Air pollution, in terms of toxic gas molecules and particulate matter in the air we breathe, is a major cause of morbidity and premature mortality, resulting in an estimated 4.2 million deaths per year. Real-time pollution monitoring, with highly-localised readings and public alerts, is vital to minimise the exposure of the population, particularly the vulnerable, to air pollution. Direct access to high quality, trustworthy data will allow optimisation of daily schedules to reduce exposure. The availability of actionable data which will, if necessary, stand up in court and with government, will drive long term changes in the behaviour of both the public and industry.
The ambient pollutant detectors currently used as reference measurements are impractical for widespread or mobile deployment, while miniature, low-cost electrochemical sensors generally are still not stable or sensitive enough for monitoring ambient pollutants reliably. The PASSEPARTOUT project will advance the development and deployment of miniature, hyperspectral optical based sensors, utilising Quartz Enhanced Photo-Acoustic Spectroscopy (QEPAS) and Photo-Thermal Interferometry (PTI) to detect a wide range of ambient pollutants. The PASSEPARTOUT optical sensors operate in the mid-infrared (MIR) or near-infrared (NIR) spectral range and allow calibration-free methodologies (since the quantification is based on the well-known optical constants of the target analytes) and will be compatible with the rigorous certification process.
PASSEPARTOUT will realise the first 3D mobile optical gas analyser network capable of operating in an urban area. Innovative and high-performance technologies for high accuracy and flexible environmental air quality monitoring will be built into robust drone-mounted, low-cost vehicle-mounted and stationary sensors. The network will provide real-time information about the concentration of polluting gases (such as NOx, SO2, NH3, CH4, CO and CO2) and black carbon particulates within urban areas, and around landfills and seaports, with extremely high precision and excellent spatial resolution.
