Abstract
One of the most complex environmental problems is the air pollution, and automotive vehicles are one of the main sources of urban air pollution. Aracaju-SE, Sergipe’s capital in the northeast of Brazil, faces frequent congestion in traffic and does not have a monitoring network of air quality, so mathematical models are useful for impact assessment. This work consisted of an unusual application of AERMOD View software for vehicular pollution evaluation at Tancredo Neves Avenue in Aracaju’s city. The modeling was performed for the two avenue tracks, considered as urban linear sources. The rate of emission source was calculated from emission factors, average speed, and the number of vehicles accounted for footage circulating on the promenade at peak times. Concentrations distributions of total suspended particles (TSP), carbon monoxide (CO), and nitrogen oxide (NOx) on the mesh receptors were determinated from weather, topographic, and sources of emission data. The dispersion maps showed that the pollutants were concentrated around the sources; the estimated TSP concentrations were within the standards of CONAMA 491/2018 law. The CO concentration values exceeded the standard due to the high rate of emission sources. NO2 concentrations also exceeded the standard for hourly average, attributed to the contribution of heavy vehicles and the emission rates of light vehicles and motorcycles. The simulations showed that the meteorological and topographical conditions of Aracaju favor the atmospheric pollutants dispersion, that vehicles significantly affect air quality in the region and that the mathematical modeling is a useful tool for the study of atmospheric dispersion.
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References
Almeida TS, Santana MO, Cruz JM, Tormen L, Lúcia V, Frescura A, Nan B, Azevedo PA, Alexandre C, Garcia B, Do JE, Alves PH, Araujo RGO (2017) Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, northeast, Brazil. Environ Pollut 226:444–451. https://doi.org/10.1016/j.envpol.2017.04.018
ANTP, Associação Nacional de Transportes Públicos (2015) Avaliando a qualidade da mobilidade urbana: aplicação de metodologia experimental. Série Cad Técnicos 23
ARACAJU (2017) Aspectos Geográficos [WWW Document]. Prefeitura de Aracaju. URL http://www.aracaju.se.gov.br/aracaju/aspectos_geograficos (accessed 1.26.18)
Baldasano JM, Massagué J (2017) Trends and patterns of air quality in Santa Cruz de Tenerife (Canary Islands) in the period 2011-2015. Air Qual Atmos Health 10:939–954. https://doi.org/10.1007/s11869-017-0484-x
Barbon A, Gomes J (2010) Simulation of atmospheric emissions over Araucaria municipality using the AERMOD model. Eng Sanitária e Ambient 15:129–140
Bertin M, Chevrier C, Serrano T, Monfort C, Rouget F, Cordier S, Viel JF (2015) Association between prenatal exposure to traffic-related air pollution and preterm birth in the PELAGIE mother-child cohort, Brittany, France. Does the urban-rural context matter? Environ Res 142:17–24. https://doi.org/10.1016/j.envres.2015.06.005
BRASIL (2018) RESOLUÇÃO CONAMA 491 DE 19 DE NOVEMBRO DE 2018 [WWW Document]. Cons Nac Meio Ambient. D.O.U. 21 nov. 2018, 1:155–156, Brasília, DF. URL http://www2.mma.gov.br/port/conama/legiabre.cfm?codlegi=740 (accessed 5.16.19)
BRASIL (2019) Qualidade do Ar [WWW Document]. Ministério do Meio Ambient Bras. URL http://www.mma.gov.br/cidades-sustentaveis/qualidade-do-ar (accessed 5.16.19)
CETESB (São Paulo) (2015) Emissões veiculares no estado de São Paulo 2014 [recurso eletrônico]. Série Relatórios, São Paulo
Costa LG, Cole TB, Coburn J, Chang YC, Dao K, Roqué PJ (2017) Neurotoxicity of traffic-related air pollution. Neurotoxicology 59:133–139. https://doi.org/10.1016/j.neuro.2015.11.008
DETRAN-SE (2019) Estatísticas - Frotas de veículo por município e espécie (anual) [WWW Document]. Dep. Estadual Trânsito Sergipe, Sergipe, 2018. URL http://www.detran.se.gov.br/estat_RB00120M.asp (accessed 5.16.19)
Duque L, Relvas H, Silveira C, Ferreira J, Monteiro A, Gama C, Rafael S, Freitas S, Borrego C, Miranda AI (2016) Evaluating strategies to reduce urban air pollution. Atmos Environ 127:196–204. https://doi.org/10.1016/j.atmosenv.2015.12.043
EPA-USA, US Environmental Protection Agency (2003) Particle pollution and your health [WWW Document]. EPA-452/F-03-001. URL http://www3.epa.gov/airnow/particle/pm-color.pdf (accessed 5.27.18)
EPA-USA, US Environmental Protection Agency (2004) Aermod: description of model formulation. Res Triangle Park, North Carolina, 2004
EPA-USA, US Environmental Protection Agency (2005) 40 CFR part 51 revision to the guideline on air quality models adoption of a preferred general purpose (flat and complex terrain), dispersion model and other revisions; final rule. Fed Regist United States 70:68218–68261
EPA-USA, US Environmental Protection Agency (2015) Aermod implementation guide. Res Triangle Park, North Carolina, 2004
Gibson MD, Kundu S, Satish M (2013) Dispersion model evaluation of PM2.5, NOx and SO2 from point and major line sources in Nova Scotia, Canada using AERMOD Gaussian plume air dispersion model. Atmos Pollut Res 4:157–167. https://doi.org/10.5094/APR.2013.016
GOOGLE MAPS (2016) Rout of Av. Beira Mar, 1383–1501 - Farolândia, Aracaju - SE to Av. Beira Mar, 3815 - Farolândia, Aracaju - SE - Google Maps [WWW Document]. URL https://www.google.com.br/maps/dir/-10.9732705,-37.0537628/−10.9571061,-37.0537299/@-10.9651665,-37.0626931,15z/data=!4m5!4m4!2m2!7e2!8j1461569340!3e0 (accessed 5.11.16)
Heist D, Isakov V, Perry S, Snyder M, Venkatram A, Hood C, Stocker J, Carruthers D, Arunachalam S, Owen RC (2013) Estimating near-road pollutant dispersion: a model inter-comparison. Transp Res Part D 25:93–105. https://doi.org/10.1016/j.trd.2013.09.003
Holmes NS, Morawska L (2006) A review of dispersion modelling and its application to the dispersion of particles: an overview of different dispersion models available. Atmos Environ 40:5902–5928. https://doi.org/10.1016/j.atmosenv.2006.06.003
Khodakarami J, Ghobadi P (2016) Urban pollution and solar radiation impacts. Renew Sust Energ Rev 57:965–976. https://doi.org/10.1016/j.rser.2015.12.166
Kimbrough S, Owen RC, Snyder M, Richmond-Bryant J (2017) NO to NO2 conversion rate analysis and implications for dispersion model chemistry methods using Las Vegas, Nevada near-road field measurements. Atmos Environ 165:23–34. https://doi.org/10.1016/j.atmosenv.2017.06.027
Kumar A, Patil RS, Dikshit AK, Kumar R (2016) Comparison of predicted vehicular pollution concentration with air quality standards for different time periods. Clean Techn Environ Policy 18:2293–2303. https://doi.org/10.1007/s10098-016-1147-6
Lakes Environmental (2018). Software AERMOD View 6.8.6
Macedo RL (2012) Qualidade do ar em Campo Grande/MS: Estudo das Emissões por fontes móveis e sua dispersão. Dissertação (Mestrado em Tecnologias Ambientais) – Programa de Pós-graduação em Tecnologias Ambientais, Universidade Federal de Mato Grosso do Sul, Campo Grande - MS
Malik A, Tauler R (2015) Exploring the interaction between O3and NOx pollution patterns in the atmosphere of Barcelona, Spain using the MCR-ALS method. Sci Total Environ 517:151–161. https://doi.org/10.1016/j.scitotenv.2015.01.105
Miranda RM, Andrade MF, Fornaro A, Astolfo R, Andre PA, Saldiva P (2012) Urban air pollution: a representative survey of PM2.5 mass concentrations insix Brazilian cities. Air Qual Atmos Health 5:63–77. https://doi.org/10.1007/s11869-010-0124-1
Richmond-Bryant J, Snyder MG, Owen RC, Kimbrough S (2018) Factors associated with NO2 and NOX concentration gradients near a highway. Atmos Environ 174:214–226. https://doi.org/10.1016/j.atmosenv.2017.11.026
Robichaud A, Comtois P (2019) Environmental factors and asthma hospitalization in Montreal, Canada, during spring 2006-2008: a synergy perspective. Air Qual Atmos Health 12:1495–1509. https://doi.org/10.1007/s11869-019-00744-2
Seangkiatiyuth K, Surapipith V, Tantrakarnapa K, Lothongkum AW (2011) Application of the AERMOD modeling system for environmental impact assessment of NO2 emissions from a cement complex. J Environ Sci 23:931–940. https://doi.org/10.1016/S1001-0742(10)60499-8
Silva RF, Araújo JHB, Teixeira GG, Meira GRN (2014) Diagnóstico das Emissões atmosféricas de origem veicular na área urbana de Campo Mourão-PR. XX Congresso Bras Eng Química-COBEQ, 2014
Su JG, Apte JS, Lipsitt J, Garcia-Gonzales DA, Beckerman BS, de Nazelle A, Texcalac-Sangrador JL, Jerrett M (2015) Populations potentially exposed to traffic-related air pollution in seven world cities. Environ Int 78:82–89. https://doi.org/10.1016/j.envint.2014.12.007
Tartakovsky D, Broday DM, Stern E (2013) Evaluation of AERMOD and CALPUFF for predicting ambient concentrations of total suspended particulate matter (TSP) emissions from a quarry in complex terrain. Environ Pollut 179:138–145. https://doi.org/10.1016/j.envpol.2013.04.023
Vellingiri K, Kim K-H, Jeon JY, Brown RJC, Jung M-C (2015) Changes in NOx and O3 concentrations over a decade at a central urban area of Seoul, Korea. Atmos Environ 112:116–125. https://doi.org/10.1016/j.atmosenv.2015.04.032
Wang W, Chai F, Zhang K, Wang A, Chen Y, Wang X, Yang Y (2008) Study on ambient air quality in Beijing for the summer 2008 Olympic games. Air Qual Atmos Health 1:31–36. https://doi.org/10.1007/s11869-008-0003-1
WORLDATLAS (2019) City populations, largest cities of the world - Worldatlas.com [WWW document]. WORLDATLAS, 2019. URL https://www.worldatlas.com/citypops.htm (accessed 5.16.19)
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The authors want to thank the “Ambientec Consultoria Ambiental LTDA.” for the disponibility of the AERMOD View software license.
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Macêdo, M.F.M., Ramos, A.L.D. Vehicle atmospheric pollution evaluation using AERMOD model at avenue in a Brazilian capital city. Air Qual Atmos Health 13, 309–320 (2020). https://doi.org/10.1007/s11869-020-00792-z
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DOI: https://doi.org/10.1007/s11869-020-00792-z