Abstract
With the increase of population living in urban areas, many transportation-related problems have grown very rapidly. Pollution causes many inhabitants health problems. A major concern for the International Community is pollution, which causes many inhabitants health problems. Accordingly, and under the risk of fines, countries are required to reduce noise and air pollutants. As a way to do so, road restrictions policies are applied in urban areas. Evaluating objectively the benefits of this type of measures is important to asses their real impact. In this work, we analyze the application of Madrid Central (MC), which is a set of road traffic limitation measures applied in the downtown of Madrid (Spain), by using smart city tools. According to our results, MC significantly reduces the nitrogen dioxide (\(NO_2\)) concentration in the air and the levels of noise in Madrid, while not arising any border effect.
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Notes
- 1.
People with reduced mobility; public transport; security and emergency services; car-sharing or moto-sharing; specific workers; distribution and commercial vehicles.
- 2.
There are no restrictions for vehicles labeled as 0 and ECO, but parking in the street for ECO vehicles is limited. B and C vehicles can only use car parks.
- 3.
Madrid Open Data Portal url: https://datos.madrid.es/.
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Acknowledgements
Irene Lebrusán has been partially funded by RCC Harvard program. Jamal Toutouh has been partially funded by European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 799078. This research has been partially funded by the Spanish MINECO and FEDER projects TIN2017-88213-R (http://6city.lcc.uma.es) and TIN2016-81766-REDT (http://cirti.es). Universidad de Málaga, Campus Internacional de Excelencia Andalucía TECH.
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Lebrusán, I., Toutouh, J. (2020). Assessing the Environmental Impact of Car Restrictions Policies: Madrid Central Case. In: Nesmachnow, S., Hernández Callejo, L. (eds) Smart Cities. ICSC-CITIES 2019. Communications in Computer and Information Science, vol 1152. Springer, Cham. https://doi.org/10.1007/978-3-030-38889-8_2
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