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Anemophilous (wind‐driven) pollen is one type of primary biological aerosol particle, which can rupture under high humidity conditions and form smaller sub‐pollen particles (SPPs). Both pollen and SPPs can reach the upper troposphere under convective conditions, acting as cloud condensation nuclei (CCN) and ice nucleating particles (INPs), thus influencing cloud formation and precipitation. However, the impacts of these biological aerosols on cold cloud formation and local climate remain unclear as there are large uncertainties on their emission flux and ice nucleating abilities. Here, we incorporate pollen emission and rupture processes in the Weather Research and Forecasting Model with Chemistry (WRF‐Chem) simulations and update the Morrison microphysics scheme within WRF‐Chem using aerosol‐aware INP parameterizations to account for pollen in addition to other anthropogenic and biogenic aerosol. INP parameterizations for pollen and SPP are derived from laboratory experiments. When including pollen rupture rates as observed in a series of chamber studies, SPP concentrations increase, leading to an increase of cloud ice and water by up to 50% and potentially extending the duration of the convective system. Among all simulated hydrometeors, graupel and raindrops exhibit the largest enhancements from the inclusion of SPPs, with intensifying precipitation at the backside of the convective system and a greater spatial extent. Sensitivity simulations indicate that SPPs have a greater effect on cloud microphysical processes than whole pollen grains, and further observational evidence is needed to constrain these processes. Plain Language Summary: Pollen grains are emitted by vegetation and carry the reproductive material of plants. Under certain conditions (e.g., high humidity, lightning), pollen grains can rupture to form smaller sub‐pollen particles (SPPs). Both intact pollen grain and SPPs have been observed to influence the formation of cloud liquid droplets and ice crystals, potentially impacting cloud properties and precipitation. In this study, we include pollen emission and pollen‐cloud interactions into a meteorology‐chemistry model and investigate the effects of pollen grains and SPPs on a strong thunderstorm event associated with a mesoscale convective system. We find that SPPs have a greater impact than whole pollen grains on the convective system properties by increasing cloud ice and water content, facilitating the transition of cloud droplets and ice into graupel, and ultimately intensifying precipitation. These changes alter the impact of the convective system, leading to an extension of the storm width and lengthening of its duration. Key Points: Sub‐pollen particles (SPPs) enhance cloud microphysical processes more than intact pollen grainsSPPs influence the spatial extent and vertical structure of convective systemsSimulated SPP impacts are intensified when incorporating laboratory measured pollen rupture rates [ABSTRACT FROM AUTHOR]

A Love-type acoustic wave sensor (AT-cut quartz substrate, SiO2 guiding layer) with a center frequency of approximately 120 MHz was used to detect a simulant of pathogenic botulinum neurotoxin type A—recombinant of BoNT-A light chain—in liquid samples. The sensor was prepared by immobilizing monoclonal antibodies specific for botulinum neurotoxin via a thiol monolayer deposited on a gold substrate. Studies have shown that the sensor enables selective analyte detection within a few minutes. In addition, the sensor can be used several times (regeneration of the sensor is possible using a low pH buffer). Nevertheless, the detectability of the analyte is relatively low compared to other analytical techniques that can be used for rapid detection of botulinum neurotoxin. The obtained results confirm the operation of the proposed sensor and give hope for further development of this label-free technique for detecting botulinum neurotoxin. [ABSTRACT FROM AUTHOR]

A Love-type acoustic wave sensor (AT-cut quartz substrate, SiO2 guiding layer) with a center frequency of approximately 120 MHz was used to detect a simulant of pathogenic botulinum neurotoxin type A—recombinant of BoNT-A light chain—in liquid samples. The sensor was prepared by immobilizing monoclonal antibodies specific for botulinum neurotoxin via a thiol monolayer deposited on a gold substrate. Studies have shown that the sensor enables selective analyte detection within a few minutes. In addition, the sensor can be used several times (regeneration of the sensor is possible using a low pH buffer). Nevertheless, the detectability of the analyte is relatively low compared to other analytical techniques that can be used for rapid detection of botulinum neurotoxin. The obtained results confirm the operation of the proposed sensor and give hope for further development of this label-free technique for detecting botulinum neurotoxin.

We present results from a study evaluating the utility of supervised machine learning to classify single particle ultraviolet laser-induced fluorescence (UV-LIF) signatures to investigate airborne primary biological aerosol particle (PBAP) concentrations in a busy, multifunctional building using a Multiparameter Bioaerosol Spectrometer. First we introduce and demonstrate a gradient boosting ensemble decision tree algorithm’s ability to accurately classify laboratory generated PBAP samples into broad taxonomic classes with a high level of accuracy. We then develop a framework to appraise the classification accuracy and performance using the Hellinger distance metric to compare product parameter probability density function similarity; this framework showed that key training classes were sufficiently different in terms of particle fluorescence and morphology to facilitate classification. We also demonstrate the utility of including advanced morphological parameters to minimise inter-class conflation and improve classification confidence, where relying on the fluorescent spectra alone would likely result in misattribution. Finally, we apply these methods to ambient data collected within a large multi-functional building where ambient bacterial- and fungal-like classes were identified to display trends corresponding to human activity; fungal-like classes displayed a consistent diurnal trend with a maximum at midday and hourly peaks correlating to movements within the building; bacteria-like aerosol displayed complex, episodic events during opening hours. All PBAP classes fell to low baseline concentrations when the building was unoccupied overnight and at weekends.

Detecting biological threat aerosol is difficult in that a small cloud lasting only a few seconds at a point location may contain sufficient material to infect large numbers of exposed individuals. Clinical analytical methods require relative large amounts of the sample in liquid form to facilitate positive measurements. Biological agents may be fragile because of their lipid membranes that can be susceptible to harsh sample collection treatment. Damaged organisms may render subsequent analyses to be invalid. Virtual impaction (VI) sample collectors have been theorized to provide usable concentration rates yet are sufficiently gentle with the aerosol particles to preserve cellular viability. This review will discuss different implementations of VI technology and examine their merits. Outstanding issues will be outlined to aid future experimentation.

The utilization of metalworking fluids in the metal machining technological process provides, apart from benefits, certain negatives that are mainly associated with air contamination of the working environment. Typical health problems that result from inhalant exposure of metalworking machine operators to the metalworking fluid mist include respiratory diseases (asthma, chronic bronchitis, hypersensitivity pneumonitis), cancer, and skin diseases. Possible health risks posed by the utilization of metalworking fluids, various methods for measuring their concentration in the working environment, and treatment of MWFs are discussed. A typical particle size range of liquid aerosol (oil mist) is in the range from 0.1 to 10 µm and more than 75% of MWF particulate matter is located in the sphere of respirable fraction (particle size less than 5 µm) that poses the highest risk for the human body. MWF aerosol mass concentration in the working atmosphere varies depending on the type of working activity, and MWFs used in a wider range (average exposure in the range of 0.55 to 5.36 mg⋅m-3 ). Attention also should be paid to microbiological contamination of water-based MWFs, when they are used or stored after dilution for longer term. The most often occurring microbial species at considerable concentration is the bacteria Pseudomonas pseudoalcaligenes. Other important species include Mycobacterium, Pseudomonas, Morganella, Citrobacter freundii, Acinetobacter, Bacillus, Fusarium, Trichoderma, Penicillium, etc. [ABSTRACT FROM AUTHOR]

Rapid analysis of transport and diffusion of chemical and biological aerosols and contaminants in an urban environment is a critical part of any homeland security response team. High performance computing (HPC) is a valuable technique for such analysis. The time constraint needed to create fully developed complex 3D city terrain models to support such dispersion simulations requires a task of converting agency data to the format necessary on the simulation platform. Numerous data sets have been employed in the development of complex 3D city models. Such data include the use of multi-layer building morphology data, the use of geographic information system (GIS) based shapefiles and digital elevation models (DEM), and the use of remote sensing data such as Light Detection and Ranging (LIDAR). The constructed geometry models are used to generate large-scale computational domains on a platform that supports our HPC tools. These tools include fully automated unstructured mesh generation, parallel and scalable flow solvers based on stabilized finite element formulations and a remote client-server environment for large-scale flow visualization. The stabilized finite element formulations, which are based on the SUPG and PSPG techniques, are parallelized and vectorized on the Cray X1. The 3D validation problem involves transient simulation of flow past a building with a source point releasing traces. A 3D application problem is presented to demonstrate the capability of the integrated HPC tools. [ABSTRACT FROM AUTHOR]

Abstract: Events following the anthrax letter incidences in 2001 changed many previously held assumptions regarding biological aerosol hazards. As there were significant fatalities resulting from the sorting of a single anthrax letter, it suggests there is a need to reevaluate how best to measure biological aerosols and to use the information to make accurate predictions. This paper describes the biological aerosol created from manipulating envelopes containing Bacillus subtilis globigii spores (a simulant for anthrax). In addition, the measurements on dispersion of spores from an envelope processed by a mail sorter provide important dynamic aerosol characteristics, information previously unavailable for health risk assessment. The findings produced a number of significant aerosol dosage estimates related to spore contaminated letters. Graphic presentations show significant hazard in handling anthrax-laced letters. Aerosol particle dynamics are described and specific lethal dosage values are listed for a range of activities; these will be useful in assisting the modeling community to create more realistic predictions in hazard assessment studies. [Copyright &y& Elsevier]

There are practical and valid reasons topresent biological field trial referenceresults as agent containing particles per literof air (ACPLA). However, workers in biologicalaerosol research have a need to know how manyviable individual organisms are contained in asingle particle of a given diameter. Anecdotalevidence may exist suggesting that the task hasbeen accomplished but without a way toreplicate the measurements, it is difficult toaccept unsubstantiated claims. It is verydifficult to declare a finite number thatsatisfies all the experimental requirements, asthe problem is a statistical probability issue. This paper describes a method for estimatingthe number with practical instructions forreplicating the work in other laboratories. The test aerosol was contained in a 90 m3chamber at concentrations as low as 5 ACPLA. Amodified version of slit sampler collectedviable particles. A statistical method was usedto demonstrate sampling predictability at 95%confidence level. By using glass fiber filtersmounted in a dichotomous sampler, samplingefficiencies were estimated for a variety ofcommon aerosol collectors. The accumulated datapermitted the estimation of the number ofviable spores per particle. For a 2.5 to4 µm particle, arguments have beenpresented for considering 4.5 as the mostprobable ACPLA value. [ABSTRACT FROM AUTHOR]

We present results from a study evaluating the utility of supervised machine learning to classify single particle ultraviolet laser-induced fluorescence (UV-LIF) signatures to investigate airborne primary biological aerosol particle (PBAP) concentrations in a busy, multifunctional building using a Multiparameter Bioaerosol Spectrometer. First we introduce and demonstrate a gradient boosting ensemble decision tree algorithm's ability to accurately classify laboratory generated PBAP samples into broad taxonomic classes with a high level of accuracy. We then develop a framework to appraise the classification accuracy and performance using the Hellinger distance metric to compare product parameter probability density function similarity; this framework showed that key training classes were sufficiently different in terms of particle fluorescence and morphology to facilitate classification. We also demonstrate the utility of including advanced morphological parameters to minimise inter-class conflation and improve classification confidence, where relying on the fluorescent spectra alone would likely result in misattribution. Finally, we apply these methods to ambient data collected within a large multi-functional building where ambient bacterial- and fungal-like classes were identified to display trends corresponding to human activity; fungal-like classes displayed a consistent diurnal trend with a maximum at midday and hourly peaks correlating to movements within the building; bacteria-like aerosol displayed complex, episodic events during opening hours. All PBAP classes fell to low baseline concentrations when the building was unoccupied overnight and at weekends. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]