EPFL launched a pioneering project to detect pollen, dust and smoke

Prof. Nenes and postdoc Kunfeng Gao on the roof of MeteoSwiss building in Payerne - 2023 EPFL / Armand Goy - CC-BY-SA 4.0

Prof. Nenes and postdoc Kunfeng Gao on the roof of MeteoSwiss building in Payerne - 2023 EPFL / Armand Goy - CC-BY-SA 4.0

Since the start of this year, a suite of instruments has been hard at work detecting a broad spectrum of aerosols at the MeteoSwiss weather station in Payerne, in Vaud Canton. This pioneering project – a joint initiative between EPFL, the Swiss Federal Office of Meteorology Climatology and European partners – aims to improve pollen forecasting and to gain further insights into the critical impact that bioaerosols, smoke and dust have on cloud formation and climate.

Hay-fever sufferers will be acutely familiar with the Swiss Federal Office of Meteorology Climatology (MeteoSwiss) pollen maps and their shades of red and yellow. These forecasts play a vital role in guiding public-health measures, especially after Switzerland experienced record-high pollen counts this spring. In an effort to develop more detailed and accurate forecasting capabilities, various new instruments were installed at the Payerne upper air station at the start of this year. This marks the first time such instruments have been deployed simultaneously.

The research is being carried out jointly by MeteoSwiss, EPFL, the National Technical University of Athens (NTUA), and the Foundation for Research and Technology - Hellas (FORTH) and has received funding from the Swiss National Science Foundation, and the prestigious European Research Council through the EU’s Pyrogenic TRansformations Affecting Climate and Health (PyroTRACH) program. In addition to detecting a wider range of pollen types than in existing studies – thanks in part to the scientists’ pioneering work on vertical-laser remote sensing systems – this project is also investigating other causes of allergies and oxidative stress such as fungal spores, bacteria, dust and wildfire smoke, as well as methods to improve pollen forecasts and cloud formation.

On the left, Professor Papagiannis and, on the right, Professor Nenes in EPFL’s atmospheric container laboratory. © 2023 EPFL / Armand Goy- CC-BY-SA 4.0

LiDAR system for 3D measurements

In May of this year, a LiDAR system was set up in EPFL’s atmospheric container laboratory located near the entrance to MeteoSwiss’s main building. The LiDAR system consists of a UV-pulsed laser coupled with a receiver telescope and electro-optical instruments. Together, these technologies detect the light reflected by particles in real time. And at night, they pick up the “glow” generated by the laser when it strikes these particles. The resulting color spectrum serves as a unique “digital fingerprint,” signaling the presence of airborne pollen, fungal spores and bacteria, as well as smoke particles and dust, by way of fluorescence-based detection. There are only four instruments of this kind currently in operation worldwide, and all of them are still highly experimental; this new one is the most advanced in terms of capacity.

The LiDAR operating. ©2023 EPFL / LAPI- CC-BY-SA 4.0

The LiDAR signals are captured every 7 minutes, at a spatial resolution of 3.5 meters and a spectral resolution of 6 nanometers, and the instrument has a range of 2–3 kilometers in altitude, stretching as far as the free troposphere. And that’s not all: the new LiDAR system also features an extended spectral filter, meaning it can distinguish between biogenic particles (those produced by living organisms) and particles of other origins located between the ground and 4–5 kilometers up in the air. It has a temporal resolution of 3–5 minutes and can take 3D measurements, unlike existing instruments that can take only 2D measurements near the ground.

This groundbreaking system is the brainchild of Prof. Alexandros Papagiannis, who has four decades of research experience in this field. Formally affiliated with NTUA, Papagiannis is also a visiting professor at EPFL’s Laboratory of Atmospheric Processes and their Impacts (LAPI), headed by Prof. Athanasios Nenes. The two professors received an EPFL research-instrument grant and used the proceeds – along with funding from LAPI, the Swiss National Science Foundation and PyroTRACH – to acquire the base components of their LiDAR system and fund the campaign. In a nod to their Greek roots, they named their project PERICLES, short for “PayernE lidaR and Insitu detection of fluorescent biomass burning, bioaerosol and dust partiCLES and their cloud impacts.”

The measurements instruments of PhD student Sophie Erb. © 2023 EPFL / Armand Goy- CC-BY-SA 4.0

Machine learning and aerosol analysis

The roof of the Payerne weather station is home to many other instruments. They’re being monitored by Sophie Erb, a PhD student at MeteoSwiss and EPFL’s Environmental Remote Sensing Laboratory, and Kunfeng Gao, a postdoc at LAPI. Erb is keeping tabs on a camera that captures photos of pollen grains and fungal spores up to ten times per second. Once processed, the 3D images are fed into a machine, which is trained to identify which type of organism the particles come from, helping to improve pollen forecast maps.

The measurements instruments of postdoc Kunfeng Gao. © 2023 EPFL / Armand Goy- CC-BY-SA 4.0

Gao, meanwhile, is measuring the concentrations and sizes of different aerosols trapped in a small vial of flowing water known as a “wet cyclone.” This capture method is preferable to a filter because it can collect dust and other insoluble particles without destroying sensitive biological particles like bacteria. The particles are then frozen so that scientists can analyze their chemical and genomic composition and determine how the particles affect human health. This information also sheds important light on the process of ice formation in clouds – and therefore on precipitation. The sampling for PERICLES is being carried out in association with Kalliopi Violaki, LAPI scientist who specializes in analytical chemistry, atmospheric chemistry and bioaerosols.

Sophie Erb with the old pollen forecasting method, now being dismantled. At the time, it was necessary to wait a week between sample collection and map production. © 2023 EPFL / Armand Goy- CC-BY-SA 4.0

Wildfire smoke

The new LiDAR system can also identify the source of particles and measure quantities in the air in real time. In May and June, for instance, the instrument recorded high levels of smoke particles originating from the forest fires in Canada and the United States. More recently, the air over Switzerland became clogged with residue from the wildfires in Germany. “The health impact of these aerosols is vastly underestimated,” says Nenes, who is spearheading PERICLES. “That’s why it’s so important to get to the bottom of what’s really happening. We’re often clueless about what’s going on right over our heads, especially when it comes to bioaerosols and smoke particles.”

Nenes hopes that one day the team’s research could help scientists develop enhanced real-time maps to inform public-health policies. But even now, the new LiDAR system could bring about a step change in forecasting capabilities. “We’ve already identified significant room for improvement in current forecasting models,” explains Papagiannis. “Pollen counts change dramatically over the course of a single day, with the highest concentrations recorded in the daytime.”

EPFL’s atmospheric container laboratory is located near the entrance to MeteoSwiss’s main building. © 2023 EPFL / Armand Goy- CC-BY-SA 4.0
Funding

The Swiss National Science Foundation, the European Research Council, EU’s Pyrogenic TRansformations Affecting Climate and Health (PyroTRACH) program.


Author: Sandrine Perroud

Source: EPFL

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2023 EPFL / LAPI - CC-BY-SA 4.0
2023 EPFL / LAPI - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0
2023 EPFL / Armand Goy - CC-BY-SA 4.0

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