Skip to main content
SpringerLink
Log in

Computational Intelligence for Evaluating the Air Quality in the Center of Madrid, Spain

  • Conference paper
  • First Online:
Book cover Optimization and Learning (OLA 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1173))

Included in the following conference series:

Abstract

This article presents the application of data analysis and computational intelligence techniques for evaluating the air quality in the center of Madrid, Spain. Polynomial regression and deep learning methods to analyze the time series of nitrogen dioxide concentration, in order to evaluate the effectiveness of Madrid Central, a set of road traffic limitation measures applied in downtown Madrid. According to the reported results, Madrid Central was able to significantly reduce the nitrogen dioxide concentration, thus effectively improving air quality.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Barrionuevo, J., Berrone, P., Ricart, J.: Smart cities, sustainable progress. IESE Insight 14(14), 50–57 (2012)

    Article  Google Scholar 

  2. Camero, A., Toutouh, J., Stolfi, D.H., Alba, E.: Evolutionary deep learning for car park occupancy prediction in smart cities. In: Battiti, R., Brunato, M., Kotsireas, I., Pardalos, P.M. (eds.) LION 12 2018. LNCS, vol. 11353, pp. 386–401. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-05348-2_32

    Chapter  Google Scholar 

  3. Cantillo, V., Ortúzar, J.: Restricting the use of cars by license plate numbers: a misguided urban transport policy. DYNA, 81(188), 75–82 (2014)

    Article  Google Scholar 

  4. European Commission: Directive 2004/107/EC of the European Parliament and of the Council of 15 December 2004 relating to arsenic, cadmium, mercury, nickel and polycyclic aromatic hydrocarbons in ambient air. Official Journal of the European Union 23, 3–16 (2004)

    Google Scholar 

  5. European Commission: Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe. Official Journal of the European Union 152, 1–44 (2008)

    Google Scholar 

  6. European Environment Agency: Air quality in Europe: 2019 report. https://www.eea.europa.eu/publications/air-quality-in-europe-2019. Accessed 11 Nov 2019

  7. Fabbiani, E., Nesmachnow, S., Toutouh, J., Tchernykh, A., Avetisyan, A., Radchenko, G.: Analysis of mobility patterns for public transportation and bus stops relocation. Program. Comput. Softw. 44(6), 508–525 (2018)

    Article  Google Scholar 

  8. Foggin, S.: Does restricting the use of private vehicles tackle Medellín’s pollution problem? Latin America Reports. https://latinamericareports.com/does-restricting-the-use-of-private-vehicles-tackle-medellins-pollution-problem/1567/. Accessed 1 Nov 2019

  9. Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. The MIT Press, Cambridge (2016)

    MATH  Google Scholar 

  10. Honarvar, A., Sami, A.: Towards sustainable smart city by particulate matter prediction using urban big data, excluding expensive air pollution infrastructures. Big Data Res. 17, 56–65 (2019)

    Article  Google Scholar 

  11. Lebrusán, I., Toutouh, J.: Assessing the environmental impact of car restrictions policies: Madrid Central case. In: Nesmachnow, S., Hernández Callejo, L. (eds.) ICSC-CITIES 2019. CCIS, vol. 1152, pp. 9–24. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-38889-8_2

    Chapter  Google Scholar 

  12. Li, J., Li, X.B., Li, B., Peng, Z.R.: The effect of nonlocal vehicle restriction policy on air quality in Shanghai. Atmosphere 9(8), 299 (2018)

    Article  Google Scholar 

  13. Liguang, F., Haozhi, Z., Yulin, J., Zhaorong, W.: Evaluation on the effect of car use restriction measures in Beijing. In: 51st Annual Transportation Research Forum, pp. 1–10 (2010)

    Google Scholar 

  14. Liu, Y., Yan, Z., Liu, S., Wu, Y., Gan, Q., Dong, C.: The effect of the driving restriction policy on public health in Beijing. Nat. Hazards 85(2), 751–762 (2016)

    Article  Google Scholar 

  15. Massobrio, R., Nesmachnow, S.: Urban data analysis for the public transportation systems of Montevideo, Uruguay. In: Nesmachnow, S., Hernández Callejo, L. (eds.) ICSC-CITIES 2019. CCIS, vol. 1152, pp. 199–214. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-38889-8_16

    Chapter  Google Scholar 

  16. OECD: The Economic Consequences of Outdoor Air Pollution (2016). https://www.oecd.org/environment/indicators-modelling-outlooks/Policy-Highlights-Economic-consequences-of-outdoor-air-pollution-web.pdf. Accessed 11 Nov 2019

  17. Orłowski, A., Marć, M., Namieśnik, J., Tobiszewski, M.: Assessment and optimization of air monitoring network for smart cities with multicriteria decision analysis. In: Nguyen, N.T., Tojo, S., Nguyen, L.M., Trawiński, B. (eds.) ACIIDS 2017. LNCS (LNAI), vol. 10192, pp. 531–538. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-54430-4_51

    Chapter  Google Scholar 

  18. O’Ryan, R., Martinez, F., Larraguibel, L.: A neural networks approach to evaluating urban policies: the case of Santiago, Chile. WIT Trans. Built Environ. 23, 127–139 (1996)

    Google Scholar 

  19. Reuters: Paris bans up to 60% of its cars as heatwave worsens pollution. https://www.reuters.com/article/us-france-pollution/paris-bans-up-to-60-of-its-cars-as-heatwave-worsens-pollution. 10 Nov 2019

  20. Soni, N., Soni, N.: Benefits of pedestrianization and warrants to pedestrianize an area. Land Use Policy 57, 139–150 (2016)

    Article  Google Scholar 

  21. Stevenson, M., et al.: Land use, transport, and population health: estimating the health benefits of compact cities. Lancet 388(10062), 2925–2935 (2016)

    Article  Google Scholar 

  22. Viard, V., Fu, S.: The effect of Beijing’s driving restrictions on pollution and economic activity. J. Public Econ. 125, 98–115 (2015)

    Article  Google Scholar 

  23. Wang, L., Xu, J., Zheng, X., Qin, P.: Will a driving restriction policy reduce car trips? A case study of Beijing, China. Transp. Res. Part A: Policy Pract. 67, 279–290 (2014)

    Google Scholar 

  24. WHO: Mortality and burden of disease from ambient air pollution (2017). https://doi.org/10.1787/9789264257474-en. Accessed 11 Nov 2019

  25. Zhang, L., Long, R., Chen, H.: Do car restriction policies effectively promote the development of public transport? World Dev. 119, 100–110 (2019)

    Article  Google Scholar 

  26. Zheng, X., et al.: Big data for social transportation. IEEE Trans. Intell. Transp. Syst. 17(3), 620–630 (2016)

    Article  Google Scholar 

Download references

Acknowledgements

I. Lebrusán has been partially funded by RCC Harvard program. J. Toutouh has been partially funded by EU’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 799078; and by the Spanish MINECO and FEDER projects TIN2017-88213-R, RTI2018-100754-B-I00, and UMA18-FEDERJA-003.

Author information

Authors and Affiliations

  1. CSAIL, Massachusetts Institute of Technology, Cambridge, MA, USA

    Jamal Toutouh

  2. IGLP, Harvard University, Cambridge, MA, USA

    Irene Lebrusán

  3. Universidad de la República, Montevideo, Uruguay

    Sergio Nesmachnow

Authors
  1. Jamal Toutouh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Irene Lebrusán
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sergio Nesmachnow
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jamal Toutouh .

Editor information

Editors and Affiliations

  1. University of Cádiz, Cádiz, Spain

    Bernabé Dorronsoro

  2. University of Cádiz, Cádiz, Spain

    Patricia Ruiz

  3. University of Cádiz, Cádiz, Spain

    Juan Carlos de la Torre

  4. University of Cádiz, Cádiz, Spain

    Daniel Urda

  5. University of Lille, Lille, France

    El-Ghazali Talbi

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Toutouh, J., Lebrusán, I., Nesmachnow, S. (2020). Computational Intelligence for Evaluating the Air Quality in the Center of Madrid, Spain. In: Dorronsoro, B., Ruiz, P., de la Torre, J., Urda, D., Talbi, EG. (eds) Optimization and Learning. OLA 2020. Communications in Computer and Information Science, vol 1173. Springer, Cham. https://doi.org/10.1007/978-3-030-41913-4_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-41913-4_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41912-7

  • Online ISBN: 978-3-030-41913-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation