Spectrally-resolved fluorescence cross sections of aerosolized biological live agents and simulants using five excitation wavelengths in a BSL-3 laboratory

Bioaerosols in the atmosphere: A comprehensive review on detection methods, concentration and influencing factors

In the past few decades, especially since the outbreak of the coronavirus disease (COVID-19), the effects of atmospheric bioaerosols on human health, the environment, and climate have received great attention. To evaluate the impacts of bioaerosols quantitatively, it is crucial to determine the types of bioaerosols in the atmosphere and their spatial-temporal distribution. We provide a concise summary of the online and offline observation strategies employed by the global research community to sample and analyze atmospheric bioaerosols. In addition, the quantitative distribution of bioaerosols is described by considering the atmospheric bioaerosols concentrations at various time scales (daily and seasonal changes, for example), under various weather, and different underlying surfaces. Finally, a comprehensive summary of the reasons for the spatiotemporal distribution of bioaerosols is discussed, including differences in emission sources, the impact process of meteorological factors and environmental factors. This review of information on the latest research progress contributes to the emergence of further observation strategies that determine the quantitative dynamics of public health and ecological effects of bioaerosols.

Environmental sampling for disease surveillance: Recent advances and recommendations for best practice

The study of infectious diseases includes both the progression of the disease in its host and how it transmits between hosts. Understanding disease transmission is important for recommending effective interventions, protecting healthcare workers, and informing an effective public health response. Sampling the environment for infectious diseases is critical to public health since it can provide an understanding of the mechanisms of transmission, characterization of contamination in hospitals and other public areas, and the spread of a disease within a community. Measurements of biological aerosols, particularly those that may cause disease, have been an ongoing topic of research for decades, and so a wide variety of technological solutions exist. This wide field of possibilities can create confusion, particularly when different approaches yield different answers. Therefore, guidelines for best practice in this area are important to allow more effective use of this data in public health decisions. This review examines air, surface and water/wastewater sampling methods, with a focus on aerosol sampling, and a goal of recommending approaches to designing and implementing sampling systems that may incorporate multiple strategies. This is accomplished by developing a framework for designing and evaluating a sampling strategy, reviewing current practices and emerging technologies for sampling and analysis, and recommending guidelines for best practice in the area of aerosol sampling for infectious disease.

Performance of feature extraction method for classification and identification of proteins based on three-dimensional fluorescence spectrometry

Three-dimensional excitation emission matrix (EEM) fluorescence spectroscopy was employed to discriminate protein samples comprising bovine serum albumin, neurotensin, ovalbumin, ricin, trypsin from bovine pancreas and trypsin from porcine pancreas. Two methods of feature extraction with and without parameterization were applied to the spectral data in order to evaluate their performance of discrimination between protein samples. The discrimination of protein samples was conducted by k-means clustering algorithm and eigenvalue extracting procedure based on principal component analysis (PCA). It was found that the method of feature extraction without parameterization performed best, correctly attributing 100% of the spectral data in the condition of two principal components (PCs) captured. Features extracted with spectral parameterization failed to separate ricin and trypsin from bovine pancreas in same condition. Without spectral parameterization, less dimensionality and unique principal components captured by PCA indicates the spectrally-resolved features of corresponding protein samples. By clustering using each spectrum at fixed excitation wavelength, excitation wavelengths matched with common intrinsic fluorophores were found to be more sensitive to the classification accuracy. Contributions of spectral features extracted from EEM to the principal components were discussed and demonstrated their feature differentiation capabilities among six protein samples. These results reveal that appropriate extraction approach of features in combination with PCA analysis could be used in discrimination of protein samples at species level as a spectroscopic diagnostic tool. Our study provides fundamental references about computational strategies when EEM are used to explore proteins in ambient environment.

A new fluorescence-based methodology for studying bioaerosol scavenging processes using a hyperspectral LIF-LIDAR remote sensing system

This paper presents a novel experimental approach to in-situ study of atmospheric phenomena such as nucleation scavenging by biological seeds, bio-droplet dehydration, and bioaerosol's particle scavenging by raindrops. Our methodology is based on the analysis of the dynamical changes of fluorescence signal. We use a remote sensing system based on a homebuilt hyperspectral laser induced fluorescence (LIF) Lidar to measure the transient back-fluorescence and backscattering signals. The spectral line shape of the transient fluorescence associated with an aerosolized tryptophan solution was first analyzed in the laboratory. It then used to study bioaerosol phase transitions between wet and dry conditions. The experiments were first conducted in a dynamic aerosol cell where we repetitively create and monitor the droplets containing bioaerosol cloud starting from its early formation till its total evaporation. The LIF-Lidar was used to simultaneously measure back-fluorescence, scattering and transmission. These measurements were synchronized with the generation of droplets containing bioaerosol and with the monitoring of aerosol's size distribution and ambient conditions. A novel optical receiver design was used to simultaneously detect both back-fluorescence polarization components. Results showed that along with droplet's evaporation process, bioaerosol's fluorescence spectrum exhibit a blue shift, known as the dynamic Stokes-shifts, of ∼2000 cm^-1 and an increase in its fluorescence anisotropy. To the best of our knowledge, this is the first report of fluorescence Stokes-shifts and anisotropy within microdroplets containing a biological solution due to wet-dry phase transitions. This method was also used to quantify scavenging of biological particle by raindrops from 100 m. It shows that valuable information can be derived from analyzing the fluorescence spectrum of bioaerosol within a cloud and demonstrate the potential of a LIF-LIDAR remote system to perform in-situ studies of scavenging processes.

Potential of laser-induced fluorescence-light detection and ranging for future stand-off virus surveillance

Viruses remain a significant public health concern worldwide. Recently, humanity has faced deadly viral infections, including Zika, Ebola and the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The threat is associated with the ability of the viruses to mutate frequently and adapt to different hosts. Thus, there is the need for robust detection and classification of emerging virus strains to ensure that humanity is prepared in terms of vaccine and drug developments. A point or stand-off biosensor that can detect and classify viruses from indoor and outdoor environments would be suited for viral surveillance. Light detection and ranging (LiDAR) is a facile and versatile tool that has been explored for stand-off detection in different environments including atmospheric, oceans and forest sensing. Notably, laser-induced fluorescence-light detection and ranging (LIF-LiDAR) has been used to identify MS2 bacteriophage on artificially contaminated surgical equipment or released amidst other primary biological aerosol particles in laboratory-like close chamber. It has also been shown to distinguish between different picornaviruses. Currently, the potentials of the LIF-LiDAR technology for real-time stand-off surveillance of pathogenic viruses in indoor and outdoor environments have not been assessed. Considering the increasing applications of LIF-LiDAR for potential microbial pathogens detection and classification, and the need for more robust tools for viral surveillance at safe distance, we critically evaluate the prospects and challenges of LIF-LiDAR technology for real-time stand-off detection and classification of potentially pathogenic viruses in various environments.

Intercomparison of Multiple UV-LIF Spectrometers Using the Aerosol Challenge Simulator

Measurements of primary biological aerosol particles (PBAPs) have been conducted worldwide using ultraviolet light-induced fluorescence (UV-LIF) spectrometers. However, how these instruments detect and respond to known biological and non-biological particles, and how they compare, remains uncertain due to limited laboratory intercomparisons. Using the Defence Science and Technology Laboratory, Aerosol Challenge Simulator (ACS), controlled concentrations of biological and non-biological aerosol particles, singly or as mixtures, were produced for testing and intercomparison of multiple versions of the Wideband Integrated Bioaerosol Spectrometer (WIBS) and Multiparameter Bioaerosol Spectrometer (MBS). Although the results suggest some challenges in discriminating biological particle types across different versions of the same UV-LIF instrument, a difference in fluorescence intensity between the non-biological and biological samples could be identified for most instruments. While lower concentrations of fluorescent particles were detected by the MBS, the MBS demonstrates the potential to discriminate between pollen and other biological particles. This study presents the first published technical summary and use of the ACS for instrument intercomparisons. Within this work a clear overview of the data pre-processing is also presented, and documentation of instrument version/model numbers is suggested to assess potential instrument variations between different versions of the same instrument. Further laboratory studies sampling different particle types are suggested before use in quantifying impact on ambient classification.

Size-Resolved Single-Particle Fluorescence Spectrometer for Real-Time Analysis of Bioaerosols: Laboratory Evaluation and Atmospheric Measurements

Characteristic particle size, fluorescence intensity, and fluorescence spectra are important features to detect and categorize bioaerosols. A prototype size-resolved single-particle fluorescence spectrometer (S2FS) was developed to simultaneously measure aerodynamic diameters and fluorescence spectra. Emission spectra are dispersed in 512 channels from 370 to 610 nm, where a major portion of biological fluorescence emission occurs. The S2FS consists of an aerodynamic particle sizer and a fluorescence spectrometer with a 355 nm laser excitation source and an intensified charge-coupled device as the detector. Highly fluorescent particles, such as Ambrosia artemisiifolia pollen and Olea europaea pollen, can be distinguished by the S2FS on a single-particle level. For weakly fluorescent particles, fluorescence spectra can only be obtained by averaging multiple particles (between 100 and 3000) of the same kind. Preliminary ambient measurements in Mainz (Germany, central Europe) show that an emission peak at ∼440 nm was frequently observed for fluorescent fine particles (0.5-1 μm). Fluorescent fine particles accounted for 2.8% on average based on the number fraction in the fine mode. Fluorescent coarse particles (>1 μm) accounted for 8.9% on average based on the number fraction, with strongest occurrence observed during a thunderstorm and in the morning.

Discriminating Bio-aerosols from Non-Bio-aerosols in Real-Time by Pump-Probe Spectroscopy

The optical identification of bioaerosols in the atmosphere and its discrimination against combustion related particles is a major issue for real-time, field compatible instruments. In the present paper, we show that by embedding advanced pump-probe depletion spectroscopy schemes in a portable instrument, it is possible to discriminate amino acid containing airborne particles (bacteria, humic particles, etc.) from poly-cyclic aromatic hydrocarbon containing combustion particles (Diesel droplets, soot, vehicle exhausts) with high selectivity. Our real-time, multi-modal device provides, in addition to the pump-probe depletion information, fluorescence spectra (over 32 channels), fluorescence lifetime and Mie scattering patterns of each individually flowing particle in the probed air.