Abstract

Bioaerosol, a significant constituent of the atmosphere, exhibits excellent broadband extinction performance and has attracted increasing attentions in the fields of atmospheric science, environmental science and electromagnetic field, et al. Relative humidity of the atmosphere has obvious diurnal and seasonal variation characteristics, and the frequent variation of relative humidity has a significant impact on bioaerosol in the atmosphere. However, the influence of relative humidity on broadband extinction performance of bioaerosol is unclear. Herein, we present the humidity growth model of bioaerosol. And the variation law of broadband extinction performance of bioaerosol in different humidity conditions was obtained by simulation. The simulation results and experimental data from an aerosol chamber experiment show that as the relative humidity values above 70%, the broadband extinction performance of bioaerosol will be increased with humidity. As the relative humidity increases from 70% to 90%, the extinction performance of AN0913 spores increase about 30% in visible and mid-infrared bands, about 20% in ultraviolet and far-infrared bands. And the extinction performance of AO0907 spores increase about 23% in the all four bands.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. Introduction

Bioaerosol, a significant constituent of atmosphere, is emitted from marine and terrestrial ecosystems or produced and released into the atmosphere by human production and life. Bacteria, microbiome spores, fungi, viruses, pollens and algae ranging in size from 10 nm to 100µm [1] are several kinds of typical bioaerosol particles. Bioaerosol particles absorb and scatter solar radiation, which directly changes the energy budget of the ground-atmosphere system and affects climate change [2]. On the other hand, bioaerosol is an effective absorber and scatterer of electromagnetic radiation energy so that they have an impact on people's use of electromagnetic waves. Therefore, bioaerosol has attracted increasing attentions in the fields of atmospheric science, environmental science and electromagnetic field, et al. Hu et al. [3] found that bioaerosol has significant wideband extinction capability in ultraviolet (UV) to infrared bands through theoretical calculation and experimental verification, providing a new direction for the development of wideband optical attenuation materials.

As is known to all, relative humidity of the atmosphere has obvious diurnal and seasonal variation characteristics, and the frequent variation of relative humidity has an important impact on the extinction performance of bioaerosol in the atmosphere. According to Mie scattering theory, the extinction coefficient of bioaerosol mainly depends on its particle size distribution and refractive index. With the increase of relative humidity, the bioaerosol particles will absorb water so that their physical properties such as particle diameter, refractive index and density will be changed, and their scattering and absorption capacity will be changed accordingly [4]. So the extinction coefficients of bioaerosol are sensitive to the change of relative humidity, the effects of relative humidity on bioaerosol cannot be ignored when calculating the extinction performance.

The theoretical and experimental results in literatures [58] show that the increase of moisture absorption of aerosol particles can improve the scattering ability of particles, and the stronger the hydrophilic ability of aerosol particles, the greater the influence on the scattering coefficient. However, so far, there are few theoretical studies on the relationship between extinction coefficients of bioaerosol particles and relative humidity. The effects of moisture absorption on the extinction performance of bioaerosol particles in wide band have not been studied. Here, we presented the humidity growth model of the bioaerosol particle size and complex refractive index. Based on the discrete-dipole approximation (DDA) model, Monte Carlo algorithm and laboratory experiment results, we studied on the broadband extinction performance of bioaerosol in various environmental relative humidity conditions.

2. Material and methods

2.1 Materials preparation

Microbial materials are the main components of bioaerosol. AN0913 spores and AO0907 spores are two kinds of the common microbial materials, which are easy to be prepared and can be produced in large quantities. It has been known in previous studies that they have significant broadband extinction performance [3]. Thus, in this paper, these two materials were devoted to study the broadband extinction performance of bioareosol in various relative humidity conditions. Agglomerated particle swarm of their spores was used for simulated numerical calculation, and an aerosol chamber experiment was carried out using these materials.

The bioaerosol materials used in this experiment were provided by the Key Laboratory of Ion Beam Bioengineering, Chinese Academy of Sciences. They optimized the fermentation conditions to improve the collection efficiency for the bioaerosol materials production [911]. The operating steps are as follows: bacterial species activation→shake flask culture→large-scale tank fermentation→centrifugation→pure water cleaning→vacuum freeze-drying→crushing with a ultra-fine Chinese medicine crusher. The materials were stored in a petri dish containing silica gel desiccant and kept at room temperature so that they were suitable to study the effects of humidity on their extinction performance. Electron micrographs of these two materials shot by scanning electron microscopy are shown in Figs. 1(a) and 1(b). As can be seen, these two kinds of spores are approximately spherical in shape. With the measurements and records by electron microscope, it was found that the spores had a particle size range: 1∼2.5µm, and an average radius of 1.5µm. They have obvious bumps on the surface and gathered in clusters.

 

Fig. 1. Structures of bioaerosol. (a, b) Electron micrographs of AN0913 spores and AO0907 spores. (c) Agglomerated particle structures constructed by the cluster-cluster aggregation model to describe the structures of the bioaerosol materials when they are floating in space.

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2.2 Complex refractive index calculation methods

The complex refractive index (CRI) is a significant parameter that characterizes the optical properties of bioaerosol materials. In general, the CRI is represented as m=n+ik, n represents the real part, which is the ratio of the speed of light in a vacuum to the speed of light in the material, and k indicates the imaginary part, which is an absorption coefficient characterizing the ability of the material to absorb light.

We calculated CRI of bioaerosol materials in the 0.2–14µm waveband using the reflection spectra of materials and the Kramers-Kronig (K-K) algorithm. In order to measure the reflection spectra of the aforementioned two bioaerosol materials, several steps were carried out: materials smashing, samples tablets producing and reflectance measurement. In the 200 nm to 2.5µm waveband, the reflectance was measured by a spectrophotometer. A 1 cm thick BaSO4 cylinder was used as a base calibration. In the 2.5µm to 14µm band, a Fourier transform infrared spectrometer with a microscope was used to measure the reflectance and a gold-plating reflective mirror was used as the background.

With the measured data of reflection spectra, the CRI of the two bioaerosol materials in the 0.2–14µm waveband were calculated by the Kramers-Kronig (K-K) algorithm [1215]. Our teammates have used this method several times to calculate the CRI of biological materials [1625].

2.3 Effects of relative humidity on bioaerosol materials

The effects of relative humidity on bioaerosol are mainly reflected in the influence on CRI and particle size [26]. CRI is a parameter describing the interaction between electromagnetic radiation and materials. In general, the CRI of bioaerosol materials in a determined relative humidity condition is jointly determined by dry bioaerosol materials and the liquid water congealed, and is often expressed by the CRI of equivalent homogeneous spherical particles. Hänel [27] obtained the empirical formula between the complex refractive index of the equivalent uniform spherical particle and the relative humidity through a lot of theoretical and experimental studies:

$$m = {m_w} + ({m_0} - {m_w}){(\frac{{{r_0}}}{{{r_{RH}}}})^3},$$
where m is the CRI of bioaerosol, and the subscripts w and $0$ represent water and dry bioaerosol particles respectively. ${r_0}$ is the radius of dry bioaerosol particle, ${r_{RH}}$ is the radius of wet bioaerosol particle. When the relative humidity is $RH$, the empirical relationship between the radius ${r_{RH}}$ of wet bioaerosol particles and the radius ${r_0}$ of dry bioaerosol is as follows:
$$\frac{{{r_0}}}{{{r_{RH}}}} = {(1 - RH)^{ - {\raise0.7ex\hbox{$1$} \!\mathord{\left/ {\vphantom {1 u}} \right.}\!\lower0.7ex\hbox{$u$}}}},$$
where $u$ is a constant coefficient, for the continental clean aerosol particles, the hygroscopicity of the bioaerosol is poor and the coefficient $u$ = 5.8; For marine aerosol particles, aerosol has strong hygroscopicity and the coefficient $u$ = 3.9; The bioaerosol particles studied in this paper have a strong hygroscopicity, and the coefficient u values between the two values mentioned above, with a value of 4.2.

With these theoretical formulas, the humidity growth model of the bioaerosol particle size and CRI can be built to study the effects of relative humidity on bioaerosol materials.

2.4 Bioaerosol spatial structure and multi-humidity extinction calculation model

Bioaerosol is composed of biological particles, which are often not monomers, but random amorphous aggregated particle systems with complex spatial structures formed by small unit particles due to static electricity, collision, adhesion, and the like. As in our previous works [3,2830], the original particles of an agglomerated particle were assumed to be spherical, the diameter of the original particles and the number of original particles in a single bioaerosol agglomerated particle was set to be 1.5µm and 50, respectively. The geometry of bioaerosol agglomerated particle was computed with the cluster–cluster aggregation (CCA) model [31].

The DDA method is an approximation method for solving the volume integral equation of electromagnetic scattering. It is one of the important methods to study the scattering characteristics of particles. The basic principle of the DDA method is to approximate the actual particles with an array of finite discrete and interacting small dipoles. Each point obtains a dipole moment by responding to local electric fields (incident field and radiation fields at other points), and the sum of far-field radiation from all points on the scatterer constitutes a scattering field. As long as the condition $|{m - 1} |\le 3$ is satisfied, the DDA method is applicable to scatterers of any geometric shape, and the scatterers can be anisotropic and non-uniform [32].

According to the results shown in Fig. 3, the CRI of the two bioaerosol materials we study in this research meet the requirements of DDA method. Thus, the DDA method was used to calculate the broadband extinction coefficients of bioaerosol particles with spatial structures in various relative humidity conditions.

The theoretical principle and calculation formula of DDA method are given in literatures [3335]. And with this method, the scattering cross section ${C_{sca}}$ and absorption cross section ${C_{abs}}$ of bioaerosol agglomerated particles can be calculated. In addition, the density of the bioaerosol agglomerated particles in an agglomerated particle swarm and the optical length through the swarm were set to be $\rho$ and L, respectively. All agglomerated particles were assumed to be evenly distributed in the particle swarm and randomly oriented. With all these parameters, the transmittance, the absorbed fraction and the scattered fraction of incident light through the bioaerosol agglomerated particle swarm can be simulated with the Monte Carlo algorithm [36].

Since the open source DDA code on the network requires lots of manual input of parameters each time so that it is impossible to calculate the broadband extinction coefficients in various humidity conditions. Thus, the entire calculation process was packaged in Python so that we can calculate the broadband extinction performance of bioaerosol in short time. With these results, taking the humidity growth model of the bioaerosol particle size and complex refractive index into account, the broadband extinction performance of bioaerosol in various humidity conditions can be calculated.

2.5 Transmittance experiment of bioaerosol in the aerosol chamber

As show in Fig. 2, in order to perform the transmittance experiment, we designed an aerosol chamber (4 m × 3 m × 2.4 m). Four pairs of light sources and detectors were placed to measure the broadband transmittance on both sides of the chamber. The model of the light sources and detectors and the corresponding spectral range are listed in Table 1. The optical length between each pair of the light source and the detector was 4 m. 50 g of bioaerosol materials were weighed each time and were filled into the filling port of the aerosol chamber. And the bioaerosol materials were injected into the aerosol chamber by N2 gas (output pressure: 0.5 MPa). Four fans were placed at the four corners of the aerosol chamber to accelerate the dispersion of the biomaterials and to better disperse the materials in the confined space of the aerosol chamber. As the bioaerosol in the aerosol chamber was evenly distributed, the average power of the light signal received by the detector over a period of time was recorded. The ratio of the average received light power to the initial emission light power was regarded as the average transmittance $\textrm{T}$. The attenuation rate can be calculated by $1 - \textrm{T}$. However, although the quality of materials used in each experiment was 50 mg, due to the limitation of the injection device, not all materials can be injected into the aerosol chamber each time. Moreover, due to the differences of sedimentation under different humidity conditions, the concentration of the materials in the aerosol chamber was not the same in each experiment, so the value of the attenuation rate are not suitable to compare the extinction performance. To solve this problem, a dust sampler was placed in the chamber and started working after the biological materials were sprayed into the chamber. The sampling flow rate and sampling time were set, and the quality of the filter membrane in the sampler was weighed before and after the experiment. So the concentration in each experiment can be calculated and the ratio of the attenuation rate to the concentration was used to compare the extinction performance of bioaerosol in each experiment. An industrial high-power humidifier was placed in the aerosol chamber to quickly change the relative humidity of the aerosol chamber, and a high-precision temperature and humidity recorder (Testo 174H) was placed to record the real-time changes of the relative humidity inside the aerosol chamber. In order to eliminate the differences caused by the attenuation effect of water molecules in various relative humidity conditions, firstly, the relative humidity in the aerosol chamber was added to 70%, 80%, and 90%, respectively. The light intensity detected by the detector was recorded as the power of the incident light, and then the biological materials were sprayed into the aerosol chamber according to the aforementioned steps. After the bioaerosol materials were evenly distributed in the aerosol chamber, the value of the detector was recorded as the received light power. In this way, the transmittance changes of biological materials in the three relative humidity conditions were obtained. The ratio of the attenuation rate to the concentration can describe the attenuation ability per unit concentration and the value of it was used to compare the extinction performance in various relative humidity conditions.

 

Fig. 2. Schematic diagram of the aerosol chamber experiment.

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Tables Icon

Table 1. The model of the light sources and detectors in the experiment

3. Results and discussion

3.1 Complex refractive index of bioaerosol materials

The CRI is a significant parameter of bioaerosol. The real part n is the refractive index, which is determined by the propagation speed of the light wave in the absorptive medium; the imaginary part k is determined by the attenuation of the light wave traveling in bioaerosol, which also called absorption coefficient. With the reflection spectra and the Kramers-Kroning (K-K) algorithm, we calculated the CRI of the two kinds of bioaerosol materials in the 0.2–14µm waveband. As shown in Fig. 3, the real index n of the two bioaerosol materials ranges from 1.1 to 1.875, and the imaginary index k ranges from 0 to 0.45. The variation trend of the real part of CRI of the two bioaerosol materials in 0.2–14µm waveband was approximately the same. Similar shapes can be found in the absorption spectra of the two bioaerosol materials and the absorption peaks of them concentrating at 0.9µm, 2.6µm and 9.7µm.

 

Fig. 3. Complex refractive index of the two kinds of bioaerosol. (a) Real part of complex refractive index. (b) Imaginary part of complex refractive index.

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3.2 Effects of relative humidity on biological materials

As shown in Figs. 4(a)–4(d), we calculated the changes in the real and imaginary parts of the CRI of two bioaerosol materials as a function of relative humidity. It can be seen from the figures that as the relative humidity increases, the real and imaginary parts of the particles’ CRI gradually decrease. When the relative humidity increases to 90%, the real parts gradually decrease and are close to the refractive index of water: 1.33. The imaginary parts gradually tend to zero. This result indicates that as the moisture absorption of bioaerosol particles increases, the moisture content thereof increases, resulting in its refractive index characteristics becoming closer to the refractive index characteristics of pure water.

 

Fig. 4. Humidity growth model of bioaerosol. (a-d)Humidity growth model of complex refractive index: (a) and (b) for AN0913 spores, (c) and (d) for AO0907 spores. (e) Humidity growth model of bioaerosol particle size.

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Such result shows that with the increase of relative humidity, the imaginary part of the CRI of the bioaerosol material, namely the absorption coefficient, is gradually close to 0, and the ability of bioaerosol material to absorb light is gradually weakened. However, we can know from the literature [3] that the extinction performance of biomaterials in the 0.2–14µm waveband is mainly depend on the absorption. Therefore, as the influence of relative humidity on the CRI of bioaerosol materials, the increase in relative humidity will result in weakening of the broadband extinction performance of bioaerosol materials.

On the other hand, with the increase of relative humidity, the particle radius of bioaerosol original particle increases due to the absorption of water. The change of particle size with relative humidity was calculated by empirical formula (see Methods part). Due to the original particles of the two biomaterials are spherical in shape, with a concentrated particle size distribution of 1∼2µm, and an average radius of 1.5µm. In the calculation, it is assumed that the dried biomaterial has an original particle size of 1.5µm. As shown in Fig. 4(e), as the relative humidity increases, the radius of bioaerosol particles shows an increasing trend and has an obvious exponential relationship. When the relative humidity values above 70%, the particle size increases sharply due to water absorption. When the relative humidity is 95%, the particle radius is about twice that of 60%. In previous research [28], our team has concluded through experiments that as the radius of the original particles of biological materials increases, the transmittance of light decreases, which means the extinction ability of biological materials is enhanced. Therefore, as the relative humidity increases, the extinction performance of the biomaterials will be enhanced due to the increase in particle size. This conclusion is just contrary to the change trend of the extinction performance caused by the influence of the relative humidity growth on the CRI of the bioaerosol.

As a result, it is necessary to comprehensively consider the influence of relative humidity on the extinction performance of bioaerosol materials in terms of particle size and CRI, and obtain specific change rules through rigorous simulation, calculation and experimental verification.

3.3 Bioaerosol spatial structure and multi-humidity extinction calculation model

In order to perform the extinction performance calculation, the spatial structure of the bioaerosol was simulated by the cluster-cluster aggregation (CCA) model. In this method, a simulated model of bioaerosol agglomerated particle was obtained as shown in Fig. 1(c).

Assuming that AN0913 and AO0907 spores diffuse evenly in a certain space, the density of aggregated particles is approximately 800 cm-3, thus, ρ=800 cm-3. Each aggregation contains 50 original particles, thus, N = 50. The original particle radius is 1.5 µm, thus, r0 = 1.5 µm. The optical length is 4 m, thus, L = 4 m. Assuming that the relative humidity of the environment changes from 0 to 100%. The absorption cross section and scattering cross section of the bioaerosol agglomerated particle, the transmittance, absorbed fraction and scattered fraction of the simulation experiment were calculated with DDA method and Monte Carlo algorithm.

Taking the simulation results of the AN0913 spores as an example, the parameters that describe the broadband extinction performance of the AN0913 spores in various relative humidity conditions are shown in Figs. 5(a)–5(f). In Figs. 5(a) and 5(c)–5(f), the two axes on the horizontal plane are waveband and relative humidity. The axe in the vertical plane is the simulation value of the parameters. As shown in Figs. 5(a) and 5(b), the transmittance of incident light through bioaerosol agglomerated particle swarm decreases with the growth of humidity when the relative humidity values above 70%. Figure 5(c)–5(f) show that the absorption and scattering of incident light by AN0913 agglomerated particle swarm are significantly enhanced with the increasing humidity from 70% to 100%. These enhancements result in a sharp decrease in transmittance. In other words, in this humidity range, the extinction ability of AN0913 agglomerated particle swarm increases with relative humidity. The simulation results of AO0907 agglomerated particle swarm also showed the same conclusion.

 

Fig. 5. Simulation results of extinction performance parameters in different humidity conditions. (a, c-f) Extinction performance parameters of AN0913 spores in different humidity conditions. (b) Contour map of transmittance simulation results of AN0913 spores. (g, h) Contrast analysis of transmittance contour map and absorption coefficient spectrum of the two spores.

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Combining the influence of relative humidity on particle size and CRI, the causes of such conclusions were analyzed. The particle size increases with relative humidity, and when the relative humidity values above 70%, the particle size increases sharply due to water absorption. In previous research [28], our team has concluded through experiments that as the radius of the original particles of bioaerosol materials increases, the transmittance of light decreases and the extinction ability is enhanced. Thus, as the relative humidity increases, especially when the value is above 70%, the extinction abilities of bioaerosol materials are enhanced, and the transmittance of the incident light through bioaerosol decreases due to the growth of the original particle size. However, with the increase of relative humidity, the imaginary part of the CRI of the bioaerosol materials gradually decreases to 0, and the abilities of bioaerosol materials to absorb light are gradually weakened and the transmittance increases. According to Figs. 5(a) and 5(b), the transmittance of the simulation model hardly changes in the humidity range of 0-70%, and decreases rapidly with the increase of humidity when the value of humidity is above 70%. Such results show that when the relative humidity is in the range of 0-70%, as the humidity increases, the increase of original particle size and the decrease of the material absorption coefficient have opposite effects on the extinction performance of the material, thereby canceling each other out. When the humidity is above 70%, due to the sharp increase in the original particle size, the decrease in the transmittance due to the increase in the particle diameter is greater than the increase in transmittance caused by the decrease in the imaginary part of the CRI.

As shown in Figs. 5(g) and 5(h), the transmittance simulation results of the two bioaerosol agglomerated particle swarms were projected onto two-dimensional planes composed of relative humidity and incident light wavelength to form contour maps. And the contour maps were compared and analyzed with the spectrums of the imaginary part of CRI. When relative humidity values from 70% to 100%, the bands in which transmittance decreases sharply with the increase of relative humidity just corresponds to the trough in the absorption coefficient spectrum as indicated by the upward arrow. The reason for this is that at the trough of the absorption coefficient spectrum, the value is close to 0 and the imaginary part of the CRI of the bioaerosol material does not change with the relative humidity. The transmittance will decrease due to the sharp increase in the particle size.

In the band corresponding to the peak of the absorption coefficient spectrum, the transmittance decreases slowly with increasing humidity as indicated by the downward arrow. The reason for this is that at the peak of the absorption coefficient spectrum, the absorption coefficient declines obviously with the increase of relative humidity (in Figs. 4(a)–4(d)) and the decreasing trend of transmittance due to particle size increase was slowed down. Such results are consistent with the conclusions of the theoretical analysis above.

3.4 Experimental analysis

AN0913 and AO0907 spores were used to perform the transmittance experiment in the aerosol chamber. In the three relative humidity conditions of 70%, 80% and 90%, the broadband transmittance of the two materials were tested. The four detectors in Table 1 were used to record the transmittance of UV (setting wavelength: 200 nm), visible light (setting wavelength: 532 nm), mid-infrared band (3.7-4.8µm) and far-infrared band (7.5-14µm) respectively. According to the previous experimental experience, 5 seconds after the material injection was taken as the start time for the materials to be evenly distributed in the aerosol chamber, and the detector value within 3 minutes after that time was recorded. In this way, the average transmittance and average attenuation rate of the four wavebands within 3 minutes can be calculated. The dust sampler was set up to calculate the average concentration of materials in the aerosol chamber within 3 minutes. The ratio of attenuation rate to concentration was calculated and the detailed data were shown in Table 2.

Tables Icon

Table 2. Results of the aerosol chamber experiment

As shown in Table 2, in the all four experimental bands, as the values of optical length are the same, the ratio of attenuation rate to concentration increases with relative humidity. In another words, both of the two bioaerosol materials showed stronger extinction ability when the relative humidity in the environment increased from 70% to 90%. This result is in good agreement with the aforementioned simulation conclusion. In addition, in the comparison of multi-group experiments, we found that when the same quality of biological material is sprayed into the aerosol chamber, the higher the relative humidity in the environment, the lower the average concentration of the formed aerosol in a certain period of time. We conjecture that this result may be related to the increase in particle size, mass, and speed of sedimentation after the materials have absorbed water.

Taking the value of the ratio of attenuation rate to concentration as a parameter to compare the extinction performance, as the relative humidity increase from 70% to 80% and 90%, the percentage increases of this parameter in the four wavebands were calculated and the results were visualized.

Figure 6 shows broadband attenuation ability per unit concentration in three relative humidity conditions of the two spores. As shown in the Fig. 6, when the relative humidity increases from 70% to 90%, the extinction performance of AN0913 spores increase about 30% in visible and mid-infrared bands, about 20% in UV and far-infrared bands. And the extinction performance of AO0907 spores increase about 23% in the all four bands.

 

Fig. 6. Percentage increases of the attenuation ability per unit concentration as the relative humidity increase from 70% to 80% and 90% in the four wavebands. (a)Broadband attenuation ability per unit concentration of AN0913 spores in three relative humidity conditions. (b) Broadband attenuation ability per unit concentration of AO0907 spores in three relative humidity conditions of AO0907 spores.

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4. Conclusion

With the increase of relative humidity, the size of bioaerosol original particle will increase, especially when the humidity is above 70%. The increase of the original particle size drives the extinction performance of bioaerosol better. On the other hand, as the humidity increases, the imaginary part of the CRI of the bioaerosol materials will gradually decrease and approach 0, which means that the absorption performance of the bioaerosol will be degraded. Considering the influence of the increasing humidity on the original particle size and CRI, the DDA model and Monte Carlo algorithm were used to calculate the extinction performance and simulate the transmittance under set conditions. The results show that in the 0.2-14µm waveband, when the relative humidity is in the range of 0 to 70%, the effects of the two aspects on the extinction performance can almost cancel each other out, that is, the extinction performance of the bioaerosol is relatively stable and almost unchanged in this humidity range. When the relative humidity value is above 70%, as the humidity increases, compared with the influence of the decrease in absorption coefficient on the extinction performance of bioaerosol, the influence of the increase in the original particle size is more greater. As we can see in Figs. 5(a)–5(f), when humidity grows, the absorption cross section and scattering cross section of the bioaerosol agglomerated particle increase obviously and the absorption fraction and scattered fraction of incident light through bioaerosol are significantly increased while the transmittance of the incident decreases.

Although in the 0.2-14µm waveband, as the relative humidity is greater than 70%, the extinction performance of bioaerosol will be enhanced with the increase of relative humidity, but the range of enhancement in different bands is quite different. This difference is determined by the absorption coefficient spectrum of the bioaerosol materials. At the trough of the absorption coefficient spectrum, the extinction performance of the bioaerosol increases obviously with relative humidity, while at the peak of the absorption spectrum, the enhancement reduce.

The results of transmittance experiment of bioaerosol in the aerosol chamber show that if the concentration of bioaerosol in the aerosol chamber is the same, bioaerosol shows greater extinction performance as the relative humidity in the chamber increase from 70% to 90% or more. As the relative humidity increases from 70% to 90%, the extinction performance of AN0913 spores increase about 30% in visible and mid-infrared bands, about 20% in UV and far-infrared bands. And the extinction performance of AO0907 spores increase about 23% in the all four bands.

In conclusion, the results reveal the influence of relative humidity on the broadband extinction performance of bioaerosol. This work is of great significance for further research in bioaerosol. Firstly, the research results provide some theoretical references for studying the effects of bioaerosol on climate change. At different latitudes, the relative humidity of environment is quite different. When studying the influence of bioaerosol absorption and scattering of solar radiation on climate change, the influence of humidity on extinction performance cannot be ignored. In addition, when carrying out optical remote sensing, optical detection, optical communication and other activities, the enhancement of the attenuation ability of bioaerosol in the atmosphere due to the increase of relative humidity should be taken into account. Finally, bioaerosol is a new direction for the development of functional materials in the UV to infrared band. The results of this study can provide some theoretical basis for the further research of new functional materials.

Funding

National Natural Science Foundation of China (60908033, 61271353, 61871389); Natural Science Foundation of Anhui Province (1408085MKL47); National University of Defense Technology (ZK18-01-02).

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13. P. Grosse and V. Offermann, “Analysis of reflectance data using the Kramers-Kronig Relations,” Appl. Phys. A 52(2), 138–144 (1991). [CrossRef]  

14. D. Poelman and P. F. Smet, “Methods for the determination of the optical constants of thin films from single transmission measurements: a critical review,” J. Phys. D: Appl. Phys. 36(15), 1850–1857 (2003). [CrossRef]  

15. M. Segal-Rosenheimer and R. Linker, “Impact of the non-measured infrared spectral range of the imaginary refractive index on the derivation of the real refractive index using the Kramers-Kronig transform,” J. Quant. Spectrosc. Radiat. Transfer 110(13), 1147–1161 (2009). [CrossRef]  

16. Y. Gu, Y. Hu, X. Zhao, and C. Xi, “Determination of infrared complex refractive index of microbial materials,” J. Quant. Spectrosc. Radiat. Transfer 217, 305–314 (2018). [CrossRef]  

17. L. Li, Y. Hu, Y. Gu, W. Chen, and Y. Zhao, “Measurement and qnalysis on complex refraction indices of pear pollen in infrared band,” Spectrosc. Spectral Anal. 35, 89–92 (2015).

18. L. Li, Y. Hu, Y. Gu, X. Zhao, S. Xu, L. Yu, Z. M. Zheng, and P. Wang, “Infrared extinction performance of randomly oriented microbial-clustered agglomerate materials,” Appl. Spectrosc. 71(11), 2555–2562 (2017). [CrossRef]  

19. Y. Gu, Y. Hu, X. Zhao, C. Xi, W. Peng, and Z. Zheng, “Discrimination of viable and dead microbial materials with Fourier transform infrared spectroscopy in 3–5 micrometers,” Opt. Express 26(12), 15842–15850 (2018). [CrossRef]  

20. D. Sun, Y. Hu, and L. Li, “Test and analysis of infrared and microwave characteristics of metallic farinas,” Infra. Laser Engin. 42, 2531–2535 (2013).

21. D. J. Sun, “Determination and model construction of microbes’ complex refractive index in far infrared band,” Acta Phys. Sin. 62(9), 94218–094218 (2013). [CrossRef]  

22. D. J. Sun, Y. Hu, Y. Gu, Y. Wang, and L. Li, “Preparation and performance testing of metallic biologic particles,” Guangzi Xuebao 42(5), 555–558 (2013). [CrossRef]  

23. X. Zhao, Y. Hu, Y. Gu, and L. Li, “Transmittance of laser in the microorganism aggregated particle swarm,” Acta Opt. Sin. 35(6), 0616001 (2015). [CrossRef]  

24. X. Zhao, Y. Hu, Y. Gu, and L. Le, “The infrared spectral transmittance of Aspergillus niger spore aggregated particle swarm,” Proc. SPIE 9678, 967817 (2015). [CrossRef]  

25. Y. Gu, Y. Hu, X. Zhao, X. Chen, and Z. Zheng, “Combined analysis of static and dynamic extinction characteristics of microbial spores and mycelia as a mid-infrared extinction material,” Optik 176, 535–541 (2019). [CrossRef]  

26. L. Shen, F. Gu, J. Zhang, and Y. Liu, “The effect of relative humidity on the extinction coefficient of aerosols,” J. Light Scatt. 29, 251–256 (2017).

27. G. Hänel, “The properties of atmospheric aerosol particles as functions of the relative humidity at thermodynamic equilibrium with the surrounding moist air,” Adv. Geophys. 19, 73–188 (1976). [CrossRef]  

28. X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Analysis of optical properties of bio-smoke materials in the 0.25-14 µm band,” Chin. Phys. B 28(3), 034201 (2019). [CrossRef]  

29. X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “A comparison of infrared extinction performances of bioaerosols and traditional smoke materials,” Optik 181, 293–300 (2019). [CrossRef]  

30. X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Aggregation-driven reductions in the mass extinction coefficient of bioaerosols,” Optik 184, 115–120 (2019). [CrossRef]  

31. C. Li and H. Xiong, “3D simulation of the Cluster–Cluster Aggregation model,” Comput. Phys. Commun. 185(12), 3424–3429 (2014). [CrossRef]  

32. B. T. Draine and P. J. Flatau, “User guide for the discrete dipole approximation code DDSCAT 7.3,” (2013).

33. T. Kozasa, J. Blum, and T. Mukai, “Optical properties of dust aggregates,” Astron. Astrophys. 263, 423–432 (1992).

34. M. Lattuada, W. Hua, and M. Morbidelli, “Radial density distribution of fractal clusters,” Chem. Eng. Sci. 59(21), 4401–4413 (2004). [CrossRef]  

35. M. Min, C. Dominik, J. W. Hovenier, A. D. Koter, and L. B. F. M. Waters, “The 10 m amorphous silicate feature of fractal aggregates and compact particles with complex shapes,” Astron. Astrophys. 445(3), 1005–1014 (2006). [CrossRef]  

36. S. L. Jacques, “Modeling tissue optics using Monte Carlo modeling: a tutorial,” Proc. SPIE 6854, 68540T (2008). [CrossRef]  

References

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  1. V. Després, J. A. Huffman, S. M. Burrows, C. Hoose, A. Safatov, G. Buryak, J. Fröhlich-Nowoisky, W. Elbert, M. Andreae, and U. Pöschl, “Primary biological aerosol particles in the atmosphere: a review,” Tellus B 64(1), 15598–153 (2012).
    [Crossref]
  2. K. Adachi, S. H. Chung, and P. R. Buseck, “Shapes of soot aerosol particles and implications for their effects on climate,” J. Geophys. Res. 115(D15), D15206 (2010).
    [Crossref]
  3. Y. Hu, X. Zhao, Y. Gu, X. Chen, X. Wang, P. Wang, Z. Zheng, and X. J. S. C. M. Dong, “Significant broadband extinction abilities of bioaerosols,” Sci. China Mater. 62(7), 1033–1045 (2019).
    [Crossref]
  4. I. N. Tang and H. R. Munkelwitz, “Water activities, densities, and refractive indices of aqueous sulfates and sodium nitrate droplets of atmospheric importance,” J. Geophys. Res. 99(D9), 18801–18808 (1994).
    [Crossref]
  5. D. E. Day and W. C. Malm, “Aerosol light scattering measurements as a function of relative humidity: a comparison between measurements made at three different sites,” Atmos. Environ. 35(30), 5169–5176 (2001).
    [Crossref]
  6. X. Li-Jones, H. B. Maring, and J. M. Prospero, “Effect of relative humidity on light scattering by mineral dust aerosol as measured in the marine boundary layer over the tropical Atlantic Ocean,” J. Geophys. Res. 103(D23), 31113–31121 (1998).
    [Crossref]
  7. I. N. Tang, “Chemical and size effects of hygroscopic aerosols on light scattering coefficients,” J. Geophys. Res. 101(D14), 19245–19250 (1996).
    [Crossref]
  8. P. Zieger, U. Frieß, B. Henzing, G. D. Leeuw, U. Baltensperger, E. Weingartner, K. Clemer, S. Yilmaz, H. Irie, and R. Fierz-Schmidhauser, “Effects of relative humidity on aerosol light scattering and its importance for the comparison of remote sensing with in-situ measurements,” Geochmica Et Cosmochimica Acta 12, 3875–3890 (2010).
  9. H. Liu, W. Peng, Y. Hu, G. Zhao, L. Hui, Z. Li, H. Wu, W. Li, and Z. Zheng, “Optimised fermentation conditions and improved collection efficiency using dual cyclone equipment to enhance fungal conidia production,” Biocontrol Science & Technology 25(9), 1011–1023 (2015).
    [Crossref]
  10. H. Liu, X. Zhao, M. Guo, H. Liu, and Z. Zheng, “Growth and metabolism of Beauveria bassiana spores and mycelia,” BMC Microbiol. 15(1), 267 (2015).
    [Crossref]
  11. P. Wang, H. Liu, Y. Zhao, Y. Gu, W. Chen, L. Wang, L. Li, X. Zhao, W. Lei, and Y. Hu, “Electromagnetic attenuation characteristics of microbial materials in the infrared band,” Appl. Spectrosc. 70(9), 1456–1463 (2016).
    [Crossref]
  12. H. C. Booij and G. P. J. M. Thoone, “Generalization of Kramers-Kronig transforms and some approximations of relations between viscoelastic quantities,” Rheol. Acta 21(1), 15–24 (1982).
    [Crossref]
  13. P. Grosse and V. Offermann, “Analysis of reflectance data using the Kramers-Kronig Relations,” Appl. Phys. A 52(2), 138–144 (1991).
    [Crossref]
  14. D. Poelman and P. F. Smet, “Methods for the determination of the optical constants of thin films from single transmission measurements: a critical review,” J. Phys. D: Appl. Phys. 36(15), 1850–1857 (2003).
    [Crossref]
  15. M. Segal-Rosenheimer and R. Linker, “Impact of the non-measured infrared spectral range of the imaginary refractive index on the derivation of the real refractive index using the Kramers-Kronig transform,” J. Quant. Spectrosc. Radiat. Transfer 110(13), 1147–1161 (2009).
    [Crossref]
  16. Y. Gu, Y. Hu, X. Zhao, and C. Xi, “Determination of infrared complex refractive index of microbial materials,” J. Quant. Spectrosc. Radiat. Transfer 217, 305–314 (2018).
    [Crossref]
  17. L. Li, Y. Hu, Y. Gu, W. Chen, and Y. Zhao, “Measurement and qnalysis on complex refraction indices of pear pollen in infrared band,” Spectrosc. Spectral Anal. 35, 89–92 (2015).
  18. L. Li, Y. Hu, Y. Gu, X. Zhao, S. Xu, L. Yu, Z. M. Zheng, and P. Wang, “Infrared extinction performance of randomly oriented microbial-clustered agglomerate materials,” Appl. Spectrosc. 71(11), 2555–2562 (2017).
    [Crossref]
  19. Y. Gu, Y. Hu, X. Zhao, C. Xi, W. Peng, and Z. Zheng, “Discrimination of viable and dead microbial materials with Fourier transform infrared spectroscopy in 3–5 micrometers,” Opt. Express 26(12), 15842–15850 (2018).
    [Crossref]
  20. D. Sun, Y. Hu, and L. Li, “Test and analysis of infrared and microwave characteristics of metallic farinas,” Infra. Laser Engin. 42, 2531–2535 (2013).
  21. D. J. Sun, “Determination and model construction of microbes’ complex refractive index in far infrared band,” Acta Phys. Sin. 62(9), 94218–094218 (2013).
    [Crossref]
  22. D. J. Sun, Y. Hu, Y. Gu, Y. Wang, and L. Li, “Preparation and performance testing of metallic biologic particles,” Guangzi Xuebao 42(5), 555–558 (2013).
    [Crossref]
  23. X. Zhao, Y. Hu, Y. Gu, and L. Li, “Transmittance of laser in the microorganism aggregated particle swarm,” Acta Opt. Sin. 35(6), 0616001 (2015).
    [Crossref]
  24. X. Zhao, Y. Hu, Y. Gu, and L. Le, “The infrared spectral transmittance of Aspergillus niger spore aggregated particle swarm,” Proc. SPIE 9678, 967817 (2015).
    [Crossref]
  25. Y. Gu, Y. Hu, X. Zhao, X. Chen, and Z. Zheng, “Combined analysis of static and dynamic extinction characteristics of microbial spores and mycelia as a mid-infrared extinction material,” Optik 176, 535–541 (2019).
    [Crossref]
  26. L. Shen, F. Gu, J. Zhang, and Y. Liu, “The effect of relative humidity on the extinction coefficient of aerosols,” J. Light Scatt. 29, 251–256 (2017).
  27. G. Hänel, “The properties of atmospheric aerosol particles as functions of the relative humidity at thermodynamic equilibrium with the surrounding moist air,” Adv. Geophys. 19, 73–188 (1976).
    [Crossref]
  28. X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Analysis of optical properties of bio-smoke materials in the 0.25-14 µm band,” Chin. Phys. B 28(3), 034201 (2019).
    [Crossref]
  29. X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “A comparison of infrared extinction performances of bioaerosols and traditional smoke materials,” Optik 181, 293–300 (2019).
    [Crossref]
  30. X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Aggregation-driven reductions in the mass extinction coefficient of bioaerosols,” Optik 184, 115–120 (2019).
    [Crossref]
  31. C. Li and H. Xiong, “3D simulation of the Cluster–Cluster Aggregation model,” Comput. Phys. Commun. 185(12), 3424–3429 (2014).
    [Crossref]
  32. B. T. Draine and P. J. Flatau, “User guide for the discrete dipole approximation code DDSCAT 7.3,” (2013).
  33. T. Kozasa, J. Blum, and T. Mukai, “Optical properties of dust aggregates,” Astron. Astrophys. 263, 423–432 (1992).
  34. M. Lattuada, W. Hua, and M. Morbidelli, “Radial density distribution of fractal clusters,” Chem. Eng. Sci. 59(21), 4401–4413 (2004).
    [Crossref]
  35. M. Min, C. Dominik, J. W. Hovenier, A. D. Koter, and L. B. F. M. Waters, “The 10 m amorphous silicate feature of fractal aggregates and compact particles with complex shapes,” Astron. Astrophys. 445(3), 1005–1014 (2006).
    [Crossref]
  36. S. L. Jacques, “Modeling tissue optics using Monte Carlo modeling: a tutorial,” Proc. SPIE 6854, 68540T (2008).
    [Crossref]

2019 (5)

Y. Hu, X. Zhao, Y. Gu, X. Chen, X. Wang, P. Wang, Z. Zheng, and X. J. S. C. M. Dong, “Significant broadband extinction abilities of bioaerosols,” Sci. China Mater. 62(7), 1033–1045 (2019).
[Crossref]

Y. Gu, Y. Hu, X. Zhao, X. Chen, and Z. Zheng, “Combined analysis of static and dynamic extinction characteristics of microbial spores and mycelia as a mid-infrared extinction material,” Optik 176, 535–541 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Analysis of optical properties of bio-smoke materials in the 0.25-14 µm band,” Chin. Phys. B 28(3), 034201 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “A comparison of infrared extinction performances of bioaerosols and traditional smoke materials,” Optik 181, 293–300 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Aggregation-driven reductions in the mass extinction coefficient of bioaerosols,” Optik 184, 115–120 (2019).
[Crossref]

2018 (2)

Y. Gu, Y. Hu, X. Zhao, C. Xi, W. Peng, and Z. Zheng, “Discrimination of viable and dead microbial materials with Fourier transform infrared spectroscopy in 3–5 micrometers,” Opt. Express 26(12), 15842–15850 (2018).
[Crossref]

Y. Gu, Y. Hu, X. Zhao, and C. Xi, “Determination of infrared complex refractive index of microbial materials,” J. Quant. Spectrosc. Radiat. Transfer 217, 305–314 (2018).
[Crossref]

2017 (2)

L. Shen, F. Gu, J. Zhang, and Y. Liu, “The effect of relative humidity on the extinction coefficient of aerosols,” J. Light Scatt. 29, 251–256 (2017).

L. Li, Y. Hu, Y. Gu, X. Zhao, S. Xu, L. Yu, Z. M. Zheng, and P. Wang, “Infrared extinction performance of randomly oriented microbial-clustered agglomerate materials,” Appl. Spectrosc. 71(11), 2555–2562 (2017).
[Crossref]

2016 (1)

2015 (5)

L. Li, Y. Hu, Y. Gu, W. Chen, and Y. Zhao, “Measurement and qnalysis on complex refraction indices of pear pollen in infrared band,” Spectrosc. Spectral Anal. 35, 89–92 (2015).

H. Liu, W. Peng, Y. Hu, G. Zhao, L. Hui, Z. Li, H. Wu, W. Li, and Z. Zheng, “Optimised fermentation conditions and improved collection efficiency using dual cyclone equipment to enhance fungal conidia production,” Biocontrol Science & Technology 25(9), 1011–1023 (2015).
[Crossref]

H. Liu, X. Zhao, M. Guo, H. Liu, and Z. Zheng, “Growth and metabolism of Beauveria bassiana spores and mycelia,” BMC Microbiol. 15(1), 267 (2015).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, and L. Li, “Transmittance of laser in the microorganism aggregated particle swarm,” Acta Opt. Sin. 35(6), 0616001 (2015).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, and L. Le, “The infrared spectral transmittance of Aspergillus niger spore aggregated particle swarm,” Proc. SPIE 9678, 967817 (2015).
[Crossref]

2014 (1)

C. Li and H. Xiong, “3D simulation of the Cluster–Cluster Aggregation model,” Comput. Phys. Commun. 185(12), 3424–3429 (2014).
[Crossref]

2013 (3)

D. Sun, Y. Hu, and L. Li, “Test and analysis of infrared and microwave characteristics of metallic farinas,” Infra. Laser Engin. 42, 2531–2535 (2013).

D. J. Sun, “Determination and model construction of microbes’ complex refractive index in far infrared band,” Acta Phys. Sin. 62(9), 94218–094218 (2013).
[Crossref]

D. J. Sun, Y. Hu, Y. Gu, Y. Wang, and L. Li, “Preparation and performance testing of metallic biologic particles,” Guangzi Xuebao 42(5), 555–558 (2013).
[Crossref]

2012 (1)

V. Després, J. A. Huffman, S. M. Burrows, C. Hoose, A. Safatov, G. Buryak, J. Fröhlich-Nowoisky, W. Elbert, M. Andreae, and U. Pöschl, “Primary biological aerosol particles in the atmosphere: a review,” Tellus B 64(1), 15598–153 (2012).
[Crossref]

2010 (2)

K. Adachi, S. H. Chung, and P. R. Buseck, “Shapes of soot aerosol particles and implications for their effects on climate,” J. Geophys. Res. 115(D15), D15206 (2010).
[Crossref]

P. Zieger, U. Frieß, B. Henzing, G. D. Leeuw, U. Baltensperger, E. Weingartner, K. Clemer, S. Yilmaz, H. Irie, and R. Fierz-Schmidhauser, “Effects of relative humidity on aerosol light scattering and its importance for the comparison of remote sensing with in-situ measurements,” Geochmica Et Cosmochimica Acta 12, 3875–3890 (2010).

2009 (1)

M. Segal-Rosenheimer and R. Linker, “Impact of the non-measured infrared spectral range of the imaginary refractive index on the derivation of the real refractive index using the Kramers-Kronig transform,” J. Quant. Spectrosc. Radiat. Transfer 110(13), 1147–1161 (2009).
[Crossref]

2008 (1)

S. L. Jacques, “Modeling tissue optics using Monte Carlo modeling: a tutorial,” Proc. SPIE 6854, 68540T (2008).
[Crossref]

2006 (1)

M. Min, C. Dominik, J. W. Hovenier, A. D. Koter, and L. B. F. M. Waters, “The 10 m amorphous silicate feature of fractal aggregates and compact particles with complex shapes,” Astron. Astrophys. 445(3), 1005–1014 (2006).
[Crossref]

2004 (1)

M. Lattuada, W. Hua, and M. Morbidelli, “Radial density distribution of fractal clusters,” Chem. Eng. Sci. 59(21), 4401–4413 (2004).
[Crossref]

2003 (1)

D. Poelman and P. F. Smet, “Methods for the determination of the optical constants of thin films from single transmission measurements: a critical review,” J. Phys. D: Appl. Phys. 36(15), 1850–1857 (2003).
[Crossref]

2001 (1)

D. E. Day and W. C. Malm, “Aerosol light scattering measurements as a function of relative humidity: a comparison between measurements made at three different sites,” Atmos. Environ. 35(30), 5169–5176 (2001).
[Crossref]

1998 (1)

X. Li-Jones, H. B. Maring, and J. M. Prospero, “Effect of relative humidity on light scattering by mineral dust aerosol as measured in the marine boundary layer over the tropical Atlantic Ocean,” J. Geophys. Res. 103(D23), 31113–31121 (1998).
[Crossref]

1996 (1)

I. N. Tang, “Chemical and size effects of hygroscopic aerosols on light scattering coefficients,” J. Geophys. Res. 101(D14), 19245–19250 (1996).
[Crossref]

1994 (1)

I. N. Tang and H. R. Munkelwitz, “Water activities, densities, and refractive indices of aqueous sulfates and sodium nitrate droplets of atmospheric importance,” J. Geophys. Res. 99(D9), 18801–18808 (1994).
[Crossref]

1992 (1)

T. Kozasa, J. Blum, and T. Mukai, “Optical properties of dust aggregates,” Astron. Astrophys. 263, 423–432 (1992).

1991 (1)

P. Grosse and V. Offermann, “Analysis of reflectance data using the Kramers-Kronig Relations,” Appl. Phys. A 52(2), 138–144 (1991).
[Crossref]

1982 (1)

H. C. Booij and G. P. J. M. Thoone, “Generalization of Kramers-Kronig transforms and some approximations of relations between viscoelastic quantities,” Rheol. Acta 21(1), 15–24 (1982).
[Crossref]

1976 (1)

G. Hänel, “The properties of atmospheric aerosol particles as functions of the relative humidity at thermodynamic equilibrium with the surrounding moist air,” Adv. Geophys. 19, 73–188 (1976).
[Crossref]

Adachi, K.

K. Adachi, S. H. Chung, and P. R. Buseck, “Shapes of soot aerosol particles and implications for their effects on climate,” J. Geophys. Res. 115(D15), D15206 (2010).
[Crossref]

Andreae, M.

V. Després, J. A. Huffman, S. M. Burrows, C. Hoose, A. Safatov, G. Buryak, J. Fröhlich-Nowoisky, W. Elbert, M. Andreae, and U. Pöschl, “Primary biological aerosol particles in the atmosphere: a review,” Tellus B 64(1), 15598–153 (2012).
[Crossref]

Baltensperger, U.

P. Zieger, U. Frieß, B. Henzing, G. D. Leeuw, U. Baltensperger, E. Weingartner, K. Clemer, S. Yilmaz, H. Irie, and R. Fierz-Schmidhauser, “Effects of relative humidity on aerosol light scattering and its importance for the comparison of remote sensing with in-situ measurements,” Geochmica Et Cosmochimica Acta 12, 3875–3890 (2010).

Blum, J.

T. Kozasa, J. Blum, and T. Mukai, “Optical properties of dust aggregates,” Astron. Astrophys. 263, 423–432 (1992).

Booij, H. C.

H. C. Booij and G. P. J. M. Thoone, “Generalization of Kramers-Kronig transforms and some approximations of relations between viscoelastic quantities,” Rheol. Acta 21(1), 15–24 (1982).
[Crossref]

Burrows, S. M.

V. Després, J. A. Huffman, S. M. Burrows, C. Hoose, A. Safatov, G. Buryak, J. Fröhlich-Nowoisky, W. Elbert, M. Andreae, and U. Pöschl, “Primary biological aerosol particles in the atmosphere: a review,” Tellus B 64(1), 15598–153 (2012).
[Crossref]

Buryak, G.

V. Després, J. A. Huffman, S. M. Burrows, C. Hoose, A. Safatov, G. Buryak, J. Fröhlich-Nowoisky, W. Elbert, M. Andreae, and U. Pöschl, “Primary biological aerosol particles in the atmosphere: a review,” Tellus B 64(1), 15598–153 (2012).
[Crossref]

Buseck, P. R.

K. Adachi, S. H. Chung, and P. R. Buseck, “Shapes of soot aerosol particles and implications for their effects on climate,” J. Geophys. Res. 115(D15), D15206 (2010).
[Crossref]

Chen, W.

P. Wang, H. Liu, Y. Zhao, Y. Gu, W. Chen, L. Wang, L. Li, X. Zhao, W. Lei, and Y. Hu, “Electromagnetic attenuation characteristics of microbial materials in the infrared band,” Appl. Spectrosc. 70(9), 1456–1463 (2016).
[Crossref]

L. Li, Y. Hu, Y. Gu, W. Chen, and Y. Zhao, “Measurement and qnalysis on complex refraction indices of pear pollen in infrared band,” Spectrosc. Spectral Anal. 35, 89–92 (2015).

Chen, X.

Y. Gu, Y. Hu, X. Zhao, X. Chen, and Z. Zheng, “Combined analysis of static and dynamic extinction characteristics of microbial spores and mycelia as a mid-infrared extinction material,” Optik 176, 535–541 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Analysis of optical properties of bio-smoke materials in the 0.25-14 µm band,” Chin. Phys. B 28(3), 034201 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “A comparison of infrared extinction performances of bioaerosols and traditional smoke materials,” Optik 181, 293–300 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Aggregation-driven reductions in the mass extinction coefficient of bioaerosols,” Optik 184, 115–120 (2019).
[Crossref]

Y. Hu, X. Zhao, Y. Gu, X. Chen, X. Wang, P. Wang, Z. Zheng, and X. J. S. C. M. Dong, “Significant broadband extinction abilities of bioaerosols,” Sci. China Mater. 62(7), 1033–1045 (2019).
[Crossref]

Chung, S. H.

K. Adachi, S. H. Chung, and P. R. Buseck, “Shapes of soot aerosol particles and implications for their effects on climate,” J. Geophys. Res. 115(D15), D15206 (2010).
[Crossref]

Clemer, K.

P. Zieger, U. Frieß, B. Henzing, G. D. Leeuw, U. Baltensperger, E. Weingartner, K. Clemer, S. Yilmaz, H. Irie, and R. Fierz-Schmidhauser, “Effects of relative humidity on aerosol light scattering and its importance for the comparison of remote sensing with in-situ measurements,” Geochmica Et Cosmochimica Acta 12, 3875–3890 (2010).

Day, D. E.

D. E. Day and W. C. Malm, “Aerosol light scattering measurements as a function of relative humidity: a comparison between measurements made at three different sites,” Atmos. Environ. 35(30), 5169–5176 (2001).
[Crossref]

Després, V.

V. Després, J. A. Huffman, S. M. Burrows, C. Hoose, A. Safatov, G. Buryak, J. Fröhlich-Nowoisky, W. Elbert, M. Andreae, and U. Pöschl, “Primary biological aerosol particles in the atmosphere: a review,” Tellus B 64(1), 15598–153 (2012).
[Crossref]

Dominik, C.

M. Min, C. Dominik, J. W. Hovenier, A. D. Koter, and L. B. F. M. Waters, “The 10 m amorphous silicate feature of fractal aggregates and compact particles with complex shapes,” Astron. Astrophys. 445(3), 1005–1014 (2006).
[Crossref]

Dong, X.

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Aggregation-driven reductions in the mass extinction coefficient of bioaerosols,” Optik 184, 115–120 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “A comparison of infrared extinction performances of bioaerosols and traditional smoke materials,” Optik 181, 293–300 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Analysis of optical properties of bio-smoke materials in the 0.25-14 µm band,” Chin. Phys. B 28(3), 034201 (2019).
[Crossref]

Dong, X. J. S. C. M.

Y. Hu, X. Zhao, Y. Gu, X. Chen, X. Wang, P. Wang, Z. Zheng, and X. J. S. C. M. Dong, “Significant broadband extinction abilities of bioaerosols,” Sci. China Mater. 62(7), 1033–1045 (2019).
[Crossref]

Draine, B. T.

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L. Shen, F. Gu, J. Zhang, and Y. Liu, “The effect of relative humidity on the extinction coefficient of aerosols,” J. Light Scatt. 29, 251–256 (2017).

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X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Aggregation-driven reductions in the mass extinction coefficient of bioaerosols,” Optik 184, 115–120 (2019).
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Y. Hu, X. Zhao, Y. Gu, X. Chen, X. Wang, P. Wang, Z. Zheng, and X. J. S. C. M. Dong, “Significant broadband extinction abilities of bioaerosols,” Sci. China Mater. 62(7), 1033–1045 (2019).
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X. Zhao, Y. Hu, Y. Gu, and L. Li, “Transmittance of laser in the microorganism aggregated particle swarm,” Acta Opt. Sin. 35(6), 0616001 (2015).
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X. Zhao, Y. Hu, Y. Gu, and L. Le, “The infrared spectral transmittance of Aspergillus niger spore aggregated particle swarm,” Proc. SPIE 9678, 967817 (2015).
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V. Després, J. A. Huffman, S. M. Burrows, C. Hoose, A. Safatov, G. Buryak, J. Fröhlich-Nowoisky, W. Elbert, M. Andreae, and U. Pöschl, “Primary biological aerosol particles in the atmosphere: a review,” Tellus B 64(1), 15598–153 (2012).
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Y. Gu, Y. Hu, X. Zhao, X. Chen, and Z. Zheng, “Combined analysis of static and dynamic extinction characteristics of microbial spores and mycelia as a mid-infrared extinction material,” Optik 176, 535–541 (2019).
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X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “A comparison of infrared extinction performances of bioaerosols and traditional smoke materials,” Optik 181, 293–300 (2019).
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Y. Gu, Y. Hu, X. Zhao, and C. Xi, “Determination of infrared complex refractive index of microbial materials,” J. Quant. Spectrosc. Radiat. Transfer 217, 305–314 (2018).
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Y. Gu, Y. Hu, X. Zhao, C. Xi, W. Peng, and Z. Zheng, “Discrimination of viable and dead microbial materials with Fourier transform infrared spectroscopy in 3–5 micrometers,” Opt. Express 26(12), 15842–15850 (2018).
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L. Li, Y. Hu, Y. Gu, W. Chen, and Y. Zhao, “Measurement and qnalysis on complex refraction indices of pear pollen in infrared band,” Spectrosc. Spectral Anal. 35, 89–92 (2015).

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[Crossref]

X. Zhao, Y. Hu, Y. Gu, and L. Le, “The infrared spectral transmittance of Aspergillus niger spore aggregated particle swarm,” Proc. SPIE 9678, 967817 (2015).
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H. Liu, W. Peng, Y. Hu, G. Zhao, L. Hui, Z. Li, H. Wu, W. Li, and Z. Zheng, “Optimised fermentation conditions and improved collection efficiency using dual cyclone equipment to enhance fungal conidia production,” Biocontrol Science & Technology 25(9), 1011–1023 (2015).
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P. Zieger, U. Frieß, B. Henzing, G. D. Leeuw, U. Baltensperger, E. Weingartner, K. Clemer, S. Yilmaz, H. Irie, and R. Fierz-Schmidhauser, “Effects of relative humidity on aerosol light scattering and its importance for the comparison of remote sensing with in-situ measurements,” Geochmica Et Cosmochimica Acta 12, 3875–3890 (2010).

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Li, C.

C. Li and H. Xiong, “3D simulation of the Cluster–Cluster Aggregation model,” Comput. Phys. Commun. 185(12), 3424–3429 (2014).
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L. Li, Y. Hu, Y. Gu, X. Zhao, S. Xu, L. Yu, Z. M. Zheng, and P. Wang, “Infrared extinction performance of randomly oriented microbial-clustered agglomerate materials,” Appl. Spectrosc. 71(11), 2555–2562 (2017).
[Crossref]

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L. Li, Y. Hu, Y. Gu, W. Chen, and Y. Zhao, “Measurement and qnalysis on complex refraction indices of pear pollen in infrared band,” Spectrosc. Spectral Anal. 35, 89–92 (2015).

X. Zhao, Y. Hu, Y. Gu, and L. Li, “Transmittance of laser in the microorganism aggregated particle swarm,” Acta Opt. Sin. 35(6), 0616001 (2015).
[Crossref]

D. J. Sun, Y. Hu, Y. Gu, Y. Wang, and L. Li, “Preparation and performance testing of metallic biologic particles,” Guangzi Xuebao 42(5), 555–558 (2013).
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D. Sun, Y. Hu, and L. Li, “Test and analysis of infrared and microwave characteristics of metallic farinas,” Infra. Laser Engin. 42, 2531–2535 (2013).

Li, W.

H. Liu, W. Peng, Y. Hu, G. Zhao, L. Hui, Z. Li, H. Wu, W. Li, and Z. Zheng, “Optimised fermentation conditions and improved collection efficiency using dual cyclone equipment to enhance fungal conidia production,” Biocontrol Science & Technology 25(9), 1011–1023 (2015).
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Li, Z.

H. Liu, W. Peng, Y. Hu, G. Zhao, L. Hui, Z. Li, H. Wu, W. Li, and Z. Zheng, “Optimised fermentation conditions and improved collection efficiency using dual cyclone equipment to enhance fungal conidia production,” Biocontrol Science & Technology 25(9), 1011–1023 (2015).
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P. Wang, H. Liu, Y. Zhao, Y. Gu, W. Chen, L. Wang, L. Li, X. Zhao, W. Lei, and Y. Hu, “Electromagnetic attenuation characteristics of microbial materials in the infrared band,” Appl. Spectrosc. 70(9), 1456–1463 (2016).
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H. Liu, X. Zhao, M. Guo, H. Liu, and Z. Zheng, “Growth and metabolism of Beauveria bassiana spores and mycelia,” BMC Microbiol. 15(1), 267 (2015).
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H. Liu, X. Zhao, M. Guo, H. Liu, and Z. Zheng, “Growth and metabolism of Beauveria bassiana spores and mycelia,” BMC Microbiol. 15(1), 267 (2015).
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H. Liu, W. Peng, Y. Hu, G. Zhao, L. Hui, Z. Li, H. Wu, W. Li, and Z. Zheng, “Optimised fermentation conditions and improved collection efficiency using dual cyclone equipment to enhance fungal conidia production,” Biocontrol Science & Technology 25(9), 1011–1023 (2015).
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X. Li-Jones, H. B. Maring, and J. M. Prospero, “Effect of relative humidity on light scattering by mineral dust aerosol as measured in the marine boundary layer over the tropical Atlantic Ocean,” J. Geophys. Res. 103(D23), 31113–31121 (1998).
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M. Min, C. Dominik, J. W. Hovenier, A. D. Koter, and L. B. F. M. Waters, “The 10 m amorphous silicate feature of fractal aggregates and compact particles with complex shapes,” Astron. Astrophys. 445(3), 1005–1014 (2006).
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M. Lattuada, W. Hua, and M. Morbidelli, “Radial density distribution of fractal clusters,” Chem. Eng. Sci. 59(21), 4401–4413 (2004).
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T. Kozasa, J. Blum, and T. Mukai, “Optical properties of dust aggregates,” Astron. Astrophys. 263, 423–432 (1992).

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Y. Gu, Y. Hu, X. Zhao, C. Xi, W. Peng, and Z. Zheng, “Discrimination of viable and dead microbial materials with Fourier transform infrared spectroscopy in 3–5 micrometers,” Opt. Express 26(12), 15842–15850 (2018).
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H. Liu, W. Peng, Y. Hu, G. Zhao, L. Hui, Z. Li, H. Wu, W. Li, and Z. Zheng, “Optimised fermentation conditions and improved collection efficiency using dual cyclone equipment to enhance fungal conidia production,” Biocontrol Science & Technology 25(9), 1011–1023 (2015).
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X. Li-Jones, H. B. Maring, and J. M. Prospero, “Effect of relative humidity on light scattering by mineral dust aerosol as measured in the marine boundary layer over the tropical Atlantic Ocean,” J. Geophys. Res. 103(D23), 31113–31121 (1998).
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V. Després, J. A. Huffman, S. M. Burrows, C. Hoose, A. Safatov, G. Buryak, J. Fröhlich-Nowoisky, W. Elbert, M. Andreae, and U. Pöschl, “Primary biological aerosol particles in the atmosphere: a review,” Tellus B 64(1), 15598–153 (2012).
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M. Segal-Rosenheimer and R. Linker, “Impact of the non-measured infrared spectral range of the imaginary refractive index on the derivation of the real refractive index using the Kramers-Kronig transform,” J. Quant. Spectrosc. Radiat. Transfer 110(13), 1147–1161 (2009).
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L. Shen, F. Gu, J. Zhang, and Y. Liu, “The effect of relative humidity on the extinction coefficient of aerosols,” J. Light Scatt. 29, 251–256 (2017).

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[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Analysis of optical properties of bio-smoke materials in the 0.25-14 µm band,” Chin. Phys. B 28(3), 034201 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “A comparison of infrared extinction performances of bioaerosols and traditional smoke materials,” Optik 181, 293–300 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Aggregation-driven reductions in the mass extinction coefficient of bioaerosols,” Optik 184, 115–120 (2019).
[Crossref]

L. Li, Y. Hu, Y. Gu, X. Zhao, S. Xu, L. Yu, Z. M. Zheng, and P. Wang, “Infrared extinction performance of randomly oriented microbial-clustered agglomerate materials,” Appl. Spectrosc. 71(11), 2555–2562 (2017).
[Crossref]

P. Wang, H. Liu, Y. Zhao, Y. Gu, W. Chen, L. Wang, L. Li, X. Zhao, W. Lei, and Y. Hu, “Electromagnetic attenuation characteristics of microbial materials in the infrared band,” Appl. Spectrosc. 70(9), 1456–1463 (2016).
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Y. Hu, X. Zhao, Y. Gu, X. Chen, X. Wang, P. Wang, Z. Zheng, and X. J. S. C. M. Dong, “Significant broadband extinction abilities of bioaerosols,” Sci. China Mater. 62(7), 1033–1045 (2019).
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X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Aggregation-driven reductions in the mass extinction coefficient of bioaerosols,” Optik 184, 115–120 (2019).
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X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “A comparison of infrared extinction performances of bioaerosols and traditional smoke materials,” Optik 181, 293–300 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “Analysis of optical properties of bio-smoke materials in the 0.25-14 µm band,” Chin. Phys. B 28(3), 034201 (2019).
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D. J. Sun, Y. Hu, Y. Gu, Y. Wang, and L. Li, “Preparation and performance testing of metallic biologic particles,” Guangzi Xuebao 42(5), 555–558 (2013).
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M. Min, C. Dominik, J. W. Hovenier, A. D. Koter, and L. B. F. M. Waters, “The 10 m amorphous silicate feature of fractal aggregates and compact particles with complex shapes,” Astron. Astrophys. 445(3), 1005–1014 (2006).
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P. Zieger, U. Frieß, B. Henzing, G. D. Leeuw, U. Baltensperger, E. Weingartner, K. Clemer, S. Yilmaz, H. Irie, and R. Fierz-Schmidhauser, “Effects of relative humidity on aerosol light scattering and its importance for the comparison of remote sensing with in-situ measurements,” Geochmica Et Cosmochimica Acta 12, 3875–3890 (2010).

Wu, H.

H. Liu, W. Peng, Y. Hu, G. Zhao, L. Hui, Z. Li, H. Wu, W. Li, and Z. Zheng, “Optimised fermentation conditions and improved collection efficiency using dual cyclone equipment to enhance fungal conidia production,” Biocontrol Science & Technology 25(9), 1011–1023 (2015).
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Y. Gu, Y. Hu, X. Zhao, C. Xi, W. Peng, and Z. Zheng, “Discrimination of viable and dead microbial materials with Fourier transform infrared spectroscopy in 3–5 micrometers,” Opt. Express 26(12), 15842–15850 (2018).
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C. Li and H. Xiong, “3D simulation of the Cluster–Cluster Aggregation model,” Comput. Phys. Commun. 185(12), 3424–3429 (2014).
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Zhang, J.

L. Shen, F. Gu, J. Zhang, and Y. Liu, “The effect of relative humidity on the extinction coefficient of aerosols,” J. Light Scatt. 29, 251–256 (2017).

Zhao, G.

H. Liu, W. Peng, Y. Hu, G. Zhao, L. Hui, Z. Li, H. Wu, W. Li, and Z. Zheng, “Optimised fermentation conditions and improved collection efficiency using dual cyclone equipment to enhance fungal conidia production,” Biocontrol Science & Technology 25(9), 1011–1023 (2015).
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Y. Gu, Y. Hu, X. Zhao, X. Chen, and Z. Zheng, “Combined analysis of static and dynamic extinction characteristics of microbial spores and mycelia as a mid-infrared extinction material,” Optik 176, 535–541 (2019).
[Crossref]

X. Zhao, Y. Hu, Y. Gu, X. Chen, X. Wang, P. Wang, and X. Dong, “A comparison of infrared extinction performances of bioaerosols and traditional smoke materials,” Optik 181, 293–300 (2019).
[Crossref]

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[Crossref]

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Figures (6)

Fig. 1.
Fig. 1. Structures of bioaerosol. (a, b) Electron micrographs of AN0913 spores and AO0907 spores. (c) Agglomerated particle structures constructed by the cluster-cluster aggregation model to describe the structures of the bioaerosol materials when they are floating in space.
Fig. 2.
Fig. 2. Schematic diagram of the aerosol chamber experiment.
Fig. 3.
Fig. 3. Complex refractive index of the two kinds of bioaerosol. (a) Real part of complex refractive index. (b) Imaginary part of complex refractive index.
Fig. 4.
Fig. 4. Humidity growth model of bioaerosol. (a-d)Humidity growth model of complex refractive index: (a) and (b) for AN0913 spores, (c) and (d) for AO0907 spores. (e) Humidity growth model of bioaerosol particle size.
Fig. 5.
Fig. 5. Simulation results of extinction performance parameters in different humidity conditions. (a, c-f) Extinction performance parameters of AN0913 spores in different humidity conditions. (b) Contour map of transmittance simulation results of AN0913 spores. (g, h) Contrast analysis of transmittance contour map and absorption coefficient spectrum of the two spores.
Fig. 6.
Fig. 6. Percentage increases of the attenuation ability per unit concentration as the relative humidity increase from 70% to 80% and 90% in the four wavebands. (a)Broadband attenuation ability per unit concentration of AN0913 spores in three relative humidity conditions. (b) Broadband attenuation ability per unit concentration of AO0907 spores in three relative humidity conditions of AO0907 spores.

Tables (2)

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Table 1. The model of the light sources and detectors in the experiment

Tables Icon

Table 2. Results of the aerosol chamber experiment

Equations (2)

Equations on this page are rendered with MathJax. Learn more.

m = m w + ( m 0 m w ) ( r 0 r R H ) 3 ,
r 0 r R H = ( 1 R H ) 1 / 1 u u ,

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