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

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 PM2.5 and PM10 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 PM2.5 concentration using a neural network. Information on transit times, meteorological data and the background level of PM10 concentration were used as model input parameters.

Keywords

• low-cost sensors
• traffic
• air quality
• pollution hotspots
• transit time
• neural network