High resolution mapping of air pollutants in cities based on wireless sensor networks

• Forschungsstelle: COST
• Projektnummer: C14.0085
• Projekttitel Englisch: High resolution mapping of air pollutants in cities based on wireless sensor networks

Schlüsselwörter (Englisch)

air quality; low-cost sensors; wireless sensor network; urban scale modelling; exposure estimation; urban planning; transport management

Forschungsprogramme (Englisch)

COST-Action TD1105 - European Network on New Sensing Technologies for Air-Pollution Control and Environmental Sustainability - EuNetAir

Kurzbeschreibung (Englisch)

The available knowledge on the relation between air pollutant concentrations and health effects is to a large extent based on epidemiological studies which rely on accurate estimates of the personal exposure. However, high quality exposure estimates are difficult to obtain, especially for air pollutants with a high spatial and temporal variability such as nitrogen dioxide, soot (or black carbon) and ultrafine particles. As a consequence, it is currently very difficult to find epidemiological evidence linking these air pollutants with health effects. This knowledge gap is especially relevant in the urban environment which inherently combines dense population and high variablity of air pollutants. In a recent study, we were able to present a modeling approach based on data from a network of small and inexpensive sensors and land-use information (GIS data) for estimation of air pollutant concentra-tions in the city of Zurich, Switzerland, with high spatial (10 m x 10 m) and temporal (30 minutes) resolution. In this project, we will advance the developed methodology and demonstrate its capabilities for personal exposure estimation and for applications in the field of urban air quality management.

Weitere Hinweise und Angaben (Englisch)

Full name of research-institution/enterprise: Empa - Swiss Federal Laboratories for Materials Science and Technology Senior Scientist - Head of Ambient Air Quality Group

Partner und Internationale Organisationen (Englisch)

AT; BE; BG; CZ; DK; FI; FR; MK; DE; EL; HU; IS; IE; IL; IT; LV; NL; NO; PL; RO; RS; SI; ES; SE; TR; UK; HR; RU; MA; UA

Abstract (Englisch)

Recent progress in sensor technology has led to inexpensive gas sensing devices which are capable for measuring air pollutants (gases and particles) at ambient concentrations. These devices allow the deployment of dense sensor networks, offering unique opportunities for air quality monitoring and air quality assessment, especially in cities where the air pollutant concentrations and the spatiotemporal variability of air pollutants are highest. However, air quality sensor networks can only provide meaningful information, when the data quality is sufficient and the measurement uncertainty of the individual sensors in the network is known. Today, knowledge about the quality of data from air quality sensors operated in networks at real-world conditions over an extended period of time is not available. This project investigates the potential of available low-cost sensors for urban air quality monitoring and the use of sensor-based data and geographic information in statistical models for mapping of urban air pollutants with high spatiotemporal resolution. Together with the Empa spin-off company Decentlab GmbH (Duebendorf, Switzerland), sensor units for the measurement of NO2 and O3 in ambient air have been developed. After a three month calibration period, where the sensors have been operated next to reference instruments, six sensor units were deployed in the city of Zurich forming a small wireless sensor network. For data quality control purposes, diffusive passive sampler tubes for NO2 were exposed next to the six sensor nodes providing 14-day average NO2 concentrations at the sensor locations. The established sensor network covers the whole range of urban air pollution situations and complements the six traditional air quality monitoring stations in the city of Zurich that are operated for regulatory purposes by the municipality and the federal authority. The data from the sensor network has been analysed for long-term stability of the individual sensors. Generic algorithms for quality assurance and quality control within air quality sensor networks have been developed and applied to the data. For example, algorithms for correction of sensor data based on the comparison of the sensor signal and the measurements at reference stations during time periods when the intra-urban variability of air pollutant concentrations is small (e.g. during the night) have been applied. Linkage of the sensor measurements to measurements from regulatory air quality monitoring sites proofed to be a necessary and a suitable method for analysing and even calibrating individual sensors. After thorough post-processing of the sensor data including correction for the interference to other trace gases and physical conditions (i.e. temperature and relative humidity), we found that the achieved accuracy is clearly below that of the diffusive passive samplers and not sufficient for reliable determination of the spatio-temporal variation of air pollutant levels in Zurich. Further improvements in sensor technology are required to bring low-cost sensor systems to a performance level which is sufficient for the described application.

Datenbankreferenzen (Englisch)

Swiss Database: COST-DB of the State Secretariat for Education and Research Hallwylstrasse 4 CH-3003 Berne, Switzerland Tel. [phone] Swiss Project-Number: C14.0085