Alain Miffre

While atmospheric particles are ubiquitous in nature and contribute to the Earth’s radiative budget, their backscattering and extinction remain insufficiently quantified due to their complexity in size, shape and chemical composition. In this paper, a novel laboratory methodology is proposed to evaluate the particle extinction-to-backscatter ratio or lidar ratio of aerosols. This methodology, called LR-lab, is based on a robust light backscatter experiment at 180.0° angle, enhanced with a cavity ring down experiment to evaluate the particle extinction. No assumption is required on the particle size, shape, nor complex refractive index. Our methodology is validated on homogeneous spherical water droplets, which follow the analytical Mie theory, for different water droplets sizes and number concentrations. The particle extinction-to-backscatter ratio of mineral dust, a heterogeneous mixture of non-spherical particles, is then evaluated at 532 nm wavelength in laboratory. The dust lidar ratio is found to be equal to (47 ± 2) sr while the dust depolarization ratio is equal to (33.6 ± 0.4) %. By proposing a combined laboratory evaluation of the particle lidar and depolarization ratios, we believe our methodology can meet the growing need for lidar-based aerosol typing and for validation of light scattering numerical models on complex-shaped particles.

An inter-laboratory comparison (ILC) involving optical particle size spectrometers (OPSSs) was organised at the French national level. The aim of this study was to make an inventory of the metrological capabilities of particle number size distribution (PNSD) measurements using OPSSs. This laboratory study was conducted over an 18-month period and involved 16 partners and 35 OPSSs. This large number of instruments provides strong statistical weight to the dataset, offering robust insight into the overall instrumental capabilities of accurately and reliably measuring PNSD. For that, each partner applied the same pre-defined experimental protocol to the OPSS(s) to be tested, operated together with a common control OPSS. Three different test aerosols were involved, and their PNSDs were measured: (1) a monodisperse amorphous silica sample, (2) glass beads, and (3) a green cornstarch powder. This article presents the measured PNSD using the 35 OPSSs associated with the description of the experimental set-up, sample preparation protocol, and comparison with scanning electron microscopy measurements.

An inter-laboratory comparison (ILC) involving optical particle counters (OPCs) was organized at the French national level. The aim of this study was to make an inventory of the metrological capabilities of particle number size distribution (PNSD) measurements using OPCs. This laboratory study took place over a period of 18 months and involved 16 partners and 35 OPCs. Rather than focusing on the actual capability of the tested OPCs, this paper aims to reveal good laboratory practices when using standard OPCs. For that, each partner applied the same pre-defined experimental protocol on the OPC(s) to be tested, operated together with a common control OPC. Three different powder-borne test aerosols were involved, and their PNSDs were measured: (1) – a monodisperse amorphous silica sample, (2) – glass beads and (3) – a green cornstarch powder. This article presents the measured PNSD using the 35 OPCs associated with the description of the experimental set-up, sample preparation protocol and comparison with Scanning Electron Microscopy measurements.

Polarization optics, which characterize the orientation of the electromagnetic field through Stokes vectors formalism, have been effectively used in lidar remote sensing to detect particles that differ in shape, such as mineral dust or pollen. In this study, for the first time, we explore the capability of polarization optics to distinguish the light-backscattering patterns of pollen and fungal spores, two complex-shaped particles that vary significantly in surface structure. A unique laboratory polarimeter operating at lidar backscattering at 180.0° was conducted to assess their light depolarization property in laboratory ambient air. If, at the precise lidar backscattering angle of 180.0°, the depolarization ratios of pollen and fungal spores were difficult to differentiate, slight deviations from 180.0° allowed us to reveal separate scattering matrices for pollen and fungal spores. This demonstrates that polarization optics can unambiguously differentiate these particles based on their light-(back)scattering properties. These findings are consistent at both 532 and 1064 nm. This non-invasive, real-time technique is valuable for environmental monitoring, where rapid identification of airborne allergens is essential, as well as in agricultural and health sectors. Polarization-based light scattering thus offers a valuable method for characterizing such atmospheric particles, aiding in managing airborne contaminants.

In this paper, the dependence of the particles' depolarization ratio (PDR) of mineral dust on the complex refractive index and size is for the first time investigated through a laboratory π-polarimeter operating at 180.0^∘ backscattering angle and at (355, 532) nm wavelengths for lidar purposes. The dust PDR is indeed an important input parameter in polarization lidar experiments involving mineral dust. Our π-polarimeter provides 16 accurate (∘ corresponding to four different complex refractive indices, studied at two size distributions (fine, coarse) ranging from 10 nm to more than 10 µm and at (355, 532) nm wavelengths while accounting for the highly irregular shape of mineral dust, which is difficult to model numerically. At 355 nm, the lidar PDR of coarser silica, the main oxide in mineral dust, is equal to (33±1) %, while that of coarser hematite, the main light absorbent in mineral dust, is (10±1) %. This huge difference is here explained by accounting for the high imaginary part of the hematite complex refractive index. In turn, Arizona dust exhibits higher depolarization than Asian dust, due to the higher proportion in hematite in the latter. As a result, when the strong light-absorbent hematite is involved, the dust lidar PDR primarily depends on the particles' complex refractive index, and its variations with size and shape are less pronounced. When hematite is less or not involved, the dust lidar PDR increases with increasing sizes, though the shape dependence may then also play a role. The (355, 532) nm wavelength dependence of the dust lidar PDR then allows discussing on the involved particle sizes, thus highlighting the importance of dual-wavelength (or more) polarization lidar instruments. We believe these laboratory findings will help improve our understanding of the challenging dependence of the dust lidar PDR with complex refractive index and size to help interpret the complexity and the wealth of polarization lidar signals.

In this paper, the dependence of the particles depolarization ratio (PDR) of mineral dust on the complex refractive index and size is for the first time investigated through a laboratory π-polarimeter operating at 180.0° backscattering angle and at (355, 532) nm wavelengths for lidar purposes. The dust PDR is indeed an important input parameter in polarization lidar experiments involving mineral dust. Our π-polarimeter provides sixteen accurate values of the dust lidar PDR at 180.0° corresponding to four different complex refractive indices, studied at two size distributions (fine, coarse) and at (355, 532) nm wavelengths, while accounting for the highly irregular shape of mineral dust, which is difficult to model numerically. At 355 nm, the lidar PDR of coarser silica, the main oxide in mineral dust, is equal to (33±1) % while that of coarser hematite, the main light absorbent in mineral dust, is (10±1) %. This huge difference is here explained by accounting for the high imaginary part of the hematite complex refractive index. In turn, Arizona dust exhibits higher depolarization than Asian dust, due to the higher proportion in hematite in the latter. As a result, when the strong light absorbent hematite is involved, the dust lidar PDR primarily depends on the particles complex refractive index and its variations with size are less pronounced. When hematite is less or not involved, the dust lidar PDR increases with increasing sizes and the (355, 532) nm wavelength dependence of the dust lidar PDR then allows discussing on the involved particle sizes, thus highlighting the importance of dual-wavelength (or more) polarization lidar instruments. We believe these laboratory findings will help improving our understanding of the challenging dependence of the dust lidar PDR with complex refractive index and size to help interpret the complexity and the wealth of polarization lidar signals.

While pollen is expected to impact public human health and the Earth’s climate more and more in the coming decades, lidar remote sensing of pollen has become an important developing research field. To differentiate among the pollen taxa, a polarization lidar is an interesting tool since pollen exhibit non-spherical complex shapes. A key attribute is thus the lidar particle depolarization ratio (PDR) of pollen, which is however difficult to quantify as pollen are large and complex-shaped particles, far beyond the reach of light scattering numerical simulations. In this paper, a laboratory π-polarimeter is used to accurately evaluate the PDR of pure pollen, for the first time at the lidar exact backscattering angle of 180.0°. We hence reveal the lidar PDR of pure ragweed, ash, birch, pine, cypress and spruce pollens at 355 and 532 nm lidar wavelengths, as presented at the ELC 2021 conference. A striking result is the spectral dependence of the lidar PDR, highlighting the importance of dual-wavelength (or more) polarization lidars to identify pollen taxa. These spectral and polarimetric fingerprints of pure pollen, as they are accurate, can be used by the lidar community to invert multi-wavelength lidar polarization measurements involving pollen.

Pollen is nowadays recognized as one of the main atmospheric particles affecting public human health as well as the Earth's climate. In this context, an important issue concerns our ability to detect and differentiate among the existing pollen taxa. In this paper, the potential differences that may exist in light scattering by four of the most common pollen taxa, namely ragweed, birch, pine and ash, are analysed in the framework of the scattering matrix formalism at two wavelengths simultaneously (532 and 1064 nm). Interestingly, our laboratory experimental error bars are precise enough to show that these four pollen taxa, when embedded in ambient air, exhibit different spectral and polarimetric light-scattering characteristics, in the form of 10 scattering matrix elements (5 per wavelength), which allow each to be identified separately. To end with, a simpler light-scattering criterion is proposed for classification among the four considered pollen taxa by performing a principal component (PC) analysis, which still accounts for more than 99 % of the observed variance. We thus believe this work may open new insights for future atmospheric pollen detection.