Development of a High Spatial Resolution Sensor System for Monitoring Air Pollutants in Metropolitan Areas

An hexagonal close packed (hcp) network structure is used to minimize the distance to neighboring sensor nodes.
© Breitegger - TU Graz/ies
WHO estimated that one in eight deaths worldwide in 2012 was due to the effects of air pollution. According to the European environment agency (EEA), 90% of European city residents are exposed to higher pollution concentrations exceeding the air quality standards. The three most harmful pollutants are nitrogen dioxide (NO2), ground level ozone (O3) and particulate matter (PM). In this project the possibility of large-scale monitoring of NO2 and PM in metropolitan areas, utilizing an intelligent sensorsystem is investigated. The focus will be laid on an increased spatial resolution, as compared to present sensor systems. To achieve this, we will implement newest developments on the Internet of Things (IoT) and energy harvesting.

eMISSION

Due to substantial health effects, particulate matter emitted by motor vehicles is limited by legislation. To determine the emissions, the current legislation requires particle number concentration measurements during the type approval procedure for new vehicle types. Recently, it was shown that these tests do not reflect the real emission behavior of motor vehicles during their normal usage. Alternative examination methods like emission monitoring via Periodical Technical Inspections (PTI) or on-board emission testing (referred to as Real Driving Emissions (RDE)) would be much more reliable. However, due to a lack of appropriate measurement instrumentation, research on reliable as well as traceable sensor systems has to be done before the aforementioned methods can be applied. The aim of this project is to develop and validate a sensor principle for the determination of particle number concentration, which is based on electrical charging of the particles. As a result of the project, a sensor prototype that is lightweight, robust, energy efficient, cost-efficient and mobile should be designed.

Sensor Systems for Particle Emissions in Harsh Environment

The aim of this PhD Thesis is on one hand to give an overview about the different measurement methods regarding particle concentrations in harsh environment and on the other hand to generate a deeper understanding for selected methods. The label “harsh environment” refers to the surrounding of the measured particles (e.g. high/low temperatures, high particle densities, high flow rates etc.) and shall not focus the work on measuring principles for automotive applications. For the main part of the studied methods the work should restrain on a theoretical examination of their functionality and evaluation of the range of use. Selected measurement methods shall be examined in detail, involving design and buildup of one or more functional vehicles and an experimental characterization. With the findings an extensive theoretical description of the functionality, the range of use and especially of the physical principles should be created which shall exceed current state of research. Depending on the progress of the research, enhancements of the examined measurement principles and/or methods can be proposed respectively performed. Here the focus shall also be on the physical principals and their description within physical theories.

Time and Space Resolved Characterization of Nanoparticles

The dissertation aims to realize and validate a multi-physical sensorsystem to characterize nano particles with respect to particle density, particle size, particle velocity and particle wettability. This characterization is targeted to be performed in a time scale < 1s in real time. This includes:
  • simulating, realizing and optimizing a laser optical setup for in-situ detection of the holographic image of the dispersing phase,
  • identifying evaluation algorithms (e.g.: Find Circle/Elliptic Algorithm, Computer Vision Algorithm, Velocity Determination, ...), developing (further) and implementing in e.g.: MATLAB / LabVIEW and assessing systematically,
  • implementing these algorithms into real time sensorsystems (e.g.: NI cRIO Hardware Platform) for the detection of particle density, particle size, particle velocity and wettability,
  • validating the sensor system using model aerosols such as soot, NaCl, DOPS and referencing equipment like Condensed Particle Counter, Scanning Mobility Particle Sizer (SMPS), static light- or X-ray scattering.

Ultrasonic Sensor Principles for Flowmeters in Harsh Environment

State of the art flowmeters are often based on the determination of ultrasonic travel time. This principle relies on a known flow field which often has to be forced with flow rectifiers. The utilization of such flow rectifiers inevitably causes a pressure loss which effects the efficiency of the mass transport. Beside this fundamental problem of the measurement principle itself some arise with the practical implementation. The often used Piezo transceivers are not well suited for harsh environment with high humidity and high temperatures and therefore limit the application range of conventional flow meters. The first part of this work deals with the research on potential improvements of the ultrasonic measurement principle utilizing multi-physical simulation and their experimental validations. This includes the comparison of different transmitter receiver arrangements as well as the usage of acoustic wave guides to decouple the Piezo transceivers from the measured medium. Subsequently also alternative principles like the utilization of beamforming and the resulting possibilities to determinate the actual flow field acoustically (cf. Laser Doppler velocimetry) will be tested. The target of this research is a working prototype consisting of an appropriate control/analysis electronic system and a setup of the most, in terms of possible improvement over state of the art systems, promising principle which will be determined during this work.