a spark-ignition engine. Performance and emissions analysis. Int J Eng Sci Technol 18:713–719. https://doi.org/10.1016/j.jestch.2015.05.003
Garcıa CA, Manzini F, Islas J (2010) Air emissions scenarios from ethanol as a gasoline oxygenated in Mexico City metropolitan area. Renew Sust Energ Rev 14:3032–3040. https://doi.org/10.1016/j.rser.2010.07.011
Garcia S, Luengo J, Sáez JA, López V, Herrera F (2013) A survey of discretization techniques: Taxonomy and empirical analysis in supervised learning. IEEE Trans Knowl Data Eng 25:734–750. https://doi.org/10.1109/TKDE.2012.35
Gentner DR, Jathar SH, Gordon TD, Bahreini R, Day DA, el Haddad I, Hayes PL, Pieber SM, Platt SM, de Gouw J, Goldstein AH, Harley RA, Jimenez JL, Prévôt ASH, Robinson AL (2017) Review of urban secondary organic aerosol formation from gasoline and diesel motor vehicle emissions. Environ Sci Technol 51:1074–1093. https://doi.org/10.1021/acs.est.6b04509
Guerrieri DA, Caffrey PJ, Rao V (1995) Investigation into the vehicle exhaust emissions of high percentage ethanol blends. SAE 1995:950777. https://doi.org/10.4271/950777
Habib K, Umar AI (2015) Research article anomalies calculation and detection in fuel expense through data mining. Res J Inf Technol. https://doi.org/10.19026/rjit.6.2165
Hitchcock G, Conlan B, Kay D et al. (2014) Air quality and road transport: impacts and solutions. RAC Foundation. http://www.racfoundation.org/assets/rac_foundation/content/downloadables/racf_ricardo_aea_air_quality_report_hitchcock_et_al_june_2014.pdf. Accessed 15 June 2020.
Hofmann M, Klinkenberg R (2014) RapidMiner: data mining use cases and business analytics applications. Getting Used to RapidMiner. Boca Raton: Chapman & Hall, C.R.C. Press.
IEA (2018) International Energy Agency. CO2 Emissions from fuel combustion - highlights. Statistics. https://www.iea.org/statistics/co2emissions/ Accessed 14 Dec 2019.
IEA (2019) International Energy Agency. CO2 emissions from fuel combustion. Data base documentation. http://wds.iea.org/wds/pdf/WorldCo2_Documentation.pdf. Accessed 15 Dec 2019).
Iodice P, Langella G, Amoresano A (2017a) A numerical approach to assess air pollution by ship engines in manoeuvring mode and fuel switch conditions. Energy Environ 28:827–845. https://doi.org/10.1177/0958305X17734050
Iodice P, Senatore A, Langella G, Amoresano AP (2017b) Advantages of ethanol-gasoline blends as fuel substitute for last generation Si engines. Environ Prog Sustain Energy 36:1173–1179. https://doi.org/10.1002/ep.12545
Iodice P, Langella G, Amoresano A (2019) Modeling and energetic-exergetic evaluation of a novel screw expander-based direct steam generation solar system. Appl Therm Eng 155:82–95. https://doi.org/10.1016/j.applthermaleng.2019.03.151
Jorge A, Larrazabal G, Guillen P et al (2017) Proceedings of the workshop on data mining for oil and gas. Data Sci Oil Gas. https://doi.org/10.13140/RG.2.2.16408.39681 Accessed 30 Aug 2020
Kalghatgi G (2018) Is it really the end of internal combustion engines and petroleum in transport? Appl Energy. https://doi.org/10.1016/j.apenergy.2018.05.076
Kim H, Kim J, Kim S et al (2017) Cardiovascular effects of long-term exposure to air pollution: a population-based study with 900.845 person-years of follow-up. J Am Heart Assoc 6:e007170. https://doi.org/10.1161/JAHA.117.007170
Knoll K, West B, Huff S et al (2009) Effects of mid-level ethanol blends on conventional vehicle emissions. SAE. https://doi.org/10.4271/2009-01-272
Koç M, Sekmen Y, Topgül T, Yücesu HS (2009) The effects of ethanol–unleaded gasoline blends on engine performance and exhaust emissions in a spark-ignition engine. Renew Energy 34:2101–2106. https://doi.org/10.1016/j.renene.2009.01.018
Najafi G, Ghobadian B, Yusaf T, Safieddin Ardebili SM, Mamat R (2015) Optimization of performance and exhaust emission parameters of a SI engine with gasoline-ethanol blended fuel using response surface methodology. Energy 90:1815–1829. https://doi.org/10.1016/j.energy.2015.07.004
Najafi G, Ghobadian B, Moosavian A et al (2016) SVM and ANFIS for prediction of performance and exhaust emissions of a SI engine with gasoline–ethanol blended fuels. Appl Therm Eng 95:186–203. https://doi.org/10.1016/j.applthermaleng.2015.11.009
Park C, Choi Y, Kim C, Oh S, Lim G, Moriyoshi Y (2010) Performance and exhaust emission characteristics of a spark ignition engine using ethanol and ethanol-reformed gas. Fuel 89:2118–2125. https://doi.org/10.1016/j.fuel.2010.03.018
Rapidminer Studio (2020) Predictive analytics software. https://rapidminer.com/. Accessed 20 May 2020.
Rice RW, Sanyal AK, Elrod AC, Bata RM (1991) Exhaust gas emissions of butanol, ethanol and methanol–gasoline blend. J Eng Gas Turbines Power 113:377–381. https://doi.org/10.1115/1.2906241
Ristoski P, Bizer C, Paulheim H (2015) Mining the web of linked data with Rapidminer. Web Semant 35:142–151. https://doi.org/10.1016/j.websem.2015.06.004
Roso VR, Santos NDSA, Alvarez CEC, Rodrigues Filho FA, Pujatti FJP, Valle RM (2019) Effects of mixture enleanment in combustion and emission parameters using a flex-fuel engine with ethanol and gasoline. Appl Therm Eng 153:463–472. https://doi.org/10.1016/j.applthermaleng.2019.03.012
Schifter I, Diaz L, Gómez JP, Gonzalez U (2013) Combustion characterization in a single cylinder engine with mid-level hydrated ethanol-gasoline blended fuels. Fuel 103:292–298. https://doi.org/10.1016/j.fuel.2012.06.002
Schifter I, González U, Díaz L, Rodríguez R, Mejía-Centeno I, González-Macías C (2018) From actual ethanol contents in gasoline to mid-blends and E-85 in conventional technology vehicles: emission control issues and consequences. Fuel 219:239–247. https://doi.org/10.1016/j.fuel.2018.01.118
Schirmer WN, Olanyk LZ, Guedes CLB, Quessada TP, Ribeiro CB, Capanema MA (2017) Effects of air/fuel ratio on gas emissions in a small spark-ignited non-road engine operating with different gasoline/ethanol blends. Environ Sci Pollut Res 24:20354–20359. https://doi.org/10.1007/s11356-017-9651-8
Schwaderlapp M, Adomeit P, Kolbeck AM, Thewes AM (2012) Ethanol and its potential for downsized engine concepts. Auto Tech Rev 1:48–53. https://doi.org/10.1365/s40112-012-0022-z
Shah B, Trivedi BH (2012) Artificial neural network based intrusion detection system: a survey. Int J Comput Appl 39:13–18 https://www.researchgate.net/profile/Bhushan_Trivedi/publication/258650781_Artificial_Neural_Network_based_Intrusion_Detection_System_A_Survey/links/58450f5908ae2d217566d926/Artificial-Neural-Network-based-Intrusion-Detection-System-A-Survey.pdf. Accessed August 10, 2020
Slovic AD, Ribeiro H (2018) Policy instruments surrounding urban air quality: the cases of São Paulo, New York City and Paris. Environ Sci Pol 81:1–9. https://doi.org/10.1016/j.envsci.2017.12.001
Suarez-Bertoa R, Zardini AA, Keuken H, Astorga C (2015) Impact of ethanol containing gasoline blends on emissions from a flex-fuel vehicle tested over the Worldwide Harmonized Light duty Test Cycle (WLTC). Fuel 143:173–182. https://doi.org/10.1016/j.fuel.2014.10.076
Thakur AK, Kaviti R, Mehra KKS et al (2017) Progress in performance analysis of ethanol-gasoline blends on SI engine. Renew Sust Energ Rev 69:324–340. https://doi.org/10.1016/j.rser.2016.11.056
Thakur AK, Kaviti AK, Singh R, Gehlot A (2020) Specifc soft computing strategies for evaluating the performance and emissions of an SI engine using alcohol-gasoline blended fuels—a comprehensive analysis. Arch Comput Methods Eng. https://doi.org/10.1007/s11831-020-09499-x
Topgul T, Yucesu HS, Çinar C et al (2006) The effects of ethanol–unleaded gasoline blends and ignition timing on engine performance and exhaust emissions. Renew Energy 31:2534–2542. https://doi.org/10.1016/j.renene.2006.01.004
Venugopal T, Sharma A, Satapathy S, Ramesh A, Gajendra Babu MK (2013) Experimental study of hydrous ethanol gasoline blend (E10) in a four stroke port fuel-injected spark ignition engine. Int J Energy Res 37:638–644. https://doi.org/10.1002/er.1957
WEC (2011) World Energy Council. Global transport scenarios 2050. WEC London. https://www.worldenergy.org/assets/downloads/wec_transport_scenarios_2050.pdf. Accessed 15 June 2020
WHO (2016) Global Urban Ambient Air Pollution Database. http://www.who.int/phe/health_topics/outdoorair/databases/cities/en/. Accessed 15 June 2020.
Acknowledgements
The authors thank the University Mauá for allowing the laboratory’s use when we did the experimental research. We also thank the Universidade Paulista Campus Swift Engineering undergraduate students who helped to carry on the tests.
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GTD designed and set up the experiment. IAN, GTD, and NDSL analyzed the data and the application of the data mining approach. NDSL was a major contributor in writing the manuscript. All authors read and approved the final manuscript.
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Duarte, G.T., de Alencar Nääs, I. & da Silva Lima, N.D. Estimating the urban environmental impact of gasoline-ethanol blended fuels in a passenger vehicle engine. Environ Sci Pollut Res 28, 63977–63988 (2021). https://doi.org/10.1007/s11356-021-13432-5
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DOI: https://doi.org/10.1007/s11356-021-13432-5