Dermal Exposure of Operators, Bystanders and Residents Derived from Unmanned Aerial Spraying Systems (UASS) in Vineyard

Academic Editor: Diego González-Aguilera Received: 18 March 2025 Revised: 22 April 2025 Accepted: 29 April 2025 Published: 1 May 2025 Citation: Sánchez-Fernández, L.; Díaz-García, F.; Pérez-Ruiz, M.; Sandin-España, P.; Alonso-Prados, J.L.; Mateo-Miranda, M.; MartínezGuanter, J.; García-Montero, E.; Márquez, M.d.C.; Abril-Muñoz, I. Dermal Exposure of Operators, Bystanders and Residents Derived from Unmanned Aerial Spraying Systems (UASS) in Vineyard. Drones 2025,9, 345. https://doi.org/ 10.3390/drones9050345 Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Article Dermal Exposure of Operators, Bystanders and Residents Derived from Unmanned Aerial Spraying Systems (UASS) in Vineyard Luis Sánchez-Fernández 1,*,† , Francisco Díaz-García 2,†, Manuel Pérez-Ruiz 1, Pilar Sandin-España 3, Jose Luis Alonso-Prados 3, Miguelina Mateo-Miranda 3, Jorge Martínez-Guanter 4, Esther García-Montero 4, Maria del Carmen Márquez 5and Isaac Abril-Muñoz 2 1Área de Ingeniería Agroforestal, Dpto. de Ingeniería Aeroespacial y Mecánica de Fluidos, Universidad de Sevilla, Ctra. Sevilla-Utrera km 1, 41013 Seville, Spain; [email protected] 2 Instituto Nacional de Seguridad y Salud en el Trabajo, Centro Nacional de Medios de Protección, C/Carabela la Niña, 16, 41007 Seville, Spain; [email protected] (F.D.-G.); [email protected] (I.A.-M.) 3Plant Protection Products Unit, Plant Protection Department, National Institute for Agricultural and Food Research and Technology INIA-CSIC, Ctra. La Coruña, km 7.5, 28040 Madrid, Spain; [email protected] (P.S.-E.); [email protected] (J.L.A.-P.); [email protected] (M.M.-M.) 4Corteva Agriscience Spain, S.L.U, Campus Tecnológico Corteva Agriscience, Carretera de Sevilla-Cazalla (C-433) km 4,6, La Rinconada, 41309 Seville, Spain; [email protected] (J.M.-G.); esther[email protected] (E.G.-M.) 5AEPLA, C/Fuencarral, 121, 28010 Madrid, Spain; [email protected] *Correspondence: [email protected] †These authors contributed equally to this work. Abstract: The increasing adoption of unmanned aerial spraying services presents a transformative opportunity for precision agriculture, enabling targeted and efficient application of plant protection products. However, ensuring their safe and regulated integration into European farming requires a comprehensive understanding of exposure risks for operators, bystanders, and residents. Expanding scientific knowledge in this domain is crucial for establishing a dedicated risk assessment framework for unmanned aerial spraying applications. This study evaluates dermal exposure levels among operators, residents, and bystanders, comparing unmanned aerial spraying applications with conventional vehicle-based and manual handheld spraying methods based on existing risk assessment and exposure models. Results suggest that unmanned aerial sprayers reduce dermal exposure for pilots, residents, and bystanders due to their remote operation and reduced drift compared to conventional spraying methods. However, critical exposure points arise during mixing, loading, and auxiliary tasks, where dermal exposure levels exceed model estimates. These elevated exposure levels are attributed to the higher frequency and concentrated handling of plant protection products in unmanned aerial spraying operations compared to traditional spraying methods. These findings highlight the need for targeted risk mitigation strategies to enhance operator safety, such as implementing closed transfer systems, optimized handling protocols, and specialized protective equipment. Keywords: UASS; UAV; dermal exposure; drift; pesticide safety; precision agriculture spraying 1. Introduction Integrating unmanned aerial spraying systems (UASS) into precision agriculture represents a transformative advancement in the targeted application of plant protection Drones 2025,9, 345 https://doi.org/10.3390/drones9050345 Drones 2025,9, 345 2 of 17 products (PPPs) spraying. Compared to conventional spraying methods, UASS offer enhanced efficiency, selectivity, and adaptability, particularly in complex terrains where conventional machinery may be impractical or unsafe to operate [ 1 – 5 ]. UASS enables sitespecific spraying, aligning with precision agriculture principles by optimizing input use and minimizing environmental impact and non-target exposure. Moreover, the potential for reduced spray drift makes UASS an attractive alternative to traditional ground-based and manned aerial applications in sensitive areas [ 6 ]. Additionally, the remote operation of UASS reduces operator exposure by limiting direct contact with PPPs during spraying activities. It enhances worker safety by avoiding navigating hazardous or uneven terrains. Furthermore, UASS can offer time and labor savings, especially during peak agricultural periods, thereby improving overall operational efficiency [7]. Regulatory constraints further complicate the adoption of UASS in Europe. Under Directive 2009/128/EC on the sustainable use of pesticides, UASS is currently classified alongside conventional manned aerial spraying, effectively prohibiting its use. However, the 2022 draft regulation on sustainable PPP use proposes Article 21, which could allow exemptions for UASS applications that meet specific criteria and demonstrate lower risks than other aerial or land-based methods. Importantly, the European Commission may adopt delegated acts to define these criteria as technological capabilities evolve. While this presents an opportunity, the absence of robust scientific data on UASS exposure risks remains a barrier to informed regulatory decisions. To support regulatory development and inform risk assessment, it is essential to quantify human exposure linked to UASS use. Human health risk assessment for PPP applications involves evaluating exposure to active substances or toxicologically relevant compounds, considering factors such as dosage, application method, and environmental conditions, as outlined in Regulation (EC) No 1107/2009. This assessment includes operators, workers, residents, and bystanders and typically relies on actual exposure measurements or validated computational models. Previous studies have investigated spray drift and deposition patterns associated with UASS spraying under various environmental and operational conditions [ 8 – 11 ]. However, the existing literature on comprehensive assessments of human exposure, particularly dermal exposure, during UASS operations remains limited. Most research to date has focused on spray drift dynamics or environmental impact modeling, without directly quantifying human exposure risks in real-world scenarios or comparing them to conventional application methods. Consequently, a significant knowledge gap remains concerning the potential of UASS to reduce human exposure to PPPs, especially in European contexts where regulatory scrutiny is particularly high. Few studies have specifically addressed operator safety given the higher concentration of active ingredients typically used in UASS spraying operations. For example, one study [ 12 ] measured PPP deposition on UASS components after spraying in an almond orchard, finding that the UASS arms accumulated the highest residues and recommending protective equipment when handling the drone. Another study [ 13 ] compared residue levels of active ingredients on UASS and conventional terrestrial airblast sprayers after treating an apple orchard. The results indicated significantly higher residues on the UASS, potentially due to the greater concentration of the sprayed solution. Recent research has begun to focus on quantifying exposure risks for residents and bystanders associated with UASS applications worldwide. A study in China evaluated bystander dermal exposure using adult-sized mannequins in a coconut plantation [ 14 ]. In the United Kingdom, researchers estimated exposure levels for both child and adult bystanders based on airborne spray drift data collected during UASS operations in open fields [ 15 ]. Similarly, a study conducted in a Swiss apple orchard measured direct dermal Drones 2025,9, 345 3 of 17 and inhalation exposure of bystanders and residents using adult and child-sized mannequins equipped with personal air sampling pumps [ 16 ]. This study concluded that dermal contact represented the primary exposure pathway for bystanders and residents. The present study compares three widely recognized models to empirical UASS exposure data. EFSA OPEX Guidance [ 17 ] provides an approach for estimating operator exposure to PPPs based on field scenarios and handling tasks using standardized exposure factors. US EPA Pesticide Handler Exposure Database (PHED) [ 18 ] offers empirical data on operator exposure across a range of pesticide handling and application activities, including scenarios relevant to conventional manned aerial applications. AgDrift ® model [ 19 ] simulates spray drift and potential exposure for bystanders and residents by modeling droplet behavior and environmental conditions during application. By comparing these models with UASS field exposure measurements, this study assesses potential and actual dermal exposure associated with UASS operations. Furthermore, it compares UASS exposure levels to those associated with conventional spraying methods, such as vehicle-mounted, manual-knapsack, and handheld spraying systems. This research aims to address the current knowledge gap concerning human exposure, particularly dermal exposure, during UASS operations and explore the potential benefits of integrating UASS technology into EU agricultural systems for PPP applications. Specifically, this study monitored the potential dermal exposure, defined as the exposure to the skin that would occur in the absence of clothing or personal protective equipment, and actual dermal exposure, which refers to the exposure to the skin that would occur in the presence of clothing and/or personal protective equipment. These dermal exposures were assessed for operators, residents, and bystanders during UASS applications of a Spinosad 480 g · L −1 formulation on grapevines. 2. Materials and Methods 2.1. Field Trials Field trials were conducted following the protocols established by OG PhytoDron in a fully developed commercial Palomino vineyard (Vitis vinifera) in Trebujena, Cádiz, Spain (36 ◦ 44 ′ N 6 ◦ 08 ′ W). The vineyard, covering 8.2 ha, was considered sufficient to simulate a full day of UASS application and assess operator dermal exposure. A 1.8 ha plot within the vineyard was selected to evaluate dermal exposure among bystanders and residents (Figure 1). This plot was treated at the start of the workday to capture potential exposure levels under standard operational conditions. The vineyard’s characteristics and management practices represented commercial vineyards in the region and the broader Mediterranean area. Drones 2025, 9, x FOR PEER REVIEW 4 of 18 Figure 1. The layout of the experimental vineyard (blue) and the plot selected to evaluate resident’s and bystander’s dermal exposure (orange). Yellow circles show the location of the bystander’s dosimeters. The red circle shows the location of the weather stations. The trials were conducted between July and August 2022, corresponding to phenological growth stages 79–83 on the BBCH scale. The grapevines were fully developed, measuring 1.2 m in height and 0.8 m in width, and planted in a 3 m × 1.7 m configuration, with a plant density of 1961 plants⋅ha−1. Notably, crop rows in the residents/bystanders trials area had an orientation of 120°. Spraying took place on four separate dates: July 14, July 21, July 28, and August 4. The first trial served as a preliminary study to identify critical points and potential sources of cross-contamination; therefore, its data were excluded from this analysis. 2.2. UASS The UASS employed in the trials was a Drone Hispania Y10 quadcopter (Drones Hispania, Seville, ES), equipped with a 10 L tank and fied with four orange XR11001VS nozzles (TeeJet Technologies, Wheaton, IL, USA), mounted just below each rotor (Figure 2). The system had a maximum takeoff weight (MTOW) of 25 kg, a flight autonomy of 14 min when fully loaded, and a wingspan of 2 m when fully deployed. The UASS also has a radar sensor to detect obstacles and keep a consistent distance from the ground. During the spraying trials, the UASS operated at a flying speed of 5 m·s−1 and a nozzle pressure of 2.5 bar. The flight path followed the crop rows, and the spraying height was maintained 1.5 m above the canopy, achieving a swath width of 3.4 m. The swath width was determined using a sampling line of 26 × 76 mm water-sensitive paper strips (Syngenta, Basel, Swierland) placed every 0.4 m. The flight height over the sampling line was held at 1.5 m during swath width trials. The final application rate was 10 L·ha−1, with the spray mixture containing 0.15 L of Spintor 480 SC (Spinosad 48% w/v; suspension concentrate, Corteva Agriscience Inc, Indianapolis, US). Figure 1. The layout of the experimental vineyard (blue) and the plot selected to evaluate resident’s and bystander’s dermal exposure (orange). Yellow circles show the location of the bystander’s dosimeters. The red circle shows the location of the weather stations. Drones 2025,9, 345 4 of 17 The trials were conducted between July and August 2022, corresponding to phenological growth stages 79–83 on the BBCH scale. The grapevines were fully developed, measuring 1.2 m in height and 0.8 m in width, and planted in a 3 m × 1.7 m configuration, with a plant density of 1961 plants · ha −1 . Notably, crop rows in the residents/bystanders trials area had an orientation of 120 ◦ . Spraying took place on four separate dates: 14 July, 21 July, 28 July, and 4 August. The first trial served as a preliminary study to identify critical points and potential sources of cross-contamination; therefore, its data were excluded from this analysis. 2.2. UASS The UASS employed in the trials was a Drone Hispania Y10 quadcopter (Drones Hispania, Seville, Spain), equipped with a 10 L tank and fitted with four orange XR11001VS nozzles (TeeJet Technologies, Wheaton, IL, USA), mounted just below each rotor (Figure 2). The system had a maximum takeoff weight (MTOW) of 25 kg, a flight autonomy of 14 min when fully loaded, and a wingspan of 2 m when fully deployed. The UASS also has a radar sensor to detect obstacles and keep a consistent distance from the ground. During the spraying trials, the UASS operated at a flying speed of 5 m · s −1 and a nozzle pressure of 2.5 bar. The flight path followed the crop rows, and the spraying height was maintained 1.5 m above the canopy, achieving a swath width of 3.4 m. The swath width was determined using a sampling line of 26 ×76 mm water-sensitive paper strips (Syngenta, Basel, Switzerland) placed every 0.4 m. The flight height over the sampling line was held at 1.5 m during swath width trials. The final application rate was 10 L · ha −1 , with the spray mixture containing 0.15 L of Spintor 480 SC (Spinosad 48% w/v; suspension concentrate, Corteva Agriscience Inc., Indianapolis, IN, USA). Drones 2025, 9, x FOR PEER REVIEW 5 of 18 Figure 2. UASS used during the spraying trials. 2.3. Weather Conditions Key meteorological variables such as wind speed, wind direction, temperature and relative humidity were monitored during exposure trials involving residents and bystanders to account for the influence of weather conditions on spray drift. Three weather stations (Raincrop, Sencrop, Lile, France; Windcrop, Sencrop, Lille, France; Froggit WH3000SE PRO, Shenzhen Fine Offset Electronics Co., Ltd., Guangdong, China) were positioned 1 m above the canopy and located 15 m downwind from the edge of the sprayed area (Figure 1). 2.4. Operator’s Exposure To assess the pilot and operators’ dermal exposure, a portion of 8 ha of the vineyard was sprayed, requiring a total of eight mixing and loading operations per working day. The pilot and auxiliary operator’s potential and actual dermal exposure were measured during each trial, with six operators sampled throughout the study. The same pilot participated in all three trials, while two different workers performed auxiliary tasks, including mixing and loading PPPs into the UASS, changing baeries, and cleaning the UASS pump. Operators were equipped with body and hand dosimeters to assess dermal exposure during auxiliary activities and piloting. The methodology followed to assess dermal exposure was based on the whole body method described in the OECD guidance document for conducting studies of occupational exposure to pesticides during agricultural application [20]. For the auxiliary operator, body dermal exposure was measured using a longsleeved coon shirt and coon trousers as internal dosimeters and coon/polyester coveralls as external dosimeters. Hand dermal exposure was assessed using coon gloves. Since the pilot operated at a distance from the UASS and had no direct contact with the spraying process, only potential body exposure was assessed using a coon/polyester coverall. Due to difficulties handling the drone’s remote touchscreen, the pilot wore nitrile gloves over the coon gloves, allowing for the assessment of both potential and actual hand exposure. At the end of each workday, trained technicians carefully removed internal and external body and hand dosimeters from the pilot and the auxiliary operator to prevent cross-contamination. The external coveralls were hung vertically and cut into sections (sleeves, torso, and legs) using cleaned scissors. Internal coon shirts were similarly cut into separate sections (sleeves and torso), while internal trousers were processed whole, without sectioning. Throughout the procedure, scissors were thoroughly cleaned before and after each cut. The gloves of both hands were treated as a single sample. Technicians in charge of recovering and processing the dosimeters wore nitrile gloves, which were Figure 2. UASS used during the spraying trials. 2.3. Weather Conditions Key meteorological variables such as wind speed, wind direction, temperature and relative humidity were monitored during exposure trials involving residents and bystanders to account for the influence of weather conditions on spray drift. Three weather stations (Raincrop, Sencrop, Lile, France; Windcrop, Sencrop, Lille, France; Froggit WH3000SE PRO, Shenzhen Fine Offset Electronics Co., Ltd., Shenzhen, China) were positioned 1 m above the canopy and located 15 m downwind from the edge of the sprayed area (Figure 1). 2.4. Operator’s Exposure To assess the pilot and operators’ dermal exposure, a portion of 8 ha of the vineyard was sprayed, requiring a total of eight mixing and loading operations per working day. The pilot and auxiliary operator’s potential and actual dermal exposure were measured during each trial, with six operators sampled throughout the study. The same pilot participated in Drones 2025,9, 345 5 of 17 all three trials, while two different workers performed auxiliary tasks, including mixing and loading PPPs into the UASS, changing batteries, and cleaning the UASS pump. Operators were equipped with body and hand dosimeters to assess dermal exposure during auxiliary activities and piloting. The methodology followed to assess dermal exposure was based on the whole body method described in the OECD guidance document for conducting studies of occupational exposure to pesticides during agricultural application [ 20 ]. For the auxiliary operator, body dermal exposure was measured using a long-sleeved cotton shirt and cotton trousers as internal dosimeters and cotton/polyester coveralls as external dosimeters. Hand dermal exposure was assessed using cotton gloves. Since the pilot operated at a distance from the UASS and had no direct contact with the spraying process, only potential body exposure was assessed using a cotton/polyester coverall. Due to difficulties handling the drone’s remote touchscreen, the pilot wore nitrile gloves over the cotton gloves, allowing for the assessment of both potential and actual hand exposure. At the end of each workday, trained technicians carefully removed internal and external body and hand dosimeters from the pilot and the auxiliary operator to prevent cross-contamination. The external coveralls were hung vertically and cut into sections (sleeves, torso, and legs) using cleaned scissors. Internal cotton shirts were similarly cut into separate sections (sleeves and torso), while internal trousers were processed whole, without sectioning. Throughout the procedure, scissors were thoroughly cleaned before and after each cut. The gloves of both hands were treated as a single sample. Technicians in charge of recovering and processing the dosimeters wore nitrile gloves, which were replaced after processing each sample to minimize the risk of cross-contamination. All samples were individually wrapped in aluminum foil, labeled, and stored at − 18 ◦ C until analysis. Each auxiliary operator generated seven samples per trial, while the pilot generated five, resulting in a total of 36 operator dosimeter samples analyzed. All operators were instructed not to remove their dosimeters during the trials and to request immediate replacement in case of breakage or deterioration. 2.5. Bystanders’ and Residents’ Exposure To assess bystanders’ and residents’ potential and actual dermal exposure, an adaptation of the whole body method described in the OECD guidance document for conducting studies of occupational exposure to pesticides during agricultural application [ 20 ] was used. Three adult-sized mannequins and three child-sized mannequins were positioned at 10 m intervals, 5 m downwind from the crop rows (Figure 1). Adult sized mannequins were 175 cm high while mannequins representing children were 110 cm high. Each mannequin was dressed in cotton clothing, which served as dosimeters. To simulate a worst-case exposure scenario, the mannequins wore T-shirts and shorts as external dosimeters, while long-sleeved cotton shirts and long cotton trousers functioned as internal dosimeters. Additionally, each mannequin’s head was covered with a balaclava to measure dermal exposure on the head (Figure 3). Internal dosimeters were cut to sample specific body parts not covered by the external dosimeters, including the arm and leg portions. For each mannequin, we obtained seven samples: external dosimeters composed of short trousers and T-shirts, internal dosimeters consisting of uncovered arm and leg body parts, covered arm and leg body parts, and balaclava covering the head. All samples were individually labeled, wrapped in foil, and stored at − 18 ◦ C under dark conditions until further analysis. A total of 126 mannequin dosimeters were analyzed. Drones 2025,9, 345 6 of 17 Drones 2025, 9, x FOR PEER REVIEW 6 of 18 replaced after processing each sample to minimize the risk of cross-contamination. All samples were individually wrapped in aluminum foil, labeled, and stored at −18 °C until analysis. Each auxiliary operator generated seven samples per trial, while the pilot generated five, resulting in a total of 36 operator dosimeter samples analyzed. All operators were instructed not to remove their dosimeters during the trials and to request immediate replacement in case of breakage or deterioration. 2.5. Bystanders’ and Residents’ Exposure To assess bystanders’ and residents’ potential and actual dermal exposure, an adaptation of the whole body method described in the OECD guidance document for conducting studies of occupational exposure to pesticides during agricultural application [20] was used. Three adult-sized mannequins and three child-sized mannequins were positioned at 10 m intervals, 5 m downwind from the crop rows (Figure 1). Adult sized mannequins were 175 cm high while mannequins representing children were 110 cm high. Each mannequin was dressed in coon clothing, which served as dosimeters. To simulate a worstcase exposure scenario, the mannequins wore T-shirts and shorts as external dosimeters, while long-sleeved coon shirts and long coon trousers functioned as internal dosimeters. Additionally, each mannequin’s head was covered with a balaclava to measure dermal exposure on the head (Figure 3). Figure 3. Mannequins array equipped with the dosimeters used for residents and bystander’s exposure trials. Internal dosimeters were cut to sample specific body parts not covered by the external dosimeters, including the arm and leg portions. For each mannequin, we obtained seven samples: external dosimeters composed of short trousers and T-shirts, internal dosimeters consisting of uncovered arm and leg body parts, covered arm and leg body parts, and balaclava covering the head. All samples were individually labeled, wrapped in foil, and stored at −18 °C under dark conditions until further analysis. A total of 126 mannequin dosimeters were analyzed. 2.6. Field Fortification A field fortification was performed at the field site to ensure uniformity across trial repetitions. Before the trials, blank control samples were collected from unused dosimeter materials, including inner shirts, pants, coon gloves, balaclavas, and outer protective coveralls. In addition to blank samples, fortified samples were prepared by spiking unused sections of the same dosimeter matrices with known analyte concentrations at both the limit of quantification (LOQ) and 100×LOQ levels. Three replicate sections (0.2 m × 0.2 m) were used for each fortification level. The fortification process was carried out in situ but outside the treated area to minimize the risk of cross-contamination. Additionally, Figure 3. Mannequins array equipped with the dosimeters used for residents and bystander’s exposure trials. 2.6. Field Fortification A field fortification was performed at the field site to ensure uniformity across trial repetitions. Before the trials, blank control samples were collected from unused dosimeter materials, including inner shirts, pants, cotton gloves, balaclavas, and outer protective coveralls. In addition to blank samples, fortified samples were prepared by spiking unused sections of the same dosimeter matrices with known analyte concentrations at both the limit of quantification (LOQ) and 100 × LOQ levels. Three replicate sections ( 0.2 m ×0.2 m ) were used for each fortification level. The fortification process was carried out in situ but outside the treated area to minimize the risk of cross-contamination. Additionally, laboratory fortification was performed following the same methodology. Field fortifications were carried out to allow the fortified samples to experience the same environmental conditions as the trial samples, helping to ensure that any potential losses or changes in analyte recovery due to environmental factors would be accurately captured. For all dosimeters except gloves, fortification involved spiking the matrices with 0.5 mL of a 10 µ g · mL −1 solution of Spintor 480 SC for the low-level (LOQ) fortification and 1 mL of a 500 µ g · mL −1 solution for the high-level (100 × LOQ) fortification. For gloves, the fortifications consisted of 0.5 mL of a 4 µ g · mL −1 solution for the low level and 1 mL of a 200 µg·mL−1solution for the high level (100 ×LOQ). Each fortified sample was wrapped in aluminum foil and stored at − 18 ◦ C until analysis. Samples were spiked at the beginning of the simulated workday and left to dry until the end of the day. After each trial, the samples were wrapped aluminum foil, bagged, individually labeled, and stored at −18 ◦C until analysis. 2.7. Analytical Determination 2.7.1. Sample Preparation After testing various proportions of acetonitrile/water mixtures (Symta SLL, Madrid, Spain), the optimal recovery of the studied analytes, Spinosyn A (99%) and Spinosyn D (98%) (Corteva Agriscience LLC, Indianapolis, IN, USA), was achieved using an 80/20 v/v acetonitrile/water mixture. The volume of this solvent mixture used during the extraction step varied based on dosimeter size, with 1000 mL, 500 mL, or 200 mL employed accordingly. For recovery studies, aliquots of individual stock solutions containing 500 µ g · mL −1 of each target analyte (Spinosyn A and Spinosyn D, the active ingredients of the plant protection product Spintor 480 SC) were mixed with a blank matrix solution, which was obtained by extracting 0.2 × 0.2 m sections from different dosimeter types. Specifically, 1000 µ L of Spinosyn A and Spinosyn D were used for the 1000 mL solutions designated for inner and outer dosimeters, 500 µ L for the 500 mL solution used with balaclavas, and 200 µ L for the Drones 2025,9, 345 7 of 17 200 mL solution applied to cotton and nitrile gloves. Although the commercial product Spintor 480 SC (Spinosad 48% w/v; suspension concentrate, Corteva Agriscience Inc., Indianapolis, IN, USA) was used during field application, the pure analytical standards of Spinosyn A and D were selected for the recovery experiments to obtain accurate and reproducible quantification of the target analytes without potential matrix interferences from the formulation additives present in the commercial product. A 500 µ g · mL −1 solution of Spinosyn A and Spinosyn D was used for the 100 × LOQ level, corresponding to final concentrations of 0.005 µ g · mL −1 for Spinosyn A and 0.5 µ g · mL −1 for Spynosin D. The samples fortified in the laboratory were allowed to stand for 30 min before being processed. For field samples, dosimeters were transferred into HDPE screw-cap bottles before the optimized extraction solvent was added, ensuring the entire sample was fully immersed. The samples were then vigorously mixed using a ROTABIT orbital shaker (J.P. Selecta, Barcelona, Spain) at 230 rpm for 1 h. After standing for 5 min, 1 mL aliquot was transferred into a High-Performance Liquid Chromatography (HPLC) vial for analysis. 2.7.2. HPLC-MS/MS Analysis The High-Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLCMS/MS) system (Agilent Technologies, Santa Clara, CA, USA) used for analysis consisted of a 1200 Series liquid chromatograph equipped with a quaternary solvent delivery system, an autosampler, a column oven, a vacuum degasser, a sample thermostat, and a triple quadrupole MS/MS (Agilent 6420, Agilent Technologies Inc., Santa Clara, CA, USA). Chromatographic separation was achieved using a C18 Kinetex column (4.6 internal diameter × 100 mm length, 2.6 µ m particle size) (Phenomenex, Milford, MA, USA) with the column oven temperature set to 20 ◦ C throughout the experiments. Samples were maintained at 8 ◦ C using an autosampler thermostat. The mobile phase (A) consisted of water with 5 mM ammonium formate (Aldrich, Steinheim, Germany) and acetonitrile (phase B). An isocratic method was employed with a 10% A and 90% B mobile phase composition. The flow rate was maintained at 0.7 mL · min −1 , and the injection volume was fixed at 2 µ L. Detection was performed using a triple quadrupole system operating in multiple-reaction monitoring (MRM) mode. The electrospray ionization (ESI) source conditions were optimized with a gas temperature of 300 ◦ C, drying gas flow rate, 11 L · min −1 , nebulizer pressure of 40 psi, and a capillary voltage of 4000 V, with N 2 gas used as the nebulizer gas. Parameters were optimized using a standard solution of Spintor (10 µ g · mL −1 of each compound) prepared in 20% water and 80% acetonitrile. Full-scan spectra were initially acquired to optimize collision-induced dissociation fragmentation for maximum sensitivity of the precursor ions. Subsequently, MS/MS spectra in production mode were acquired to obtain fragment ion information. A multiple reaction monitoring (MRM) experiment was conducted to select the optimum collision energy for each specific transition, with collision energies ranging from 2 to 60 eV. Data processing was performed with Agilent Mass Hunter Data Acquisition software (version B.07.00) and processed with Agilent Mass Hunter Quantitative Analysis software (version B.07.00). 2.7.3. Method Validation The method was validated to assess its performance according to a conventional validation procedure, following the guidelines outlined in SANTE/2020/12830 [ 21 ]. The validation parameters included selectivity, linearity, limit of detection (LOD), limit of quantification (LOQ), matrix effects, accuracy, and precision. Selectivity was assessed by analyzing blank samples to identify any potential interfering peaks under the same chromatographic conditions as the test samples. Chromatograms were monitored for the Drones 2025,9, 345 8 of 17 characteristic ions of each analyte (Spinosyn A and Spinosyn D) at their expected retention times, and no significant interferences were observed in the blanks used for recovery experiments. Linearity was evaluated using calibration curves prepared in an acetonitrile/water mixture (80/20% v/v) covering two working ranges: 0.001–0.075 µ g · mL −1 for low concentrations and 0.001–0.25 µ g · mL −1 for high concentrations. Method acceptance criteria required a correlation coefficient (r 2 ) greater than 0.99 and residuals below 30% for linearity. The matrix effect, expressed as signal suppression/enhancement (SSE), was assessed by comparing the slope ratio of the matrix-matched calibration curve to that of the pure solvent calibration curve. The limit of detection (LOD) was determined as the analyte concentration corresponding to a signal-to-noise (S/N) ratio of 3, obtained from chromatograms at the lowest tested concentration. The limit of quantification (LOQ) was established as the lowest concentration that provided acceptable recoveries and precision within the defined method parameters. To assess accuracy and precision, recovery assays were conducted by spiking cotton dosimeters with Spinosyn A and Spinosyn D at two concentration levels: LOQ and 100 ×LOQ . 5 replicates of each spiked sample were prepared, followed by analyte extraction and purification. Accuracy was evaluated based on recovery percentages, with an acceptance range between 70% and 120%, while precision was assessed by ensuring a relative standard deviation (RSD) below 20%. Repeatability precision, expressed as RSD, was determined by intra-day and inter-day assays. 2.7.4. Data Analysis Dermal exposure for operator’s body parts exposure and residents/bystanders was assessed using a one-way analysis of variance (ANOVA) coupled with Fisher’s least significant difference (LSD) test [ 22 ]. Data normality data were assessed using the Shapiro–Wilk test [ 23 ], while Levene’s test [ 24 ] was employed to examine the homogeneity of variance. All statistical analyses were performed at a 95% confidence level. In some cases the data did not meet the assumptions for ANOVA; therefore, the Kruskal–Wallis test was applied [ 25 ]. Data analysis was performed using the R statistical software [26]. To contextualize the pilot and operator dermal exposure results, estimated exposure values from established operator exposure models were used as standardized reference points for conventional application scenarios. Specifically, the EFSA calculator [ 17 ] and US EPA PHED [ 18 ] are harmonized tools accepted by regulatory authorities for operator exposure assessment. It is important to note that these model estimates represent point values without associated variability and were not included in statistical hypothesis testing. Instead, the model outputs were used for descriptive comparison with the empirical data to illustrate the magnitude of differences in exposure levels. The spraying methods for this comparative assessment included tractor-mounted application, manual application with a knapsack, manual handheld application (spraying tank with a lance), and conventional aircraft application. 3. Results 3.1. Weather Conditions Average weather conditions for each field trial are reflected in Table 1. ANOVA analysis suggests that differences in climatic conditions between trials did not significantly influence pilots’ or auxiliary operators’ exposure. However, ANOVA test results revealed that the first residents/bystanders’ trial had statistical differences compared to the other trials, suggesting a potential influence by the climatic conditions. Drones 2025,9, 345 9 of 17 Table 1. Average weather data collected during the residents/bystander’s exposure trials and their standard deviation. Parameters Trial 1 Trial 2 Trial 3 Date (dd/mm/yyyy) 21/07/2022 28/07/2022 04/08/2022 Air temperature (◦C) 19.66 ±1.14 20.74 ±2.23 16.82 ±0.79 Relative humidity (%) 76.10 ±0.99 90.89 ±7.97 79.22 ±2.65 Mean wind speed (m·s−1)0.84 ±0.59 2.21 ±0.18 1.55 ±0.25 Mean wind direction (◦) 247.14 ±7.71 250.85 ±16.81 225.12 ±5.76 Given that the crop rows in the residents/bystanders’ trial area were oriented at 120 ◦ , a wind direction of 210 ◦ would have been perpendicular to the spraying direction. This represents a worst-case scenario and is typically considered an ideal condition for drift assessment trials. 3.2. Auxiliary Operator Dermal Exposure Auxiliary operator dermal exposure values obtained in this study were compared to those derived from the Agricultural Operator Exposure Model (AOEM) [ 27 ], as included in the EFSA OPEX Guidance, for conventional tractor spraying, manual knapsack, and manual handheld spraying. Exposure values were expressed in micrograms of residue per kilogram of active substance (µg·kg−1). Table 2presents the exposure values measured for the auxiliary operator, expressed as µg·kg−1of active substance (a.s.) for each dosimeter. Table 2. Auxiliary operator exposure for each dosimeter and trial. Average exposure values and corresponding standard error are presented in µg·kg−1of active substance. Dosimeter Trial 1 Trial 2 Trial 3 Average Arms internal 216.76 43.24 173.26 144.42 ±42.56 Torso internal 52.51 43.32 51.97 49.27 ±2.43 Legs internal 313.56 124.44 664.53 367.51 ±129.19 Hands internal 548.11 814.70 199.67 520.82 ±145.39 Arms external 1913.95 1476.37 2807.39 2065.90 ±319.80 Torso external 5925.16 2780.41 11,241.57 6649.05 ±2016.09 Legs external 10,709.59 15,726.34 1683.15 9373.03 ±3354.68 As Table 2indicates, auxiliary operator’s most vulnerable body parts during UASS operations seem to be the hands, followed by the legs, arms and torso. However, this is just a trend, as the Kruskal–Wallis test revealed no statistically significant differences between the internal dosimeters. Regarding external dosimeters, the results of ANOVA reveal no statistical differences; however, results suggest a trend in which lower parts of the body appear to have higher potential dermal exposure for operators. Table 3presents the total potential and actual dermal exposure values recorded for auxiliary operators in this study, alongside exposure estimates obtained using the EFSA OPEX Guidance 2022 for conventional tractor-mounted, manual knapsack, and manual handheld spraying, as well as exposure estimates derived from US EPA PHED for aerial applications. Results (Table 3) show that dermal body and hand exposure generated by UASS spraying were substantially higher than those associated with traditional spraying methods. Drones 2025,9, 345 16 of 17 conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Abbreviations The following abbreviations are used in this manuscript: AOEM Agricultural Operator Exposure Model EFSA European Food Safety Authority EU European Union LOD Limit of detection LOQ Limit of quantification MRM Multiple reaction monitoring OPEX Operator exposure PHED Pesticide handler exposure database PPP Plant Protection Product SSE Signal suppression/enhancement RSD Relative standard deviation UASS Unmanned Aerial Spraying System UAV Unmanned Aerial Vehicle References 1. Giles, D.K.; Billing, R.C. Deployment and Performance of a Uav for Crop Spraying. Chem. Eng. Trans. 2015,44, 307–312. [CrossRef] 2. Wang, G.; Li, X.; Andaloro, J.; Chen, P.; Song, C.; Shan, C.; Chen, S.; Lan, Y. Deposition and Biological Efficacy of UAV-Based Low-Volume Application in Rice Fields. Int. J. Precis. Agric. Aviat. 2018,1, 65–72. 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