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Gómez, M., Hidalgo, D.. (1393). New Strategy for a good Management and Control of Pollution Caused by urban Traffic. , 8(4), 1215-1222. doi: 10.22059/ijer.2014.828
M. Gómez; D. Hidalgo. "New Strategy for a good Management and Control of Pollution Caused by urban Traffic". , 8, 4, 1393, 1215-1222. doi: 10.22059/ijer.2014.828
Gómez, M., Hidalgo, D.. (1393). 'New Strategy for a good Management and Control of Pollution Caused by urban Traffic', , 8(4), pp. 1215-1222. doi: 10.22059/ijer.2014.828
Gómez, M., Hidalgo, D.. New Strategy for a good Management and Control of Pollution Caused by urban Traffic. , 1393; 8(4): 1215-1222. doi: 10.22059/ijer.2014.828

New Strategy for a good Management and Control of Pollution Caused by urban Traffic

International Journal of Environmental Research
مقاله 36، دوره 8، شماره 4، دی 2014، صفحه 1215-1222    اصل مقاله (978.59 K)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22059/ijer.2014.828
نویسندگان
M. Gómez* ؛ D. Hidalgo
Environment Area, CARTIF Technology Center, Parque Tecnológico de Boecillo, 205 – 47151Boecillo, Valladolid, Spain
چکیده
Pollution control is based on correctly measuring pollutant concentrations but, at the moment,
the principal European cities only monitor pollution levels by means of a few fixed stations co-located in
selected points of the urban layout far from hotspots and/or by means of meteorological prediction models of
future pollution. Few cities integrate the information from both sources. The implementation of wireless
sensor network provides an alternative solution by deploying a larger number of disposable sensor nodes and
it is the key that enable more flexible real-time environmental monitoring. This paper presents a new system
for sustainable traffic management by using models that predict pollution levels, which are fed with data,
gathered by the air quality sensors network and may help to take early action. This new system has been
implemented in Salamanca (Spain), thus allowing, to test in real urban environments the collection and processing
of data from 35 motes located in experimental roads during a year-round period. Monitoring results allow
building a database with the temporal evolution of the different environmental indicators registered. In general
the prediction model has an average error around 20% for predictions at one hour and 30% at three hours. The
results highlight the very good performance of the prediction model. The strategic approach proposed is
highly innovative and embodies great scientific and technological advances. The use and integration of measured
and modeled data thus becomes a key element in the future management of atmospheric pollution.
کلیدواژه‌ها
pollution control؛ Sensors network؛ Sustainable traffic management
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