An Integrated System for Simultaneous Monitoring of Traffic and Pollution Concentration—Lessons Learned for Bielsko-Biała, Poland

Krzysztof Brzozowski, Artur Ryguła and Andrzej Maczyński
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Krzysztof Brzozowski: Department of Transport, Faculty of Management and Transport, University of Bielsko-Biala, Willowa 2, 43-300 Bielsko-Biała, Poland
Artur Ryguła: Department of Transport, Faculty of Management and Transport, University of Bielsko-Biala, Willowa 2, 43-300 Bielsko-Biała, Poland
Andrzej Maczyński: Department of Transport, Faculty of Management and Transport, University of Bielsko-Biala, Willowa 2, 43-300 Bielsko-Biała, Poland

Energies, 2021, vol. 14, issue 23, 1-18

Abstract: The challenge of maintaining the required level of mobility and air quality in cities can be met by deploying an appropriate management system in which the immediate vicinity of roads is monitored to identify potential pollution hotspots. This paper presents an integrated low-cost system which can be used to study the impact of traffic related emission on air quality at intersections. The system was used for three months in 2017 at five locations covering intersections in the centre of a mid-sized city. Depending on the location, pollution hotspots with high PM 2.5 and PM 10 concentrations occurred 5–10% of the time. It was shown that despite the close mutual proximity of the locations, traffic and the immediate surroundings lead to significant variation in air quality. At locations with adverse ventilation conditions a tendency towards more frequent occurrences of moderate and sufficient air quality was observed than at other locations (even those with more traffic). Based on the results, a practical extension of the system was also proposed by formulating a model for the prediction of PM 2.5 concentration using a neural network. Information on transit times, meteorological data and the background level of PM 10 concentration were used as model input parameters.

Keywords: low-cost sensors; traffic; air quality; pollution hotspots; transit time; neural network (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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