Temporal Trends and Statistical Analysis of PM10 and TSP Concentrations in the Region of Grande Vitória from 2008 to 2017

Authors

DOI:

https://doi.org/10.5902/2179460X69023

Keywords:

Comparison Tests, Time Series, Air Pollution, Region of Grande Vitória, Statistics

Abstract

This study aimed to statistically evaluate the PM10 and TSP time series data in the RGV, between 2008 and 2017, verifying whether the series of each pollutant are generated by the same stochastic process. For that, the tests proposed by Coates and Diggle (1986), by Quenouille (1958) and the series difference procedure developed by Silva, Ferreira and Sáfadi (2000) were used. PM10 time series for Laranjeiras (E1), Carapina (E2), Jardim Camburi (E3), Enseada do Suá (E4), Vitória (E5), IBES (E6) and Cariacica (E8) stations were compared two by two, and for TPS time series of stations E3, E4, E5, E6 and E8 the same was done. Results indicate that, for a 5% significance level, stations E2, E3, E4, E5 and E6 for PM10 and, E3, E4, E5 and E6, for the TSP, present time series generated by the same stochastic process. Therefore, is considered that, the results obtained are indicative of the need to reformulation the initial RAMQAr project, which, if added to a pollutant dispersion study, can guarantee the network coverage area expansion, with emphasis in the existing stations re-spatialization, aiming to improve their data representativeness and installation of new stations in places still lacking monitoring.

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Author Biographies

Isamara Maria Schmidt, Universidade Federal do Espírito Santo

Bachelor of Environmental and Sanitary Engineering. Master's student of the Graduate Program in Environmental Engineering at the Federal University of Espírito Santo (PPGEA-UFES) in the area of concentration in Air Pollution.

Jaqueline Knaak, Universidade Federal do Espírito Santo

Bachelor of Environmental and Sanitary Engineering. Master's student of the Graduate Program in Environmental Engineering at the Federal University of Espírito Santo (PPGEA-UFES) in the area of concentration in Air Pollution.

Wanderson de Paula Pinto, Faculdade da Região Serrana - FARESE

Doctor by the Graduate Program in Environmental Engineering at the Federal University of Espírito Santo (PPGEA-UFES) in the area of concentration in Air Pollution. Professor at the Department of Environmental Sciences and coordinator of the Integrated Center for Research in Environmental Engineering at the Faculty of the Region Serrana (FARESE).

Edson Zambom Monte, Universidade Federal do Espírito Santo

Doctor by the Graduate Program in Environmental Engineering at the Federal University of Espírito Santo (PPGEA-UFES). Professor at the Department of Economics, Federal University of Espírito Santo (UFES).

Michel Trarbach Bleidorn, Universidade Federal do Espírito Santo

Bachelor of Environmental and Sanitary Engineering. Master's student of the Graduate Program in Environmental Engineering at the Federal University of Espírito Santo (PPGEA-UFES) in the area of concentration in Water Resources.

Gemael Barbosa Lima, Faculdade da Região Serrana - FARESE

Coordinator and Professor of the Environmental Engineering course (FARESE). Doctoral student in Environmental Engineering at the Federal University of Espírito Santo (UFES).

References

Abe, K. C. and Miraglia, S. G. K. (2018). Avaliação de impacto à saúde do Programa de Controle de Poluição do Ar por veículos automotores no município de São Paulo, Brasil. Revista Brasileira de Ciências Ambientais (Online), (47):61–73. DOI: 10.5327/z2176-947820180310.

Amaral, M. V. S. G. (2014). Ajuste de modelos e comparação de séries temporais para dados de vazão específica em microbacias pareadas. Mestrado em ciências, Escola Superior de Agricultura Luiz de Queiroz, Universidade de São Paulo, Piracicaba, São Paulo.

Béjot, Y., Reis, J., Giroud, M., and Feigin, V. (2018). A review of epidemiological research on stroke and dementia and exposure to air pollution. International Journal of Stroke,13(7):687–695. DOI: 10.1177/1747493018772800.

Bowe, B., Xie, Y., Li, T., Yan, Y., Xian, H., and Al-Aly, Z. (2018). The 2016 global and national burden of diabetes mellitus attributable to PM2.5 air pollution. The Lancet Planetary Health, 2(7):e301–e312. DOI:10.1016/s2542-5196(18)30140-2.

Box, G. E. P. and Pierce, D. A. (1970). Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models. Journal of the American Statistical Association, 65(332):1509–1526. DOI:10.1080/01621459.1970.10481180.

Brockwell, P. and Davis, R. (2006). Time Series: Theory and Methods. Springer, New York, 2 edition.

Calderón-Garcidueñas, L., Leray, E., Heydarpour, P., Torres-Jardón, R., and Reis, J. (2016). Air pollution, a rising environmental risk factor for cognition, neuroinflammation and neurodegeneration: The clinical impact on children and beyond. Revue Neurologique,172(1):69–80. DOI: 10.1016/j.neurol.2015.10.008.

Celis, J. E., Morales, J. R., Zaror, C. A., and Carvacho, O. F. (2007). Contaminación del aire atmosférico por Material Particulado em uma ciudad intermedia: El caso de Chillán (Chile). Información tecnológica, 18(3). DOI:10.4067/s0718-07642007000300007.

Coates, D. S. and Diggle, P. J. (1986). Tests for comparing two estimated spectral densities. Journal of Time Series Analysis, 7(1):7–20. DOI: 10.1111/j.1467-9892.1986.tb00482.x.

CONAMA (2018). Resolução nº491, de 19 de novembro de 2018. Dispõe sobre padrões de qualidade do ar. Technical report, Brasília.

Costa, F. M. (2010). Comparação estatística de duas séries de Material Particulado (MP10) na cidade de SãoPaulo. Mestrado em estatística e experimentação agronômica, Universidade Federal de Lavras, Lavras, Minas Gerais.

Costa, F. M. and Sáfadi, T. (2010). Comparação estatística de duas séries de Material Particulado (MP10) na cidade de São Paulo. Revista Brasileira de Biometria, 28(3):23–38.

Cotta, H. H. A., Reisen, V. A., Bondon, P., and Filho, P. R. P. (2020). Identification of redundant air quality monitoring stations using Robust Principal Component Analysis. Environmental Modeling & Assessment, 25(4):521–530. DOI:10.1007/s10666-020-09717-7.

Dapper, S. N., Spohr, C., and Zanini, R. R. (2016). Poluição do ar como fator de risco para a saúde: uma revisão sistemática no estado de São Paulo. Estudos Avançados, 30(86):83–97. DOI:10.1590/s0103-40142016.00100006.

ECOSOFT (2019). Inventário de emissões atmosféricas da região da grande vitória ano base - 2015. Technical report, Vitória.

ESPÍRITO SANTO (2013). Decreto no 3463-r, de 16 de dezembro de 2013. Technical report, Vitória.

Freitas, C. U., Leon, A. P., Junger, W., and Gouveia, N. (2016). Air pollution and its impacts on health in Vitoria, Espirito Santo, Brazil. Revista de Saúde Pública, 50(0). DOI:10.1590/s1518-8787.2016050005909.

Galvão, E. S., Reis, N. C., Lima, A. T., Stuetz, R. M., Orlando, M. T. D., and Santos, J. M. (2019). Use of inorganic and organic markers associated with their directionality for the apportionment of highly correlated sources of particulate matter. Science of The Total Environment, 651:1332–1343. DOI: 10.1016/j.scitotenv.2018.09.263.

Hamanaka, R. B. and Mutlu, G. M. (2018). Particulate Matter Air Pollution: Effects on the Cardiovascular System. Frontiers in Endocrinology, 9. DOI:10.3389/fendo.2018.00680.

IBGE (2023). Panorama do Censo 2022. Technical report, Rio de Janeiro.

IEMA (2018). Qualidade do ar. Technical report, Vitória.

IEMA (2021). Relatório da qualidade do ar da Região da Grande Vitória - 2021. Technical report, Vitória.

Junger, W. L. (2008). Análise, imputação de dados e interfaces computacionais em estudos de séries temporais epidemiológicas. Doutorado em saúde coletiva, Instituto de Medicina Social, Universidade do Estado do Rio de Janeiro, Rio de Janeiro.

Kendall, M. (1975). Rank Correlation Methods. Charles Griffin, London.

Khan, N. U., Shah, M. A., Maple, C., Ahmed, E., and Asghar, N. (2022). Traffic flow prediction: An intelligent scheme for forecasting traffic flow using air pollution data in smart cities with bagging ensemble. Sustainability, 14(7):4164. DOI:10.3390/su14074164.

Köppen, W. (1900). Versuch einer klassifikation der klimate, vorzugsweise nach ihren beziehungen zur pflanzenwelt.Geographische Zeitschrift, 6(12):657–679.

Leite, R. C. M., Guimarães, E. C., de Lima, E. A. P., de Souza Barrozo, M. A., and Tavares, M. (2011). Utilização de regressão logística simples na verificação da qualidade do ar atmosférico de Uberlândia. Engenharia Sanitaria e Ambiental, 16(2):175–180. DOI:10.1590/s1413-41522011000200011.

Mann, H. B. (1945). Nonparametric Tests Against Trend. Econometrica, 13(3):245. DOI:10.2307/1907187.

Monte, E. Z., de Almeida Albuquerque, T. T., and Reisen, V. A. (2016). Impactos das Variáveis Meteorológicas na Qualidade do Ar da Região da Grande Vitória, Espírito Santo, Brasil. Revista Brasileira de Meteorologia, 31(4):546–554. DOI:10.1590/0102-7786312314b20150100.

Monticelli, D. d. F., Santos, J. M., Dourado, H. O., Moreira, D. M., and Jr, N. C. R. (2020). Assessing particle dry deposition in an urban environment by using dispersion models. Atmospheric Pollution Research, 11(1):1–10. DOI:10.1016/j.apr.2019.07.010.

Moreira, D. M., Tirabassi, T., and de Moraes, M. R. (2008). Meteorologia e poluição atmosférica. Ambiente & Sociedade, 11(1):1–13. DOI: 10.1590/s1414-753x2008000100002.

Morettin, P. and Toloi, C. (2006). Análise de Séries Temporais. Edgard. Blücher, São Paulo, 2ªedition.

Nascimento, A. P., Santos, J. M., Mill, J. G., de Souza, J. B., Júnior, N. C. R., and Reisen, V. A. (2017). Association between the concentration of fine particles in the atmosphere and acute respiratory diseases in children. Revista de Saúde Pública, 51(0). DOI:10.1590/s1518-8787.2017051006523.

Nesamani, K. (2010). Estimation of automobile emissions and control strategies in India. Science of The Total Environment, 408(8):1800–1811. DOI:10.1016/j.scitotenv.2010.01.026.

Oliveira, L. M. d. (2017). Contribuição do programa Despoluir para a redução das emissões atmosféricas pela frota de ônibus da Região Metropolitana de Natal. Mestrado em uso sustentável de recursos naturais, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Norte, Rio Grande do Norte.

Petro, F. and Konečný, V. (2017). Calculation of emissions from transport services and their use for the internalization of external costs in road transport. Procedia Engineering,192:677–682. DOI: 10.1016/j.proeng.2017.06.117.

Pires, J., Sousa, S., Pereira, M., Alvim-Ferraz, M., and Martins, F. (2008). Management of air quality monitoring using principal component and cluster analysis—part I: SO2 and PM10. Atmospheric Environment, 42(6):1249–1260. DOI: 10.1016/j.atmosenv.2007.10.044.

Pooley, F. D. and Mille, M. (1999). Composition of Air Pollution Particles, pages 619–634. Academic Press, London.

Quenouille, M. H. (1958). The Comparison of Correlations in Time-Series. Journal of the Royal Statistical Society: Series B (Methodological), 20(1):158–164.

R Development Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.

Raaschou-Nielsen, O., Beelen, R., Wang, M., Hoek, G., Andersen, Z., Hoffmann, B., Stafoggia, M., Samoli, E., Weinmayr, G., Dimakopoulou, K., Nieuwenhuijsen, M., Xun, W., Fischer, P., Eriksen, K., Sørensen,M.,Tjønneland,A.,Ricceri,F.,deHoogh,K., Key, T., Eeftens, M., Peeters, P., de Mesquita, H. B., Meliefste, K., Oftedal, B., Schwarze, P., Nafstad, P., Galassi, C., Migliore, E., Ranzi, A., Cesaroni, G., Badaloni, C., Forastiere, F., Penell, J., Faire, U. D., Korek, M., Pedersen, N., Östenson, C.-G., Pershagen, G., Fratiglioni, L., Concin, H., Nagel, G., Jaensch, A., Ineichen, A., Naccarati, A., Katsoulis, M., Trichpoulou, A., Keuken, M., Jedynska, A., Kooter,I., Kukkonen, J., Brunekreef, B., Sokhi, R., Katsouyanni, K., and Vineis, P. (2016). Particulate Matter air pollution components and risk for lung cancer. Environment International, 87:66–73. DOI: 10.1016/j.envint.2015.11.007.

Ramachandra, T. and Shwetmala (2009). Emissions from India's transport sector: Statewise synthesis. Atmospheric Environment, 43(34):5510–5517. DOI: 10.1016/j.atmosenv.2009.07.015.

Raz, R., Roberts, A. L., Lyall, K., Hart, J. E., Just, A. C., Laden, F., and Weisskopf, M. G. (2015). Autism Spectrum Disorder and Particulate Matter Air Pollution before, during, and after Pregnancy: A nested case–control analysis within the nurses’ health study II cohort. Environmental Health Perspectives, 123(3):264–270. DOI: 10.1289/ehp.1408133.

Reina, J. and Olaya, J. (2012). Curve fitting nonparametric methods for studying behavior from air pollution PM10. Revista EIA, (18):19–31.

Santos, J. M., Reis, N. C., Galvão, E. S., Silveira, A., Goulart, E. V., and Lima, A. T. (2017). Source apportionment of settleable particles in an impacted urban and industrialized region in Brazil. Environmental Science and Pollution Research,24(27):22026–22039. DOI: 10.1007/s11356-017-9677-y.Seinfeld, J. H. and Pandis, S. N. (2006). Atmospheric chemistry and physics: from air pollution to climate change. John Wiley & Sons, Chichester.

Sgrancio, A. M. (2015). Análise fatorial em series temporais com long-memory, outliers e sazonalidade: aplicação em poluição do ar na região da Grande Vitória-ES. Doutorado em engenharia ambiental, Universidade Federal do Espírito Santo, Vitória.

Silva, R. B. V., Ferreira, D. F., and Sáfadi., T. (2000). Modelos de séries temporais aplicados à série dos índices de preços ao consumidor na região de Lavras, MG, no período de 1992 a 1999. Organizações Rurais & Agroindustriais, 2(2):44–55.

Stadlober, E., Hörmann, S., and Pfeiler, B. (2008). Quality and performance of a PM10 daily forecasting model. Atmospheric Environment, 42(6):1098–1109. DOI: 10.1016/j.atmosenv.2007.10.073.

Toloi, C. M. C. and Echeverry, G. (2000). Testes para comparação de séries temporais: uma aplicação a séries de temperatura e salinidade da água, medidas em profundidades diferentes. Revista Brasileira de Estatística, 61(215):51–80.

Torres, J. M., Pérez, J. P., Val, J. S., McNabola, A., Comesaña, M. M., and Gallagher, J. (2020). A functional data analysis approach for the detection of air pollution episodes and outliers: A case study in Dublin, Ireland. Mathematics, 8(2):225. DOI: 10.3390/math8020225.

Vardoulakis, S. and Kassomenos, P. (2008). Sources and factors affecting PM10 levels in two European cities: Implications for local air quality management. Atmospheric Environment, 42(17):3949–3963. DOI: 10.1016/j.atmosenv.2006.12.021.

Wang, B., Jiang, Q., and Jiang, P. (2019). A combined forecasting structure based on the L1norm: Application to the air quality. Journal of Environmental Management, 246:299–313. DOI: 10.1016/j.jenvman.2019.05.124.

Wei, W. (2006). Time Series Analysis: Univariate and Multivariate Methods. Addison Wesley, Boston.

WHO (2021). Who global air quality guidelines. Technical report, Copenhagen, Denmark. Zamprogno, B., Reisen, V. A., Bondon, P.,

Cotta, H. H. A., and Reis, N. C. (2020). Principal component analysis with autocorrelated data. Journal of Statistical Computation and Simulation, 90(12):2117–2135. DOI: 10.1080/00949655.2020.1764556.

Zhang, X., Chen, X., and Zhang, X. (2018). The impact of exposure to air pollution on cognitive performance. Proceedings of the National Academy of Sciences, 115(37):9193–9197. DOI: 10.1073/pnas.1809474115.

Zhu, F., Ding, R., Lei, R., Cheng, H., Liu, J., Shen, C., Zhang, C., Xu, Y., Xiao, C., Li, X., Zhang, J., and Cao, J. (2019). The short-term effects of air pollution on respiratory diseases and lung cancer mortality in Hefei: A time-series analysis. Respiratory Medicine, 146:57–65. DOI: 10.1016/j.rmed.2018.11.019.

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Published

2024-11-07

How to Cite

Schmidt, I. M., Knaak, J., Pinto, W. de P., Monte, E. Z., Bleidorn, M. T., & Lima, G. B. (2024). Temporal Trends and Statistical Analysis of PM10 and TSP Concentrations in the Region of Grande Vitória from 2008 to 2017. Ciência E Natura, 46, e69023. https://doi.org/10.5902/2179460X69023

Issue

Vol. 46 (2024): Publicação contínua

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Statistics

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