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Use of Low-Cost Air Quality Monitoring Devices for Assessment of Road Transport Related Emissions

Transportation research procedia(2019)

Tech Univ Munich | Hawa Dawa GmbH

Cited 2|Views2
Abstract
Comprehensive information on air quality is very important for development and assessment of air pollution reduction measures, especially for urban areas facing these problems. Such information is useful not only for monitoring of air quality levels but also for validation of air quality modelling tools. These tools are used, among many application fields, to assess road transport related air pollution as well as to investigate impacts of traffic management measures. Today, in addition to high precision monitoring stations in the cities, there are several low-cost monitoring devices available which can provide additional information on a larger area with less costs. This paper investigates the utilization of such devices as an additional data source for air quality assessment through a case study in the city of Munich and focuses on PM10 measurements. In this context, hourly PM10 values are measured with ten low-cost devices in the study area and it is checked if the measured values from devices capture general trends in air quality levels. Firstly, a statistical analysis is conducted which analyses officially reported historical PM10 concentrations, weather conditions and traffic data for the use case area from the year 2016. The analysis showed strong correlations between PM10 concentrations and background pollutant levels, wind conditions as well as traffic volumes. The evaluation focuses on investigation of whether the values from low-cost devices also showed similar trends as expected by the statistical correlations. The results represented some of the anticipated relationships, however, others could not be easily concluded. The experiment implies the importance of extensive measurement periods and frequent calibration of devices. In addition, the study demonstrates the difficulties of interpreting point measurement data in terms of causalities. Use of dispersion models can additionally help to understand the reasons of unexpected high or low concentrations at certain areas, as they consider complex relationships between factors affecting air quality such as meteorological conditions and the built structure.
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Air Quality Measurement,Low-Cost Devices,Assessment of Road Transport Related Emissions,PM10 Measurement
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