1. Introduction

Interests and concerns in bioaerosols have grown rapidly in recent years. Bioaerosols may play a significant role in every ecosystem including human society. Their biological-physical-chemical characteristics combined with organism are very sensitive and the ability to change properties according to circumstances also makes the effect more powerful and unpredictable. Dust storms include bioaerosols such as fungal spores, plant and grass pollens, and long-range atmospheric transport routes and concentrations shift through time due to climatic and geological changes [1]. Negative influences of bioaerosols on human societies in downwind environments may occur. Hay-fever patients of Japanese cedar in Japan exceed one-third of the population [2], concerns to Olympics athletes from high concentrations of aeroallergen of goosefoot, mugwort, Alternaria and Cladosporium [3], continuation of the risk of pathogenic avian influenza virus for juveniles of wild birds and mammals [4], emergency announcement of World Health Organization’s regarding the Coronavirus disease [5], and many other reports call attention to the negative influences of bioaerosols, but positive influences are also reported. In agriculture, microorganisms isolated from the soil, rivers or sea have been used to treat wastewater, produce ethanol and glycerol, and create fermented foods [6]. Maki, et al. were successful in producing “natto” [7], which is a very popular Japanese food, using bacteria named Bacillus subtilis collected in the atmosphere and inside the snow cover of mountain, the bacteria was transported by Asian desert dust (KOSA) [8]. Bioaerosols appear to have continuously influenced the formation of traditional food culture and will continue to have influences on food cultures and industries. A reduction in atmospheric CO₂ concentrations by dust aerosols and the promotion of phytoplankton growth by providing nutrients to oceans were also reported [9]. While there are many reports on bioaerosols, they were generally limited to some biocomponents representing a fraction of only about 1% of all total bioaerosols [10]. The magnitude of feedback of bioaerosols to the ecosystem and human society may depend on the aerosol type. Techniques and systems for identification of aerosol types are in demand.

2. Methodology

In clinical and medical areas, fluorescence methods such as FISH (fluorescence in situ hybridization) are used as analytical techniques for diagnoses. If this method can be incorporated into a lidar monitoring technique, monitoring of airborne bioaerosols using a lidar will become a reality. However, since the above fluorescence diagnosis is usually performed in a specific room where the sample material is stained/mixed with fluorescent dyes such as green protein or some biochemical reactants such as RPA (recombinase polymerase amplification) enzyme, this method is not applicable to lidar monitoring. This is because lidar monitoring target substances that are out of reach, and this is one of the features of lidar monitoring. On the other hand, it is well known that many substances emit (auto)fluorescence by irradiation of light. Fluorescence is emitted as the result of a transition of its internal energy that is unique and different for each substance, so every substance has its own fluorescence spectrum. This means that fluorescence can be an index of identification and its operation principle is similar to that of lidar monitoring because they both detect optical response of substances to laser (light) irradiation.

Fluorescent liders were not as common as Mie scattering liders. However, recent technological developments in optics, such as the combination of diversified laser equipment and spectroscopic detection systems, have enabled simultaneous emission and detection of multiple wavelengths, expanding the range of fluorescence lidars to ecological research, such as insect, migratory bird, and fish movement monitoring [11], agricultural plant growth monitoring using a mobile fluorescence lidar [12], aquatic environment monitoring with a drone [13]. We constructed a mobile laser induced fluorescence spectrum (LIFS) lidar using a 355 nm laser and made several fluorescence observations at different locations such as forests [14], lakes [15], and residential areas [16] that demonstrated the importance to get information on local areas. However, some natural targets such as trees, soils, and organisms excited by only one wavelength of 355 nm might show similar fluorescence spectral shapes and it was sometimes difficult to clarify the differences. This strongly suggested the use of multi-wavelength excitation. This approach is common in biophotonics [17][18], but is not frequently used in fluorescence lidars. In this paper, we propose the use of an EEM (Excitation-Emission-Matrix) fluorescence dataset that consists of multiple fluorescence spectrum information corresponding to each of the multiple excitations, and study the usefulness of its application to lidar bioaerosol monitoring by a simulation experiment using a simple EEM fluorescence lidar which we have constructed. It should be noted that trials of identifying aerosol type using a lidar that fuses information on Mie depolarization, Raman scattering, and fluorescence has been reported [19–21].

3. EEM fluorescence measurement

Three pollens of Japanese cedar, ragweed, and apple were prepared for the study. They are typical bioaerosols found in our surroundings. The first and second pollens are the substances that cause hay fever in spring and in autumn, respectively. These are representative substances that have negative effects to our life. The third one is essential for horticulture and apples are one of main agricultural products in our area (Nagano, Japan), a positive effective substance. If a lidar can follow their behaviors in the air, the benefit will be great for human society. The cedar pollen and the apple pollen were purchased from vendors (Miyaso-kahun-kennkyukai, Kujigun, Ibaraki, Japan) and (Hoshino Co., Ltd. Niigata City, Niigata, Japan), respectively, and the ragweed pollen was collected by ourselves around in local surroundings. Fluorescence spectrum measurements of these substances were made using a commercial fluorescence spectrometer (F7000, Hitachi High-Tech Science Corporation, Minato-ku, Tokyo, Japan). Each type of pollen was placed in a stainless-steel cell with a non-fluorescent quartz window of 12 mm diameter, and was irradiated by light coming from the spectrometer light unit at an incident angle of 45 degrees. The wavelength of the continuous-wave (CW) light from the unit to excite the pollen was selected with a diffraction grating and changed from 300 nm to 540 nm with 2 nm spectral width in increments of 10 nm. The fluorescence spectral measurement was done using the spectrometer detection unit in which a diffraction grating and a photomultiplier tube (PMT) were assembled. Several long-pass filters (SCF-50S series, SIGMAKOKI Co., Ltd., Hidaka, Saitama, Japan) were put between the cell and the spectrometer detection unit to cut the excitation wavelength scattered by the surfaces of the cell window and pollen. Therefore the actual measurement range started at a wavelength about 20 nm longer where fluorescence can pass the filter, but block the excitation wavelength. The filter changes were done manually corresponding to the excitation wavelength.

Figure 1 displays the EEM fluorescence of each pollen type. As shown in the figure, it is easy to see the difference of pollen kinds by just looking at the EEM fluorescence patterns. Pollens of apple, apricot, and peach were difficult to identify because they showed very similar patterns [16]. It should be added that their scientific classification from clade, order, to family are the same as Rosids, Rosales, and Rosaceae [22]. If we only look at fluorescence induced by 355 nm excitation that is a popular wavelength of fluorescence lidars, we were not able to obtain enough information for identifying the kind. Fluorescence spectra of cedar and apple resembled each other and their peaks appeared in the same region at around 450 nm. In our previous experiment using only 355 nm excitation, pollens of locust tree and Japanese black pine also appeared at around 450 nm [14] and the peaks of fluorescence spectrum of many substances including natural and artificial ones appeared from 450 nm to 500 nm [16]. The 355 nm wavelength seemed preferable in the case of detection of ragweed and apple if we only consider the fluorescence intensity. Cedar pollen had a higher fluorescence intensity than those of the other two pollens in the case of 532 nm excitation which is the most popular wavelength for lidars and with 355 nm excitation it showed a bit higher intensity among the three but not good enough to identify them. Fluorescence intensity might be one of indices for identification, but it is not of critical relevance compared with EEM fluorescence because lidar detection intensity depends on the concentration.

 

Fig. 1. EEM fluorescence of cedar, ragweed and apple pollen measured with a fluorescence spectrometer. Each is expressed relatively to its maximum intensity. Pollen images were recorded using a laser microscope (VK-9500, Keyence, Osaka City, Japan).

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4. EEM fluorescence lidar simulation experiment

4.1 System

A compact EEM fluorescence lidar (Fig. 2) was constructed to show the usefulness of the EEM fluorescence in lidar observations. The possibility of detection and identification of bio aerosols using pollens was investigated by lidar simulation experiments. Cedar pollen and apple pollen were the same ones as those used in the EEM fluorescence measurement. Ragweed pollen was newly purchased from a vendor (Biostir Inc. Osaka City, Osaka, Japan). Pollens were placed in a rectangular quartz cell with four clear windows that had an exterior height of 45 mm and 10 mm width. Each type of pollen was irradiated by each of three laser diodes (LDs) (TC-20 series, Neoark, Hachijoji, Tokyo) or one light emitting diode (LED) (MODEL 325-FL-01-G02 manufactured by Dowa, Chiyoda-ku, Tokyo, assembled by Neoark) and the wavelengths were 520 nm±5 nm, 445 nm±5 nm, 405 nm±5 nm and 325 nm±24 nm, respectively (see right side on Fig. 1). A short-pass filter having a cut-off tolerance of ±1% (#84 series, Edmund Optics, New Jersey, USA) was inserted in front of the output to ensure the rejection of undesired non-laser emissions of the LDs that would possibly overlap the fluorescence. For the LED, no filters were used because we could not find a standard product that worked well in the wavelength range. The distance between the cell and the excitation source was 2 m. Each LD had a collimator inside the unit and the beam directly irradiated the pollens with a 10 mm laser spot. Since the total viewing angle of the LED was large, about 130 degrees, we reduced the angle by inserting a quartz lens in front of the output. However, because it was hard to improve the spot size to be smaller than the cell width, a pinhole with a diameter of 6 mm on a stainless-steel plate with a thickness of 0.5 mm was placed between the cell and the LED, and the beam spot on the cell was finally the same as the cell width. The powers measured (OPTICAL SENSOR 9742 and OPTICAL POWER METER 3664 and 9742, Hioki E.E. Corp., Ueda City, Japan) on the cell surface were 30.0 mW at 520 nm, 17.5 mW at 445 nm, 34.3 mW at 405 nm, and 0.3 mW at 325 nm. As a lidar receiver, a commercial ultra violet camera lens (UV-Nikkor, Nikon Corporation, Minato-ku, Tokyo) with 24 mm diameter and 70% transmittance in the region of 220-900 nm collected fluorescence. The distance between the cell and the camera lens was 2 m. The fluorescence was sent to a spectral detection unit of the F7000 fluorescence spectrometer through a bundle fiber (BF20HSMA, Thorlabs Inc., New Jersey, USA) available in the region of 250 nm-1200 nm collecting light at the focus point of the camera lens. In the experiments using LDs, the same filters we used in the EEM fluorescence measurement were inserted between the outlet of the fiber and the entrance of the detection unit. In LED experiments (325 nm), a long-pass filter (ITY 385, Isuzu Glass LTD., Sano City, Osaka, Japan) was used to reject the envelope of the LED spectrum that might extend beyond 370 nm. The filter had a steeper transmission curve than normal filters, that is cut-on wavelength is 385 nm with a 1.8% slope as shown in Fig. 2.

 

Fig. 2. Layout of EEM fluorescence lidar simulation experiment. L: lens, SF: short-pass filter, PH: pinhole, CL: camera lens, OF: optical fiber, SD: spectrometer detecting unit, LF: long-pass filter, DG: diffraction grating, M: mirror, PMT: photomultiplier tube, PC: personal computer. The graph on the right is a characteristic of the filter used in the LED experiment drawn by ourselves using data from the manufacturer.

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4.2 Result

The experimental results are summarized in Figs. 3 and 4. The fluorescence spectra in Fig. 3 are raw signals without correction for excitation power. The fluorescence of cedar pollen highly depended on the excitation wavelength. That of ragweed pollen showed a great increase in the case of 325 nm excitation. The data of Fig. 3 were corrected for the excitation power and expressed relatively with the peak intensity of each pollen fluorescence to compare with Fig. 1. We can see that the results of the lidar simulation experiment (Fig. 4) and the EEM fluorescence (Fig. 1) are consistent. On the point of system configuration, it would be better to obtain data excited at around 360 nm to show the difference among the three. We could not get such LD equipment at that time and this will be discussed in the next section.

The large peak at 440 nm of ragweed pollen excited with 325 nm that appeared in the EEM fluorescence was not found. Detailes of the reason have not cleared, but there are several things that may be of concern. The large spectral width of 48 nm of the LED contained a shorter wavelength than 325 nm and its high photon energy might result in the difference, such as photobleaching. We frequently moved the irradiated position and replaced the pollen with new one in order to minimize the influence of bleaching, although. The fluorescence spectrum of ragweed pollen induced at 325 nm had two peaks at 440 nm and 525 nm (see Fig. 1), which means that there are two different fluorophores. In general, short-wavelength-fluorescence emission requires higher excitation energy than long-wavelength-fluorescence one. That is, the fluorophore associated with 440 nm-fluorescence could have been easily bleached under the influence of the high photon energy contained in the shorter wavelength region of the LED. On the other hand, the spectral width of light used in the EEM fluorescence measurement was 2 nm and we could obtain pure fluorescence not affected by other (shorter) wavelengths than the intended excitation wavelength. The ragweed pollen used for EEM fluorescence measurement was collected by ourselves in our local surroundings at the end of August, and the EEM fluorescence measurement was done soon after that. Otherwise the ragweed pollen we used for the lidar simulation experiment was provided as freeze-dried products from the vendor and was stored for one year in a desiccator at normal temperature and moderate room light condition in our laboratory. It is necessary to investigate more precisely if the properties of pollen change or not depending on the varieties even if they are the same type and status of activation (fresh/old). Differences/changes in fluorescence spectrum were reported even in the same type depending on geographical origin [23][24], increasing geological age [25], alive or dead status [26]. On the other hand, the ragweed pollen fluorescence spectrum monitored at a local field by our mobile LIFS lidar coincided quite well to that collected at the same field and measured in the laboratory using a fluorescence spectrometer just after the lidar measurement [14]. To understand the magnitude of feedback of bioaerosols to human society and to be free from the threats of bioaerosols in downwind environments, local and real-time information is of utmost importance. That is what lidar observation does best.

 

Fig. 3. Raw fluorescence spectrum of cedar, ragweed and apple pollens measured by the fluorescence lidar. Data are not corrected with excitation power. The spectrum for 325 nm excitation is shown in the figure to the right.

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Fig. 4. EEM fluorescence of cedar, ragweed and apple pollen measured in the fluorescence lidar simulation experiment. Each is expressed relatively to its maximum intensity.

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5. Discussion regarding construction of an EEM fluorescence lidar system

Considering the actual operation of EEM fluorescence systems, it seems realistic to set two measurement regions, one for short-range lidar measurement and one for in-situ measurement. In the former case, measurements within the troposphere for heights below 100 m are suitable, where there are many natural substances that generate bioaerosols and artificial substances that adsorb them, and they easily spread by strong convection in our living areas. The combination of a high power pulsed solid optical parametric generator (OPG)/optical parametric oscillator (OPO) light source that can tune to any wavelength continuously, and a multichannel spectrometer using a gate-typed charge coupled device (CCD)/complementary metal–oxide–semiconductor (CMOS)/multianode PMT detector is a reliable system. For this configuration, the gate function is powerful enough to get range information and also reduces back-ground noise of sun light. Another potential combination is CW He-Cd/Ar/Kr/He-Ne lasers whose wavelengths are discrete but can cover the range from 325 nm to 543 nm, and a CW detection system like the fluorescence spectrometer used in this experiment. In this CW measurement, a configuration using a bistatic imaging lidar [27] is suitable to get range information. For the latter case, close monitoring using a drone type EEM fluorescence lidar is expected. Many types of LDs that can cover from ultraviolet to visible regions and micro electro mechanical systems (MEMS) type spectrometers whose volumes are less than10 cm³ are ideal for loading on drones. The development of LDs that operate in the UV region with a spectral width of less than a few nm and a beam divergence of less than 1 mrad is also required. Wavelengths shorter than 300 nm may have great opportunities in bioaerosol detection [28].

6. Conclusion

The fluorescence lidar simulation results of this work could demonstrate the usefulness of EEM fluorescence data. An EEM fluorescence lidar offers many potential uses. Aside from applications to atmospheric science that have traditionally been the main purpose of lidar monitoring, the EEM fluorescence lidar focuses on investigations of the livingsphere [29] close to our lives such as pollen dispersal forecasts, watch-dog station of airborne microorganisms from livestock facilities [30], etc. Bacterial and virus detection in crowded confined facilities is most urgent. Feasibility of Corona-virus detection using fluorescence techniques have also been reported [31–34]. Fluorescence lidars will be powerful systems because operators can complete measurements without approaching the infected area.