Colorimetric Systems for the Detection of Bacterial Contamination: Strategy and Applications

Bacterial contamination is a public health concern worldwide causing enormous social and economic losses. For early diagnosis and adequate management to prevent or treat pathogen-related illnesses, extensive effort has been put into the development of pathogenic bacterial detection systems. Colorimetric sensing systems have attracted increasing attention due to their simple and single-site operation, rapid signal readout with the naked eye, ability to operate without external instruments, portability, compact design, and low cost. In this article, recent trends and advances in colorimetric systems for the detection and monitoring of bacterial contamination are reviewed. This article focuses on pathogen detection strategies and technologies based on reaction factors that affect the color change for visual readout. Reactions used in each strategy are introduced by dividing them into the following five categories: external pH change-induced pH indicator reactions, intracellular enzyme-catalyzed chromogenic reactions, enzyme-like nanoparticle (NP)-catalyzed substrate reactions, NP aggregation-based reactions, and NP accumulation-based reactions. Some recently developed colorimetric systems are introduced, and their challenges and strategies to improve the sensing performance are discussed.

Evaluating the effectiveness of drones for quantifying invasive upside-down jellyfish (Cassiopea sp.) in Lake Macquarie, Australia

Upside-down jellyfish (Cassiopea sp.) are mostly sedentary, benthic jellyfish that have invaded estuarine ecosystems around the world. Monitoring the spread of this invasive jellyfish must contend with high spatial and temporal variability in abundance of individuals, especially around their invasion front. Here, we evaluated the utility of drones to survey invasive Cassiopea in a coastal lake on the east coast of Australia. To assess the efficacy of a drone-based methodology, we compared the densities and counts of Cassiopea from drone observations to conventional boat-based observations and evaluated cost and time efficiency of these methods. We showed that there was no significant difference in Cassiopea density measured by drones compared to boat-based methods along the same transects. However, abundance estimates of Cassiopea derived from scaling-up transect densities were over-inflated by 319% for drones and 178% for boats, compared to drone-based counts of the whole site. Although conventional boat-based survey techniques were cost-efficient in the short-term, we recommend doing whole-of-site counts using drones. This is because it provides a time-saving and precise technique for long-term monitoring of the spatio-temporally dynamic invasion front of Cassiopea in coastal lakes and other sheltered marine habitats with relatively clear water.

Metal-Organic Framework Based Gas Sensors

The ever-increasing concerns over indoor/outdoor air quality, industrial gas leakage, food freshness, and medical diagnosis require miniaturized gas sensors with excellent sensitivity, selectivity, stability, low power consumption, cost-effectiveness, and long lifetime. Metal-organic frameworks (MOFs), featuring structural diversity, large specific surface area, controllable pore size/geometry, and host-guest interactions, hold great promises for fabricating various MOF-based devices for diverse applications including gas sensing. Tremendous progress has been made in the past decade on the fabrication of MOF-based sensors with elevated sensitivity and selectivity toward various analytes due to their preconcentrating and molecule-sieving effects. Although several reviews have recently summarized different aspects of this field, a comprehensive review focusing on MOF-based gas sensors is absent. In this review, the latest advance of MOF-based gas sensors relying on different transduction mechanisms, for example, chemiresistive, capacitive/impedimetric, field-effect transistor or Kelvin probe-based, mass-sensitive, and optical ones are comprehensively summarized. The latest progress for making large-area MOF films essential to the mass-production of relevant gas sensors is also included. The structural and compositional features of MOFs are intentionally correlated with the sensing performance. Challenges and opportunities for the further development and practical applications of MOF-based gas sensors are also given.

Measurement of circular intensity differential scattering (CIDS) from single airborne aerosol particles for bioaerosol detection and identification

The circular intensity differential scattering (CIDS), i.e. the normalized Mueller matrix element -S₁₄/S₁₁, can be used to detect the helical structures of DNA molecules in biological systems, however, no CIDS measurement from single particles has been reported to date. We report an innovative method for measuring CIDS phase functions from single particles individually flowing through a scattering laser beam. CIDS signals were obtained from polystyrene latex (PSL) microspheres with or without coating of DNA molecules, tryptophan particles, and aggregates of B. subtilis spores, at the size of 3 μm in diameter. Preliminary results show that this method is able to measure CIDS phase function in tens of microseconds from single particles, and has the ability to identify particles containing biological molecules.

Comparison of Minimally Invasive Monitoring Methods and Live Trapping in Mammals

The conservation and management of wildlife requires the accurate assessment of wildlife population sizes. However, there is a lack of synthesis of research that compares methods used to estimate population size in the wild. Using a meta-analysis approach, we compared the number of detected individuals in a study made using live trapping and less invasive approaches, such as camera trapping and genetic identification. We scanned 668 papers related to these methods and identified data for 44 populations (all focused on mammals) wherein at least two methods (live trapping, camera trapping, genetic identification) were used. We used these data to quantify the difference in number of individuals detected using trapping and less invasive methods using a regression and used the residuals from each regression to evaluate potential drivers of these trends. We found that both trapping and less invasive methods (camera traps and genetic analyses) produced similar estimates overall, but less invasive methods tended to detect more individuals compared to trapping efforts (mean = 3.17 more individuals). We also found that the method by which camera data are analyzed can significantly alter estimates of population size, such that the inclusion of spatial information was related to larger population size estimates. Finally, we compared counts of individuals made using camera traps and genetic data and found that estimates were similar but that genetic approaches identified more individuals on average (mean = 9.07 individuals). Overall, our data suggest that all of the methods used in the studies we reviewed detected similar numbers of individuals. As live trapping can be more costly than less invasive methods and can pose more risk to animal well-fare, we suggest minimally invasive methods are preferable for population monitoring when less-invasive methods can be deployed efficiently.

COVID surveillance robot: Monitoring social distancing constraints in indoor scenarios

Observing social/physical distancing norms between humans has become an indispensable precaution to slow down the transmission of COVID-19. We present a novel method to automatically detect pairs of humans in a crowded scenario who are not maintaining social distancing, i.e. about 2 meters of space between them using an autonomous mobile robot and existing CCTV (Closed-Circuit TeleVision) cameras. The robot is equipped with commodity sensors, namely an RGB-D (Red Green Blue-Depth) camera and a 2-D lidar to detect social distancing breaches within their sensing range and navigate towards the location of the breach. Moreover, it discreetly alerts the relevant people to move apart by using a mounted display. In addition, we also equip the robot with a thermal camera that transmits thermal images to security/healthcare personnel who monitors COVID symptoms such as a fever. In indoor scenarios, we integrate the mobile robot setup with a static wall-mounted CCTV camera to further improve the number of social distancing breaches detected, accurately pursuing walking groups of people etc. We highlight the performance benefits of our robot + CCTV approach in different static and dynamic indoor scenarios.

Low-cost Gent type sampler constructed for urban atmospheric aerosol sampling

The importance of studying the atmospheric pollution due to its effects on human health and other ecosystems, the inexistence of national production of equipment for air sample collection, and the high cost of the imported equipment (especially in developing countries) led the authors of the present work to construct a low-cost Gent type sampler. The construction of the sampler was carried out by combining low-cost materials with good mechanical strength (such as nylon 6.0), hydraulic piping PVC, and the use of a 3D printer. The innovation of the present work is the employment of a 3D printer using ABS polymer to create the grids that cannot be machined. In addition to the sampler, the system is composed of a vacuum pump, a gas meter, and a rotameter. The total cost of the sampling system amounted at about 1200 USD, and the cost of the manufactured Gent type sampler did not reach 100 USD. The results obtained while using this set for sampling atmospheric aerosol for a period of 11 months were compared with the mass concentration of PM₁₀ obtained from the official environmental company, CETESB of São Paulo State, Brazil, showing good correlation with those from CETESB - which confirmed its effectiveness and suitability for use. The low cost, easy operation, and versatility of the built Gent type sampler enable its use for scientific and academic purposes. The equipment can be useful in environmental monitoring networks, in low-income regions, and as an instrument for environmental education used in universities.

Erosion and deposition vulnerability of small (<5,000 km2) tropical islands

The tropics are naturally vulnerable to watershed erosion. This region is rapidly growing (projected to be 50% of the global population by 2050) which exacerbates erosional issues by the subsequent land use change. The issue is particularly of interest on the many (~45,000) small tropical (<5,000 km²) islands, and their >115M residents, where ecotourism and sediment intolerant ecosystems such as coral reefs are the main driver of their economies. However, vulnerability to erosion and deposition is poorly quantified in these regions due to the misclassification or exclusion of small islands in coarse global analyses. We use the only vulnerability assessment method that connects watershed erosion and coastal deposition to compare locally sourced, high-resolution datasets (5 x 5 m) to satellite-collected, remotely sensed low-resolution datasets (463 x 463 m). We find that on the island scale (~52 km²) the difference in vulnerability calculated by the two methods is minor. On the watershed scale however, low-resolution datasets fail to accurately demonstrate watershed and coastal deposition vulnerability when compared to high-resolution analysis. Specifically, we find that anthropogenic development (roads and buildings) is poorly constrained at a global scale. Structures and roads are difficult to identify in heavily forested regions using satellite algorithms and the rapid, ongoing rate of development aggravates the issue. We recommend that end-users of this method obtain locally sourced anthropogenic development datasets for the best results while using low resolution datasets for the other variables. Fortunately, anthropogenic development data can be easily collected using community-based research or identified using satellite imagery by any level of user. Using high-resolution results, we identify a development trend across St. John and regions that are both high risk and possible targets for future development. Previously published modeled and measured sedimentation rates demonstrate the method is accurate when using low-resolution or high-resolution data but, anthropogenic development, watershed slope, and earthquake probability datasets should be of the highest resolution depending on the region specified.

Local- and regional-scale racial and ethnic disparities in air pollution determined by long-term mobile monitoring

Disparity in air pollution exposure arises from variation at multiple spatial scales: along urban-to-rural gradients, between individual cities within a metropolitan region, within individual neighborhoods, and between city blocks. Here, we improve on existing capabilities to systematically compare urban variation at several scales, from hyperlocal (<100 m) to regional (>10 km), and to assess consequences for outdoor air pollution experienced by residents of different races and ethnicities, by creating a set of uniquely extensive and high-resolution observations of spatially variable pollutants: NO, NO2, black carbon (BC), and ultrafine particles (UFP). We conducted full-coverage monitoring of a wide sample of urban and suburban neighborhoods (93 km2 and 450,000 residents) in four counties of the San Francisco Bay Area using Google Street View cars equipped with the Aclima mobile platform. Comparing scales of variation across the sampled population, greater differences arise from localized pollution gradients for BC and NO (pollutants dominated by primary sources) and from regional gradients for UFP and NO2 (pollutants dominated by secondary contributions). Median concentrations of UFP, NO, and NO2 are, for Hispanic and Black populations, 8 to 30% higher than the population average; for White populations, average exposures to these pollutants are 9 to 14% lower than the population average. Systematic racial/ethnic disparities are influenced by regional concentration gradients due to sharp contrasts in demographic composition among cities and urban districts, while within-group extremes arise from local peaks. Our results illustrate how detailed and extensive fine-scale pollution observations can add new insights about differences and disparities in air pollution exposures at the population scale.

Modeling hyperspectral normalized water-leaving radiance in a dynamic coastal ecosystem

Next-generation satellite sensors such as the Ocean Color Instrument (OCI) aboard the NASA Plankton, Aerosols, Cloud and ocean Ecosystem (PACE) satellite and the proposed Surface Biology and Geology (SBG) sensor will provide hyperspectral measurements of water-leaving radiances. However, acquiring sufficiently accurate in situ validation data in coastal ecosystems remains challenging. Here we modeled hyperspectral normalized water-leaving radiance ([L_W(λ)]_N) in a dynamic coastal ecosystem using in situ inherent optical properties (IOPs) as inputs to the Hydrolight radiative transfer model. By reducing uncertainty of modeled hyperspectral [L_W(λ)]_N (%RMSE ≤ 21%) relative to [L_W(λ)]_N derived from in situ radiometric measurements (%RMSE ≤ 33%), we introduce modeling as an alternative or complementary method to in-water radiometric profilers for validating satellite-derived hyperspectral data from coastal ecosystems.

Transport of Aerosols in Underground Mine Workings in Terms of SARS-CoV-2 Virus Threat

This paper presents a method of implementation and the results of aerosol dispersion tests in underground mine workings. Numerous tests were carried out to determine the potential risk of SARS-CoV-2 coronavirus infection in the underground environment of the mines. The influence of selected parameters of mine air on the possibility and method of aerosol transmission through ventilation routes was experimentally determined in real conditions. The concentration of additional aerosols in the class of ultrafine and fine aerosols increased with the distance from the generator, while the concentration of coarse particles decreased. Assuming the consumption of the solution with which aerosols were generated, even at a small level of 1 cm3/min., the number of additional aerosols was several hundred particles in one cubic centimeter of air at a distance of 50-70 m from the generator. The concentration of ultrafine particles in the range of 40-20,000 nm increased from 122 particles/cm3 to 209 particles/cm3 at air temperature of 12 °C and relative humidity of 95-96%, and from 90 particles/cm3 to 243 particles/cm3 at air temperature of 17 °C and relative humidity of 76-82%, with the increasing distance from the generator (10 m to 50 m).

Concurrent assessment of personal, indoor, and outdoor PM2.5 and PM1 levels and source contributions using novel low-cost sensing devices

The intensity, frequency, duration, and contribution of distinct PM2.5 sources in Asian households have seldom been assessed; these are evaluated in this work with concurrent personal, indoor, and outdoor PM2.5 and PM1 monitoring using novel low-cost sensing (LCS) devices, AS-LUNG. GRIMM-comparable observations were acquired by the corrected AS-LUNG readings, with R2 up to 0.998. Twenty-six non-smoking healthy adults were recruited in Taiwan in 2018 for 7-day personal, home indoor, and home outdoor PM monitoring. The results showed 5-min PM2.5 and PM1 exposures of 11.2 ± 10.9 and 10.5 ± 9.8 µg/m3 , respectively. Cooking occurred most frequently; cooking with and without solid fuel contributed to high PM2.5 increments of 76.5 and 183.8 µg/m3 (1 min), respectively. Incense burning had the highest mean PM2.5 indoor/outdoor (1.44 ± 1.44) ratios at home and on average the highest 5-min PM2.5 increments (15.0 µg/m3 ) to indoor levels, among all single sources. Certain events accounted for 14.0%-39.6% of subjects' daily exposures. With the high resolution of AS-LUNG data and detailed time-activity diaries, the impacts of sources and ventilations were assessed in detail.

Optimized workflow for unknown screening using gas chromatography high-resolution mass spectrometry expands identification of contaminants in silicone personal passive samplers

RATIONALE

Silicone wristbands have emerged as valuable passive samplers for monitoring of personal exposure to environmental contaminants in the rapidly developing field of exposomics. Once deployed, silicone wristbands collect and hold a wealth of chemical information that can be interrogated using high-resolution mass spectrometry (HRMS) to provide a broad coverage of chemical mixtures.

METHODS

Gas chromatography coupled to Orbitrap™ mass spectrometry (GC/Orbitrap™ MS) was used to simultaneously perform suspect screening (using in-house database) and unknown screening (using vendor databases) of extracts from wristbands worn by volunteers. The goal of this study was to optimize a workflow that allows detection of low levels of priority pollutants, with high reliability. In this regard, a data processing workflow for GC/Orbitrap™ MS was developed using a mixture of 123 environmentally relevant standards consisting of pesticides, flame retardants, organophosphate esters, and polycyclic aromatic hydrocarbons as test compounds.

RESULTS

The optimized unknown screening workflow using a search index threshold of 750 resulted in positive identification of 70 analytes in validation samples, and a reduction in the number of false positives by over 50%. An average of 26 compounds with high confidence identification, 7 level 1 compounds and 19 level 2 compounds, were observed in worn wristbands. The data were further analyzed via suspect screening and retrospective suspect screening to identify an additional 36 compounds.

CONCLUSIONS

This study provides three important findings: (1) a clear evidence of the importance of sample cleanup in addressing complex sample matrices for unknown analysis, (2) a valuable workflow for the identification of unknown contaminants in silicone wristband samplers using electron ionization HRMS data, and (3) a novel application of GC/Orbitrap™ MS for the unknown analysis of organic contaminants that can be used in exposomics studies.

Satellite Observations and Malaria: New Opportunities for Research and Applications

Satellite remote sensing provides a wealth of information about environmental factors that influence malaria transmission cycles and human populations at risk. Long-term observations facilitate analysis of climate–malaria relationships, and high-resolution data can be used to assess the effects of agriculture, urbanization, deforestation, and water management on malaria. New sources of very-high-resolution satellite imagery and synthetic aperture radar data will increase the precision and frequency of observations. Cloud computing platforms for remote sensing data combined with analysis-ready datasets and high-level data products have made satellite remote sensing more accessible to nonspecialists. Further collaboration between the malaria and remote sensing communities is needed to develop and implement useful geospatial data products that will support global efforts toward malaria control, elimination, and eradication.

On-field test and data calibration of a low-cost sensor for fine particles exposure assessment

BACKGROUND

Accurate individual exposure assessment is crucial for evaluating the health effects of particulate matter (PM). Various portable monitors built upon low-cost optical sensors have emerged. However, the main challenge for their application is to guarantee accuracy of measurements.

OBJECTIVE

To assess the performance of a newly developed PM sensor, and to develop methods for post-hoc data calibration to optimize its data quality.

METHOD

We conducted a series of laboratory experiments and field evaluations to quantify the reproducibility within Plantower PM sensors 7003 (PMS 7003) and the consistency between sensors and two established PM_2.5 measurement methods [tapered element oscillating microbalances (TEOM) and gravimetric method (GM)]. Post-hoc data calibration methods for sensors were based on a multiple linear regression model (MLRM) and a random forest model (RFM). Ratios of raw and calibrated readings over the data of reference methods were calculated to examine the improvement after calibration.

RESULTS

Strong correlations (≥0.82) and relatively small relative standard deviations (16-21%) between sensors were found during the laboratory and the field sampling. Compared with the reference methods, moderate to strong coefficients of determination (0.56-0.83) were observed; however, significant deviations were presented. After calibration, the ratios of PMS measurements over that of two reference methods both became convergent.

CONCLUSIONS

Our study validated low-cost optical PM sensors under a wide range of PM_2.5 concentrations (8-167 μg/m³). Our findings indicated potential applicability of PM sensors in PM_2.5 exposure assessment, and confirmed a need of calibration. Linear calibration methods may be sufficient for ambient monitoring using TEOM as a reference, while nonlinear calibration methods may be more appropriate for indoor monitoring using GM as a reference.

Development of a personal passive air sampler for estimating exposure to effective chlorine while using chlorine-based disinfectants

With an increasing use of indoor disinfectants such as chlorine (Cl₂ ) and hypochlorous acid, a convenient sampler for estimating exposure to oxidants, such as effective chlorine, is necessary. Here, we developed a personal passive air sampler (PPAS) composed of a redox dye, o-dianisidine, in a polydimethylsiloxane (PDMS) sheet. o-Dianisidine readily reacts with gaseous oxidants generated by bleach usage, and its color changes as the reaction progresses; hence, personal exposure to effective chlorine could be easily detected by the naked eye, while cumulative exposure could be determined by measuring concentrations of o-dianisidine reacting with it. The PPAS was calibrated, and a sampling rate of 0.00253 m³ /h was obtained using a small test chamber. The PPAS was tested with the help of ten volunteers whose personal exposure to Cl₂ -equivalent gas was estimated after bathrooms were cleaned using spray and liquid-type household disinfection products, and the accumulated exposure-gas concentrations ranged from 69 to 408 ppbv and 148 to 435 ppbv, respectively. These PPAS-derived exposure concentrations were approximately two orders lower than those estimated using ConsExpo, suggesting a significant overestimation by prevailing screening models, possibly due to the ignorance of transformation reactions.

Monitoring changes in human activity during the COVID-19 shutdown in Las Vegas using infrasound microbarometers

While studies of urban acoustics are typically restricted to the audio range, anthropogenic activity also generates infrasound (<20 Hz, roughly at the lower end of the range of human hearing). Shutdowns related to the COVID-19 pandemic unintentionally created ideal conditions for the study of urban infrasound and low frequency audio (20-500 Hz), as closures reduced human-generated ambient noise, while natural signals remained relatively unaffected. An array of infrasound sensors deployed in Las Vegas, NV, provides data for a case study in monitoring human activity during the pandemic through urban acoustics. The array records a sharp decline in acoustic power following the temporary shutdown of businesses deemed nonessential by the state of Nevada. This decline varies spatially across the array, with stations close to McCarran International Airport generally recording the greatest declines in acoustic power. Further, declines in acoustic power fluctuate with the time of day. As only signals associated with anthropogenic activity are expected to decline, this gives a rough indication of periodicities in urban acoustics throughout Las Vegas. The results of this study reflect the city's response to the pandemic and suggest spatiotemporal trends in acoustics outside of shutdowns.

High-sensitivity biomedical sensor based on photoacoustic and cavity enhanced absorption spectroscopy with a new software platform for breath analysis

An easy-to-use highly sensitive sensor is reported for trace gas analysis. A near-infrared fiber-coupled external cavity diode laser in combination with a photoacoustic spectroscopy cell and a cavity enhanced absorption spectroscopy cell is used for analysis of trace gases. A software platform for direct absorption and wavelength modulation spectroscopy is developed in order to identify and quantify the molecules and to achieve a higher signal-to-noise ratio. Considering all of these features, the main advantage of our system is to analyze two different samples simultaneously and quickly. Trace gas measurement is assessed, and a detection limit of 1.5 ppb at 6528.76cm^-1 for ammonia is demonstrated. Furthermore, the sensor with our software platform can be easily used outside of the laboratory, for example, in hospitals.

Aerosol emission of adolescents voices during speaking, singing and shouting

Since the outbreak of the COVID-19 pandemic, singing activities for children and young people have been strictly regulated with far-reaching consequences for music education in schools and ensemble and choir singing in some places. This is also due to the fact, that there has been no reliable data available on aerosol emissions from adolescents speaking, singing, and shouting. By utilizing a laser particle counter in cleanroom conditions we show, that adolescents emit fewer aerosol particles during singing than what has been known so far for adults. In our data, the emission rates ranged from 16 P/s to 267 P/s for speaking, 141 P/s to 1240 P/s for singing, and 683 P/s to 4332 P/s for shouting. The data advocate an adaptation of existing risk management strategies and rules of conduct for groups of singing adolescents, like gatherings in an educational context, e.g. singing lessons or choir rehearsals.

Comparative field study on bioassay responses and micropollutant uptake of POCIS, Speedisk and SorbiCell polar passive samplers

Routine water quality monitoring is generally performed with chemical analyses of grab samples, which has major limitations. First, snapshot samples will not give a good representation of the water quality. Second, it is not sufficient to analyze only a limited number of (priority) pollutants. These limitations can be circumvented by an alternative environmental risk assessment that combines time-integrated passive sampling (PS) with effect-based methods. This study aimed to select which of three polar PS devices was best suited for effect-based monitoring strategies. In the first part of this study, Speedisk, SorbiCell and POCIS polar PS devices were compared by simultaneous deployment at five sites. Chemical analyses of 108 moderately polar compounds (-1.82 < log D < 6.28) revealed that highest number of compounds, with the widest range of log K_OW, log D and pKa, were detected in extracts of POCIS, followed by Speedisk. SorbiCell samplers accumulated the lowest numbers and concentrations of compounds, so they were not further investigated. In a follow-up study, bioassay responses were compared in extracts of POCIS and Speedisk devices deployed at eight sites. The passive sampler extracts were subjected to bioassays for non-specific toxicity, endocrine disruption, and antibiotics activities. More frequent and higher responses were induced by POCIS extracts, leading to more exceedances of effect-based trigger values for environmental risks. As POCIS outperformed Speedisk, it is better suited as PS device targeting polar compounds for semi-quantitative effect-based water quality monitoring.

Comparison of samplers collecting airborne influenza viruses: 1. Primarily impingers and cyclones

Researchers must be able to measure concentrations, sizes, and infectivity of virus-containing particles in animal agriculture facilities to know how far infectious virus-containing particles may travel through air, where they may deposit in the human or animal respiratory tract, and the most effective ways to limit exposures to them. The objective of this study was to evaluate a variety of impinger and cyclone aerosol or bioaerosol samplers to determine approaches most suitable for detecting and measuring concentrations of virus-containing particles in air. Six impinger/cyclone air samplers, a filter-based sampler, and a cascade impactor were used in separate tests to collect artificially generated aerosols of MS2 bacteriophage and swine and avian influenza viruses. Quantification of infectious MS2 coliphage was carried out using a double agar layer procedure. The influenza viruses were titrated in cell cultures to determine quantities of infectious virus. Viral RNA was extracted and used for quantitative real time RT-PCR, to provide total virus concentrations for all three viruses. The amounts of virus recovered and the measured airborne virus concentrations were calculated and compared among the samplers. Not surprisingly, high flow rate samplers generally collected greater quantities of virus than low flow samplers. However, low flow rate samplers generally measured higher, and likely more accurate, airborne concentrations of Infectious virus and viral RNA than high flow samplers. To assess airborne viruses in the field, a two-sampler approach may work well. A suitable high flow sampler may provide low limits of detection to determine if any virus is present in the air. If virus is detected, a suitable lower flow sampler may measure airborne virus concentrations accurately.

Soil dissipation of sugarcane billet seed treatment fungicides and insecticide using QuEChERS and HPLC

Chemical treatment of sugarcane seed with fungicides and insecticides prior to planting increases yields of cane and sugar for the perennial, annually harvested crop. However, the fate of the applied chemicals is unknown. Therefore, the purpose of this study was to measure the aerobic dissipation of selected billet seed treatment chemicals in a mineral sugarcane soil from Louisiana. Soil samples from the surface 15 cm were treated with either thiamethoxam, azoxystrobin, fluxapyroxad, propiconazole, or pyraclostrobin and monitored over 100 days under laboratory conditions. Insecticide and fungicide levels were determined by high performance liquid chromatography. Dissipation data were fitted to four kinetic models: simple first-order (SFO), first order multi-compartment (FOMC), double-first order in parallel (DFOP), and hockey-stick (HS). The dissipation half-life (DT₅₀) of thiamethoxam, azoxystrobin, fluxapyroxad, propiconazole, or pyraclostrobin were 275, 100, 144, 74, and 39 d, respectively. Overall, the DT₅₀ for the pesticides in the study indicated medium to long persistence in soil under the conditions of the experiment. This is the first report for several of these pesticides related to the aerobic dissipation in soils used to grow sugarcane.

Enriched Aerosol-to-Hydrosol Transfer for Rapid and Continuous Monitoring of Bioaerosols

Bioaerosols, including infectious diseases such as COVID-19, are a continuous threat to global public safety. Despite their importance, the development of a practical, real-time means of monitoring bioaerosols has remained elusive. Here, we present a novel, simple, and highly efficient means of obtaining enriched bioaerosol samples. Aerosols are collected into a thin and stable liquid film by the unique interaction of a superhydrophilic surface and a continuous two-phase centrifugal flow. We demonstrate that this method can provide a concentration enhancement ratio of ∼2.4 × 10⁶ with a collection efficiency of ∼99.9% and an aerosol-into-liquid transfer rate of ∼95.9% at 500 nm particle size (smaller than a single bacterium). This transfer is effective in both laboratory and external ambient environments. The system has a low limit of detection of <50 CFU/m³_air using a straightforward bioluminescence-based technique and shows significant potential for air monitoring in occupational and public-health applications.

Passive sampling of toluene (and benzene) in indoor air using a semipermeable membrane device

The distribution and concentration of organic compounds in the environment have attracted great interest mainly due to their capability of bioaccumulation, dispersion, and danger to living organisms. Factors such as urbanization, population growth, and the emergence of new technologies contribute to the increase in pollutant emissions, especially volatile organic compounds (VOCs), such as benzene, toluene, ethylbenzene, and xylenes (BTEX). These compounds are emitted by several sources, becoming more common in work environments, influencing indoor air quality (IAQ), which can cause health damage, in addition to increasing the likelihood of cancer development. In this context, we developed a semipermeable membrane device (SPMD), consisting of low density polyethylene membrane (8 cm long × 3 cm wide), filled with 3 mL of acetonitrile, for passive sampling of toluene (and benzene) in gas phase. With this configuration, the SPMD needed 24 h exposure to the indoor air in order to achieve equilibrium. The target compounds were quantified in the acceptor phase by HPLC-DAD. The optimized SPMD was tested for the collection of toluene and benzene in six chemistry laboratories at Fluminense Federal University and in five nail salons in the city of Niterói, in the state of Rio de Janeiro, Brazil. The developed sampling method was able to identify the analytes in the indoor air of the studied environments, and was easy to operate, with no need to clean up the extracts, allowing their direct injection into the chromatographic system.

Classifying the Biological Status of Honeybee Workers Using Gas Sensors

Honeybee workers have a specific smell depending on the age of workers and the biological status of the colony. Laboratory tests were carried out at the Department of Apiculture at UWM Olsztyn, using gas sensors installed in two twin prototype multi-sensor detectors. The study aimed to compare the responses of sensors to the odor of old worker bees (3–6 weeks old), young ones (0–1 days old), and those from long-term queenless colonies. From the experimental colonies, 10 samples of 100 workers were taken for each group and placed successively in the research chambers for the duration of the study. Old workers came from outer nest combs, young workers from hatching out brood in an incubator, and laying worker bees from long-term queenless colonies from brood combs (with laying worker bee’s eggs, humped brood, and drones). Each probe was measured for 10 min, and then immediately for another 10 min ambient air was given to regenerate sensors. The results were analyzed using 10 different classifiers. Research has shown that the devices can distinguish between the biological status of bees. The effectiveness of distinguishing between classes, determined by the parameters of accuracy balanced and true positive rate, of 0.763 and 0.742 in the case of the best euclidean.1nn classifier, may be satisfactory in the context of practical beekeeping. Depending on the environment accompanying the tested objects (a type of insert in the test chamber), the introduction of other classifiers as well as baseline correction methods may be considered, while the selection of the appropriate classifier for the task may be of great importance for the effectiveness of the classification.