Drone-based particle monitoring above two harmful algal blooms (HABs) in the USA †

a Little is known about the transport and fate of aerosolized particles associated with harmful algal blooms (HABs). An Airborne DROne Particle-monitoring System (AirDROPS) was developed and used to monitor, collect, and characterize airborne particles over two HABs in Grand Lake St Marys (GLSM) and Lake Erie (LE), Ohio USA in August 2019. The AirDROPS consisted of an impinging device (ID) and an optical particle counter (OPC) mounted on a large commercial quadcopter (DJI Inspire 2). The sensor package was mounted above the airframe to limit the e ﬀ ects of propeller downwash that can corrupt measurements taken below the drone. Nineteen ﬂ ights were conducted 10 m above water level (AWL) at GLSM, and ﬁ ve ﬂ ights were conducted 10 m AWL at LE. The sampling height was chosen to minimize the e ﬀ ects of propwash on aerosolization from the lake surface. One intercomparison ﬂ ight was conducted at GLSM over land adjacent to a sonic anemometer mounted on the top of a ﬂ agpole 15 m above ground level (AGL). Particle counts generally decreased from morning to afternoon ﬂ ights, ranging from >4000 in the morning to <1000 later in the day. Decreased particle counts were associated with an increase in windspeed that corresponded with time of day, ranging from >4000 below 4 m s − 1 to <2500 above 4 m s − 1 . Flow cytometry was used to image particles trapped in a liquid impinger onboard the AirDROPS. Sixty percent (15/25) of the impinger samples contained at least one biotic ( ﬂ uorescent) object. Impinger samples were also analyzed for a suite of potential cyanotoxins using liquid chromatography-mass spectrometry (LC-MS/MS), but no cyanotoxins were detected in any of these air samples (water samples collected during a similar time contained greater than 20 m g L − 1 microcystins). Additional work is needed to understand the environmental factors associated with the potential aerosolization and transport of cyanobacterial cells and toxins in aquatic environments.


Introduction
2][3] HABs form as a result of lake conditions favorable to cyanobacterial growth, such as high levels of phosphorus and warmer temperatures. 4These conditions can occur in areas with high agricultural runoff and are a particular risk to shallow waters.6][7] The exposure of HAB associated aerosols has been shown to pose health threats using Drosophila melanogaster as an animal model. 8Furthermore, HABs appear to be increasing in freshwater bodies around the world. 4,9esearch is needed to mitigate HABs, including the development of new low-cost and turn-key technologies to capture, detect, and quantify HAB cells and toxins in water and air. 3,4ater samples suspected to contain HABs are usually collected by hand from crewed boats and shipped to off-site laboratories for cyanotoxin analyses.Detailed cyanotoxin analyses are usually conducted using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), but the high costs of these instruments preclude their widespread use.Commercially available enzyme linked immunosorbent assays (ELISAs) are common for some cyanotoxins such as microcystins (MCs), employing either monoclonal or polyclonal antibodies. 6New low-cost technologies with quick turn-around times are needed to understand threats, manage risks, and mitigate incidents associated with HABs.
Grand Lake Saint Marys (GLSM) is a natural HAB laboratory; the lake has experienced a recurring HAB since 2010. 10LE has also experienced several signicant HABs in recent years.A HAB in 2014 near the water treatment plant intake for Toledo, OH led to non-potable water for days. 11HABs on LE are oen associated with the southern and western portions of the lake, likely stemming from increased nutrient input from the Maumee River. 12Similar to GLSM, LE has been experiencing HABs for at least the past few decades, due in large part to the highly agricultural watershed and resulting nutrient rich runoff coupled with the shallow depth and bathymetry of the lake. 13akes with HABs have been shown to produce lake spray aerosols (LSAs) through the breaking of waves and the bursting of bubbles. 14,15These processes may release HAB-associated particles into the air above the lake surface. 16Red tides in the ocean are known to produce aerosolized toxins known as brevetoxins that may irritate the eyes and lungs of humans. 17hough red tides have been the focus of a considerable amount of research in the past decade, 18 relatively little is known about the airborne transport and fate of freshwater HABs and their associated toxins.This information is critical for health advisories issued via water quality experts, and for the communities of people that live on or around contaminated bodies of water. 19 number of different techniques and approaches have been used to study the aerosolization and transport of microorganisms from aquatic environments.May   20 used a chamber to study the potential impact of salinity on the aerosolization of microorganisms from aquatic environments.Powers et al. 21developed an extensive sampling tower for an uncrewed surface vehicle (USV) to collect microorganisms and monitor particle sizes in the atmosphere above a salt pond in Falmouth, MA, USA and a freshwater lake in Dublin, VA, USA.The bioaerosol-sampling system featured in that work included a series of 3D-printed impingers, two different optical particle counters, and a weather station.A small, uncrewed aircra system (sUAS; a xed-wing drone) was used in a coordinated effort with the USV to collect microorganisms 50 m above the surface of the water.Samples from the USV and sUAS were cultured on selective media to estimate concentrations of culturable microorganisms.In this manuscript, we extend these prior efforts to the development and use of a unique Airborne DROne Particle-monitoring System (AirDROPS) to collect and characterize aerosols directly over HABs in two freshwater lakes.The AirDROPS consisted of low-cost and lightweight sensors, including an impinging device (ID) and an optical particle counter (OPC) mounted above a large commercial quadcopter (DJI Inspire 2).The OPC used on the AirDROPS can characterize particles up to 10 mm, which is above the size range of cells of Microcystis which have been reported to be 1-7 mm. 14Laboratory calibration experiments were conducted to assess the reliability of the OPCs aer a period of use. 22,23We hypothesized that particle size distributions above two freshwater HABs would be associated with windspeed, wind direction, and temperature.The specic objectives of our work were to: (1) design an automated drone-based sampler to monitor particle sizes in the atmosphere and collect HAB cells and toxins, (2) use the dronebased sampler to monitor the distribution of particles in the atmosphere directly above two freshwater HABs, and (3) observe potential associations of wind direction, windspeed, and temperature with particle counts from the drone-based sampler.

Study sites
GLSM is an articial lake in western Ohio with a surface area of 54.6 square kilometers and average depth of about 2 m. 10 In the GLSM watershed, over 90% of the land use is row crops or pastureland which leads to a high amount of nutrient pollution into the lake. 24The shallow lake warms to between 20 and 30 C in the summer months. 11The warmer waters and higher nutrient load in the lake allow the cyanobacteria to outcompete other algae in the lake, creating a bloom of toxin producing cyanobacteria.Samples were collected over ve consecutive days between 5-9 August 2019 at GLSM and LE in Ohio, USA (LE).Drone sampling missions were conducted 10 m above the water surface at coordinates 40.544074, -84.508220 (Table 1) in order to obtain unique measurements of collected aerosols and particle counts at heights above the water surface that could not be reached by boat.Wind speed and direction were collected by an anemometer attached to a agpole at coordinates 40.544035, −84.508114.Due to the lack of an unobstructed space to place the stationary wind sensor at LE (there were tall trees at the sampling location that obstructed the sampling domain), wind data were collected through a separate drone own simultaneously 10 m above the water.Wind data from these ights were gathered using previously published methods where the motion of the drone was used to infer windspeed and wind direction. 25,26One of the ights at GLSM was also used for comparison with a concurrent separate drone ight measuring wind conditions and was own adjacent to a sonic anemometer mounted on the top of a 15 m agpole (Flight 20, Table 1).

Airborne drone particle-monitoring system
The AirDROPS was designed and deployed for sampling bioaerosols and monitoring particle size distributions.The sampler was constructed using a 38.5 mm diameter by 290 mm length PolyPropylene tube and Polylactic Acid 3D printer components (Fig. 1A).The sampler was mounted on top of the drone airframe (Fig. 1B) to limit the effects of propeller downwash that can corrupt measurements taken below the drone. 27,28he sampler was powered via a single 3.7 V 3000 mA h 15 A lithium-ion battery (Samsung 30Q INR 18650) that was changed out with every ight.An impinger was designed using a stainless-steel tube and PolyCarbonate 3D printed components to allow for high temperature sterilization by autoclave and eld  This ow rate was determined using an FTS Flow Calibrator from ARA Instruments (Eugene, OR, USA), and was optimized to ensure that the impinging uid was not evacuated from the tube during the sampling mission (i.e., higher ow rates caused water to escape the tube into the vacuum pump).The collection efficiency of the impinger has been reported previously by Powers et al. 21to be 75% for 1 mm polysterene latex beads and 99% for 3 mm polysterene latex beads.The inlet to the impinger was located 330 mm above the horizontal plane of the drone propellers to limit fouling of the sensor due to propwash (Fig. 1B).An optical particle counter (PMS7003, Plantower, Shunyi District, Beijing, China) was used to record six particle size bins, each greater than 0.3, 0.5, 1.0, 2.5, 5.0, and 10.0 mm.PM 1 , PM 2.5 , and PM 10 numbers were calculated internally by the PMS7003.The inlet to PMS7003 sensor was located 312 mm above the horizontal plane of the drone propellers (Fig. 1B).An environmental sensor (BME280, Bosch Sensortec GmbH, Gerhard-Kindler-Strasse 9, 72 770 Reutlingen Germany) was used to measure ambient temperature, relative humidity, and barometric pressure.The BME280 was located 132 mm above the horizontal plane of the drone propellers.A GPS module (GPS-13740, SparkFun Electronics, 6333 Dry Creek Parkway, Niwot, CO 80503) was used for location and time data.All available data was recorded by the ARM-based microcontroller to a secure digital (SD) card at 1 Hz.The combined weight of the AirDROP including a battery and a 15 mL conical tube with 2.5 mL of sterile water was 587 g.This is below the safe limit operations of the Inspire 2 platform payload, which the manufacturer has specied as no greater than 810 g. 29 With the AirDROPS installed, the Inspire 2 platform had a reasonable (safe) ight time of about 15 minutes.Our sampling missions were designed with this limit in mind (10 minutes), providing enough time for takeoff, transit to and from the sampling location, and return to home for landing (about two minutes, given the location of our takeoff and landing spot).

Flight operations
For each sampling mission, the AirDROPS was own into position, and held in 'Positioning mode' at a constant altitude of 10 m above the lake surface (Fig. 1D).This height was chosen to reduce the impact of downwash on the lake surface as well as to measure aerosol levels higher above the HAB source than had been done previously using watercra.The sensor package was powered on using a photoelectric switch mounted over the le rear green LED light on the Inspire 2. The lights were powered on in the DJIGO4 app, starting the sensor package over water once the drone was in the correct position.The sensor package remained on for a period of 10 min.Aer 10 min, the sensor package was powered off using the photoelectric sensor, and the drone was returned home for landing.

Flow cytometry of impinger samples collected 10 m above the HABs
The concentration of impinged particles from the atmosphere above freshwater lake sites was determined with an Imaging Cytometer (Amnis ImageStream MarkII).The impinged aerosols were counted as obj per mL at 60Â magnication in both the brighteld (BF) (457/45 nm bandpass lter) and red channels (642 nm excitation and 702/86 nm emission wavelength) (Fig. 2).Phycocyanins are the light harvesting pigments found in cyanobacteria and these pigments are optimally excited in the red range with an emission spectrum that can be captured between 630 nm and 800 nm.Samples were stored at −20 C, thawed, and equilibrated at room temperature, prior to being run.One mL of the impinged liquid sample was spun twice at 3000Â gravity for ve minutes.Two aliquots of 42 mL were immediately recovered from the liquid near the bottom of the tube, with care to avoid any debris on the tube bottom.Molecular biology grade water was ltered with a 0.2 mm lter and used as a blank in the machine before running samples.Due to the predicted low number of putative captured biotic aerosols, a 3 min run time was standardized for each impinged sample.In a previous study with natural and simulated rain, samples were run for three min to obtain obj per mL outputs. 21hese authors determined that 3 min sample runs showed similar size distributions relative to samples that reached 1000 obj per mL in less than three min, and the background level of bacteria in the nucleic acid staining dye in sterile control water was 297 AE 82 DNA-containing particles per 10 mL (n ¼ 3).We did not use a nucleic acid staining dye in this study.Instead, the total obj per mL data for biotic particles was captured in the red channel to eliminate abiotic debris that might give rise to a false count in the BF channel alone.The objects counted in the red channel were considered to be biotic in origin, regardless of uorescence level.Sample run focusing was achieved with SpeedBead® reagent beads (Amnis Cat.#400040) during data acquisition.The beads were removed by gating before object counts were generated for each run.To obtain total aerosolized particles captured, the BF channel data was corrected by subtraction of particles within the SpeedBead capture range.These counts were sorted by the size of the objects into bins of 0.13-1.13,1.13-1.60,1.60-1.95,1.95-2.76,2.76-3.91,3.91-5.64,5.64-6.91,6.91-7.98,and 7.98-8.92mm radius objects.The radius was calculated using the total size of the objects and assuming a circular (spherical) shape.
To calculate the total number of aerosolized particles collected during each impinger collection, the average of the total BF obj per mL for the zero red channel runs were assigned to a discrete size bin.The mean of this total obj per mL (for each size bin) was subtracted from the corresponding total BF obj per mL (for each size bin) for each run that contained a positive uorescent object in the red channel.By subtracting the average particle count data for samples with zero objects in the red channel, from those with red objects, we were able to normalize by correcting for abiotic debris particle capture.

Cyanotoxin analyses using LC-MS/MS
Toxins from cyanobacteria were detected using LC-MS/MS methods described in Birbeck et al. 2019. 30Sample analytes were loaded into a Thermo Scientic TSQ Altis™ triple quadrupole mass spectrometer (Thermo Scientic, Waltham, MA, USA) with an EQuan MAX Plus™ system and then separated on a Thermo Accucore aQ, 50 Â 2.1 mm, 2.6 mm particle size column.A standard curve was prepared between 0.5-500 ng L −1 , with detection limits for MCs and nodularin being between 0.5-10 ng L −1 .An electrospray ionization source was used in positive ion mode.Additional details regarding these methods are provided in Hanlon et al. (2022) 31 and reference ions are provided in Table 1.† The TraceFinder™ EFS 4.1 soware package was used to ensure proper cyanotoxin identication (Table 1 †).

Particle counts 10 m above the HABs
The PMS7003 was used to count particles six particle size bins, each greater than 0.3, 0.5, 1.0, 2.5, 5.0, and 10.0 mm diameter in 0.1 L of air, and had a sample rate of about 1 Hz.The sampling occurred over 10 min intervals in tandem with the drone-based impinger.Airborne particle counts were measured according to the times shown in Table 1.The data collected was saved to an SD card in comma-separated values (CSV) le format and transferred before clearing the SD card to prepare for the next ight.

Ground-based measurements of windspeed and wind direction
At GLSM, an Atmos 22 sonic anemometer weather station was aligned north with a compass and raised on a agpole to a height of 15 m where it recorded wind speed and direction measurements every 15 s.Data were saved to an SD card and collection was run from 8:00 until 16:00 local time, daily.The same ground-based anemometer was also used at LE, but trees obstructed this sensor during ight operations so local wind data for the LE ights were determined from drone-based measurements of wind. 32These measurements were taken every second and matched with the time recorded on the AirDROPS to align particle count measurements with the wind speed and direction calculations.

Drone-based wind velocity measurements
Drone-based wind velocity measurements were derived from a 3DR Solo quadrotor using the model-based wind estimation technique described in (González-Rocha et al., 2019; 2020). 25,26ith this method, wind velocity is inferred from wind-induced vehicle motion perturbations experienced as the drone sustains hovering ight.[27]

Optical particle counter calibration experiments
The initial OPC calibrations were done according to the procedure outlined in Powers et al., 2018. 21The accuracy of the OPC used onboard the AirDROPS was assessed in a series of controlled laboratory experiments against an Aerodynamic Particle Sizer (APS, Model 3321, TSI Incorporated, Shoreview Minnesota, USA).Briey, particles of known sizes (1 and 3 microns) were released into a sealed bag and measurements from the OPC were compared to the APS.

Data analyses
Data were saved in CSV les and were trimmed and aligned in Microso Excel.Statistical analyses were performed with JMP Pro Version 17 soware (Cary, North Carolina, USA).A model was t using the JMP neural network to create a prediction equation for GLSM which utilized wind speed, wind direction, and temperature to predict the particle count.The neural network weighs inputs from a provided dataset to create a prediction equation that will estimate a specic output parameter.The model was set up to create three hidden node equations that combine into an overall theta equation.The theta equation predicts the particle count from the provided weather data.The program adjusts the values in the hidden node equations and overall theta equation until it ts the best curve to the data. 33,34To get the best t, the model was trained using all of the data collected from the sampling periods of August 5 th and August 6 th , 2019 for which we had both weather data and particle counts.The model was trained with a randomly selected 2/3 rds of the collected data, and utilized the remaining 1/3 rd as verication for the prediction equation.This resulted in 368 measurements to train the model, and another 184 to verify the model.

Flights
Twenty ights were conducted at GLSM, and ve ights were conducted at LE (Table 1).Twenty-four of the ights were conducted 10 m above the surface of the water (Table 1).One of the ights at GLSM was used to calibrate the drone sensor package (Flight 20, Table 1), and was own adjacent to a sonic anemometer mounted on the top of a agpole (Fig. 1C).

Wind direction and wind speed
The wind direction was consistent across the lakes and toward the shore-based operations for all the sampling missions performed at the two lakes (Fig. 1 and 4).For GLSM, the sonic anemometer (mounted on the agpole) recorded wind speeds from 0-10 m s −1 (Fig. 4), and wind directions ranging from a source of 150-300 (Fig. 3.At GLSM, windspeed increased from morning to aernoon ights (Fig. 4)).At LE, windspeed was variable and ranged from 1 to 12 m s −1 across all sampling missions (Fig. 4).
At LE, airborne particle counts were generally lower than GLSM and consistent from morning to aernoon ights (Fig. 5).At the time LE was not experiencing an algal bloom at the severity of the one in GLSM, which could have contributed to the lower particle counts.There was no association with particle counts with windspeed (Fig. 6).For the size bin of 0.3-0.5 mm diameter, particle counts ranged from about 400 to 700 per measurement (Fig. 5).For the size bin of 0.5-1.0mm diameter, particle counts ranged from about 100 to 300 per measurement (Fig. 5).For the size bin of 1.0-2.5 mm diameter, particle counts ranged from about 20 to 35 per measurement (Fig. 5).For larger size bins (2.5-5.0,5.0-10.0,and 10.0+ mm), particle counts ranged from 0 to 2 per measurement (Fig. 5).
At GLSM when looking at particle counts over time, we saw the particle count decrease signicantly as the day went on, dropping to as little as 1/6 th the morning particle count levels (Fig. 5).During our sampling throughout the day.The windspeed increased by 2 to 3 times the morning speed (Fig. 4), but the wind direction only slightly shied and was always coming from off the lake.At LE, we saw lower average particle counts than at GLSM but had similar wind source distribution with over 90 percent of wind source direction coming from between 270 and 360 which was off the lake.

Flow cytometry and cyanotoxin analyses of impinger samples
Selected panels of uorescent objects present in the impinger samples are shown in Fig. 2. Sixty percent (15/25) of the impinger samples contained at least one biotic (uorescent) object, ranging from 1 to 7 obj per mL (Fig. 2).Total biological objects counted in the R1 channel were sorted by size with the majority falling between 1.95 and 3.91 mm (Fig. 7).When comparing total particle counts and object concentrations, no association was observed (Table 1).However, despite lower particle counts at LE there were larger numbers of objects observed in the impinger (Table 1).Impinger samples were also analyzed for a suite of cyanotoxins using LC-MS/MS, but no cyanotoxins were detected in any of the samples.Water samples collected during a similar time contained greater than 20 mg L −1 microcystins. 31

Predicting particle counts as a function of environmental parameters
Particle counts >0.3 mm from August 5 were observed as a function of wind speed, wind direction, and temperature (Fig. 8).Fig. 8 shows the actual measured particle counts plotted against the model predicted versions which results in an optimized model with a R Square of 0.87 and a validation prediction with a R Square of 0.86.The hidden node equations and overall prediction equation, are as follows: This model based on a neural network allowed for a prediction of the particle counts in the air above the HAB based on weather conditions.Little is known about the airborne fate and transport of HABs and their associated toxins.To address these knowledge gaps, we developed and deployed an airborne drone particle-monitoring system (AirDROPS) to collect and characterize aerosols directly over HABs in two freshwater lakes (GLSM and LE), each with different size and conditions that impact aerosolization processes.The AirDROPS consisted of an impinging device and an optical particle counter mounted above a large commercial quadcopter.Nineteen ights were conducted 10 m above water level (AWL) at GLSM, and ve ights were conducted 10 m AWL at LE.One intercomparison ight was conducted at GLSM over land adjacent to a sonic anemometer mounted on the top of a agpole 15 m above ground level (AGL).Though airborne concentrations of particles have been reported over water using uncrewed boats, 21 to our knowledge, the work described here represents the rst drone-based measurements of airborne particle counts directly over HABs.
Airborne particle size distributions varied with increasing windspeed for GLSM.Particle counts generally decreased from   morning to aernoon ights, and the decreased particle counts were associated with an increase in windspeed.In contrast, LE particle counts were much lower, and we did not observe signicant trends in particle counts with respect to wind direction, wind speed, or time of day.Airborne particle concentrations have been shown to be associated with windspeed and wind direction above a lake surface. 21The time of day plays a role in the conditions affecting windspeed and direction through diurnal cycling. 357][38] In the case of GLSM, the relatively small size and depth may cause less wave formation and breaking than we would see in large lake spray or sea spray studies, instead likely having aerosol production limited to the surf zone and mechanical disturbances of the surface.LE, however, would be more likely to produce larger numbers of aerosols from wave breaking and bubble-bursting due to the larger size and depth. 14Previous studies have shown a difference in particle counts with respect to wind direction when it caused a switch from offshore to onshore winds as wind can drive droplet formation from the water surface. 8,39Our drone sampling missions were conducted exclusively during onshore winds, so consequently we were unable to examine potential associations of particle counts with offshore winds.Since all of our sampling missions were conducted during onshore winds, we speculate that a signicant fraction of the observed airborne particles were from the lakes studied.We acknowledge, however, that some of the particles may have originated from other non-lake sources.Future experiments with multiple background sampling locations would help to elucidate potential contributions to airborne particle concentrations.
Sixty percent (15/25) of the impinger samples contained at least one biotic (uorescent) object.We saw higher numbers on average from LE, which could be caused by lake chemistry or environmental conditions that favor aerosolization of biotic objects. 37,38Since the biotic objects were oen on the larger end of the range (3-10 mm), we speculate that they may have stronger associations with particle counts of those sizes.Unfortunately, due to the low number of particle counts in the larger size bins, we were unable to provide a constructive analysis of this potential association.Impinger samples were also analyzed for a suite of cyanotoxins using LC-MS/MS, but no cyanotoxins were detected in any of the samples.Hanlon et al. (2022) 31 conducted a series of water sampling missions at GLSM and LE during the same calendar dates and reported high levels of microcystin in the water, 15.0 and 1.92 mg L −1 , respectively.1][42] In addition, wave breaks and bubble-bursting cause water to spray and contributes to aerosol production and the dispersal of cells, especially in larger bodies of water such as LE, 8 and cyanotoxins into the air. 18Aerosols produced in this way have been found to contain MCs in samples collected over land near a HAB, showing that the toxin can be transported over land to the surrounding area. 14Sutherland et al. 43 detected anatoxin-a in air samples during a HAB at Capaum Pond on Nantucket Island, Massachusetts, USA in 2019.Though air samples have not yet been incorporated into routine HAB monitoring in freshwater environments, the spread of HABassociated aerosols in marine environments (e.g., brevetoxin) is known to cause respiratory problems and can be dangerous to those with underlying health conditions. 17The approach showcased here demonstrates the feasibility of a rapid dronebased system to extend monitoring protocols beyond the water's edge.And while we did not necessarily detect any appreciable toxin values in our samples, our data regarding the distribution of particles as well as impingement of numerous uorescent objects does validate the approach.
The concerns regarding the accuracy of lightweight and inexpensive OPCs is an important limitation to consider when comparing values of one OPC to another or to determine absolute high or low levels of particles. 22,23Our eld experiments relied on a single OPC as part of the AirDROPS package.However, as shown in the laboratory calibration experiments, the data recorded from this OPC were robust and consistent with simultaneous measurements recorded from the APS.
Additional work is needed to understand the environmental factors associated with the potential aerosolization and transport of cyanobacterial cells and toxins in aquatic environments.Higher windspeeds may decrease total particle counts above a lake, but also drive aerosol production closer to the lake surface. 8,36,44Though our study was only focused on an altitude of 10 m above the water surface, it sets the stage for future work to examine the vertical distribution of HABs above a lake surface.Powers et al. 21conducted simultaneous sampling missions of microorganisms with a UAS and a USV at Claytor Lake, Virginia, USA.It should be noted that although Claytor Lake had relatively high levels of the bacterium Pseudomonas syringae, it was not experiencing a HAB.Additional research is needed to understand threats, manage risks, mitigate incidents, develop capabilities, and strengthen collaborations for improved water quality and security. 3Aerial and aquatic robots can be tted with the tools to be used to work alongside health professionals and air and water quality experts to provide critical and timely information to guide regulatory decisions.Modeling of particle counts as a function of the wind speed, wind direction, and temperature could allow for future predictions of areas impacted by HAB-associated aerosols. 39Such information is critical for determining time-sensitive health advisories, and to create public health forecasting models for the communities of people that live near contaminated bodies of water.
ethanol.The impinger was based on a design previously described by Powers et al., 2018 21 adapted for use with a 15 mL polypropylene sterile conical centrifuge tube (CLS430791, Corning, Millipore Sigma).An aliquot of 2.5 mL of sterile water was added to the 15 mL conical tube immediately prior to each sampling mission.Two micro vacuum pumps (PN: SC3101PM, 21 Hualun Sci & Tech Pk 1st Ind Zn Fenghuang Village, Fuyong Town, Shenzhen, Guangdong, China) were used in parallel to supply a ow rate of 0.6 L min −1 to the impinger.

Fig. 1 (
Fig. 1 (A) Engineering model of the AirDROPS package.(B) The AirDROPS attached to the DJI Inspire 2 platform.(C) Intercomparison flight of the AirDROPS adjacent to the sonic anemometer mounted on the flagpole.(D) Sampling mission at GLMS, 10 m above the surface of the water.(E) Drone image and aerial view of the sampling location at LE to the right of the point in the image.

Fig. 2
Fig. 2 Selected images from flow cytometry analyses of impinger samples from the AirDROPS.(A) Objects from an impinger sample collected above GLSM showing brightfield, red filter, and combination of the two.(B) Objects from an impinger sample collected above LE showing brightfield, red filter, and combination of the two.(C) Objects from a lake water sample from LE showing brightfield, red filter, and combination of the two.

Fig. 3
Fig. 3 Wind direction (degrees) over the course of the day.The first two graphs represent August 5 th to 6 th , 2019 at GLSM.The third graph represents August 8 th , 2019 at LE.The wind direction was determined using a sonic anemometer for August 5 th to 7 th , 2019, and using GLOS data for August 8 th , 2019.

Fig. 4
Fig. 4 Wind speed (m s −1 ) over the course of the day.The first two graphs represent August 5 th to 6 th , 2019 at GLSM.The third graph represents August 8 th , 2019 at LE.The wind speed was determined by our sonic anemometer for August 5 th to 7 th , 2019, and using GLOS data for August 8 th , 2019.

Fig. 5
Fig. 5 Airborne particle counts over the course of the day.Data were recorded from a PMS7003 OPC onboard the AirDROPS.The first two graphs show flights that occurred August 5 th to 6 th , 2019 at GLSM while hovering 10 m over the water.The third graph depicts the flights on August 8 th , 2019 while hovering 10 meters over the water at LE.To the right of each graph is the corresponding wind rose which shows wind direction and speed (m s −1 ) each day.

Fig. 6
Fig. 6 Airborne particle counts recorded from the OPC onboard the AirDROPS, and windspeed from the sonic anemometer mounted on a flagpole and drone-modeled data for LE.The first two graphs show flights that occurred August 5 th to 6 th , 2019 at GLSM while hovering 10 m over the water.The third graph depicts the flights on August 8 th , 2019 while hovering 10 m over the water at LE.

Fig. 7
Fig. 7 Biological object frequency by size from collected air impinged samples onboard the AirDROPS.The graph depicts object counts sorted by size with radius size bins from 1.60-1.95,1.95-2.76,2.76-3.91,3.91-5.64,5.64-6.91,6.91-7.98,and 7.98-8.92mm.The size bins were determined by assuming a spherical shape and calculating the radius of an object from its recorded size in the flow cytometer.

Fig. 8
Fig. 8 Measured vs. predicted particle counts used in the best fit model.The graph on the top panel shows the fit of the model on the training set of data, while the graph on the bottom shows the fit of the validation set of data.The model was made using the wind speed, temperature, and wind direction through the JMP Pro neural network modeling.The model was trained on two days of collected data, and verified on a random subset of the collected data that was not used to train the model.
et al. (2016) 15 developed a chamber to study LSA generation under controlled environmental conditions.Pietsch et al. (2018) 16 used a thin tank to study wind-induced aerosolization of the bacterium Pseudomonas syringae.Harb et al. (2019)

Table 1
Details on AirDROPS sampling missions at GLSM and LE.AirDROPS was used to collect and characterize particles over two HABs.The AirDROPS consisted of an impinging device and an optical particle counter mounted above a large commercial quadcopter.Nineteen flights were conducted 10 m above water level (AWL) at GLSM, and five flights were conducted 10 m AWL at LE.One sensor intercomparison mission (flight 20) was conducted over land adjacent to a sonic anemometer mounted on the top of a flagpole 15 m above ground level (AGL) 6-Aug-19 10:04 AM 10:14 AM 10 10 40.544873, −84.510843 18.9 n.d.