Optimization of passive sampler preparation for the detection of reactive gases (NO2, NH3, HNO3, O3, SO2) in ambient air

Optimization of passive sampler preparation for the detection of reactive gases (NO2, NH3, HNO3, O3, SO2) in ambient air | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimization of passive sampler preparation for the detection of reactive gases (NO 2 , NH 3 , HNO 3 , O 3 , SO 2 ) in ambient air Julien Bahino, Sékou Keita, Véronique Yoboué This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8071359/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract This study conducted within the European DACCIWA FP7 program (2014–2017), presents an optimized protocol for the preparation, deployment, and laboratory analysis of International Network to study Deposition and Atmospheric chemistry in Africa (INDAAF) passive samplers used to monitor reactive gases (NO 2 , NH 3 , HNO 3 , O 3 , SO 2 ) in ambient air. The updated procedure improves the cleaning of reusable components, the preparation of impregnation solutions, the controlled drying and storage of filters, and the standardization of field handling and ion chromatography analysis. From 2013 to 2017, a total of 5026 passive samplers were produced and deployed across urban monitoring sites in West and Central Africa. The protocol optimization led to a systematic enhancement in analytical performance. Detection limits were reduced to approximately 0.05 ± 0.02 ppb for HNO 3 , 0.15 ± 0.07 ppb for NO 2 , 0.5 ± 0.1 ppb for NH 3 , 0.04 ± 0.02 ppb for SO 2 , and 0.07 ± 0.05 ppb for O 3 . Reproducibility also improved, reaching 12% for HNO 3 , 7% for NO 2 , 10% for NH 3 , 12% for SO 2 , and 8% for O 3 , indicating greater measurement stability and consistency. Performance evaluation based on co-located NH 3 measurements using INDAAF samplers and CEH ALPHA reference badges showed strong agreement (R² = 0.84), confirming the reliability of the optimized method under real field conditions. passive sampler ammonia nitrogen dioxide ozone ion chromatography INDAAF air pollution Africa Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1. Introduction Reactive trace gases such as nitrogen dioxide (NO 2 ), ammonia (NH 3 ), sulfur dioxide (SO 2 ), nitric acid (HNO 3 ), and ozone (O 3 ) play crucial roles in atmospheric chemistry by influencing air quality, nutrient deposition, and radiative forcing. Monitoring their ambient concentrations is essential for evaluating emission sources, understanding atmospheric processes, and assessing long-term environmental and health impacts [ 1 , 2 ]. In regions where continuous monitoring networks are scarce, particularly in tropical and subtropical Africa, passive sampling has become a reliable and affordable alternative to traditional active analysers [ 3 , 4 ]. Gaseous passive samplers are especially useful in distant and resource-constrained settings because they don't require electricity and rely on chemical trapping and molecular diffusion to collect gaseous species over long exposure times [ 5 – 8 ]. Within the International Network for the Study of Atmospheric Deposition in Africa (INDAAF), passive samplers have been deployed since 1995 to measure major atmospheric gases across diverse African ecosystems. Based on Ferm's, (1991) pioneering design and validated under the World Meteorological Organization - Global Atmosphere Watch (WMO-GAW) standards, these samplers ensure high scientific reliability and comparability with other global networks such as the Equatorial Africa Deposition Network (EADN) [ 10 ]. Their robustness, stability and precision under both rural and urban conditions has been demonstrated in numerous studies. Adon et al. (2010, 2013) confirmed their accuracy across humid savanna, dry savanna, and forest ecosystems, while Bahino (2018), Bahino et al. (2018) and Adon et al. (2016) validated their performance in urban settings such as Abidjan, Dakar, Bamako or Cotonou, where emission sources and pollutant gradients are more variable [ 5 , 6 , 11 – 13 ]. More recently, Bahino et al. (2025), further confirmed the reliability and accuracy of INDAAF ammonia (NH₃) passive samplers under tropical urban conditions of Akouedo landfill in Abidjan [ 14 ]. These results reinforce the robustness of the INDAAF methodology, recognized internationally [ 15 ], while emphasizing the importance of continuous optimization in sampler fabrication, impregnation procedures, and analytical protocols to ensure consistent and high-quality data across monitoring sites. The main objective of this study is to present a comprehensive overview of the design, preparation, and field deployment of the INDAAF passive samplers, developed for monitoring key reactive gases in the atmosphere (NO 2 , NH 3 , HNO 3 , O 3 and SO 2 . This paper aims to standardise and optimise the production process to ensure high reproducibility, accuracy and comparability of atmospheric measurements at different monitoring sites. To this end, it documents the entire methodological workflow, from preparing impregnation solutions to assembling sensors and conditioning them in the field. 2. Materials and methods 2.1 Design of INDAAF passive samplers The INDAAF passive samplers consist of six main components which are a snap-on polythene cap, a snap-on polyhe cap with hole both with 29 mm diameter, a cellulose filter (21 mm diameter) impregnated with a selective trapping solution for each gas measured, a PVC ring, a PTFE membrane filter (25 mm, 1 µm pore size) that limits particle entry and reduces internal turbulence, and a stainless-steel protection grid. Figure 1 illustrate the mains parts of a INDAAF passive sampler. Within the INDAAF network, four color-coded passive samplers are used to identify the target gases. The white caps are used for NH₃, the gray caps for NO₂, the black caps for HNO₃ and SO₂, and the gray-black caps are used for the O₃ samplers. This standardized color scheme ensures easy recognition, reduces handling errors, and improves consistency during both field deployment and laboratory analysis. An illustration of the INDAAF passive samplers and their corresponding color codes is shown in Fig. 2 , highlighting their specific design and visual differentiation for monitoring reactive trace gases in ambient air. 2.2 Operating principle of INDAAF passive samplers As mentioned previously, the design of the INDAAF passive gas samplers is based on the foundational work of Ferm [ 9 , 16 ]. Their reliability was subsequently confirmed through rigorous field evaluations by Adon et al. (2010, 2013) [ 5 , 6 ]. These samplers operate based on two core principles that facilitate the capture and chemical fixation of reactive gases in the atmosphere. 2.2.1 Molecular diffusion This first principle relies on the physical process of molecular diffusion. It assumes that the mean concentration of the target gas in the surrounding ambient air is higher than inside the sampler. According to Fick's first law of diffusion, the gas molecules will naturally migrate from the region of higher concentration (the ambient air) to the region of lower concentration (inside the sampler). This passive diffusion process enables continuous airflow into the sampler, without the need for active pumping or an external power supply. This makes it ideal for long-term, low-maintenance monitoring campaigns in remote or resource-limited environments. 2.2.2 Chemical reaction mechanisms The second principle involves a chemical reaction between diffused gas molecules and a trapping reactive agent impregnated onto a cellulose filter inside the sampler. Each reactive gas (NO₂, SO₂, HNO₃, NH₃ and O₃) reacts specifically with its respective absorbing solution to form stable ionic species that can be quantified in a laboratory, usually by ion chromatography. These chemical reactions have been demonstrated to be efficient and specific across various atmospheric conditions, ensuring the selective capture and quantitative determination of each gas [ 17 ]. The main trapping reactions used in INDAAF passive samplers are summarised in Table 1 . Table 1 Chemical reactions between reactive gases and trapping solutions (adapted from Al-Ourabi, 2002)[ 17 ]. Gas (Sampler color) Chemical reaction on filter HNO 3 , SO 2 (Black) \(\:{\text{H}\text{N}\text{O}}_{3}\) (g) + \(\:{\text{O}\text{H}}^{-}\) → \(\:{\text{N}\text{O}}_{3}^{-}\) + \(\:{\text{H}}_{2}\text{O}\) ; (1) 2 \(\:{\text{S}\text{O}}_{2}\:\) (g) + 4 \(\:{\text{O}\text{H}}^{-}\) + \(\:{\text{O}}_{2}\) → 2 \(\:{\text{H}}_{2}\text{O}\) + 2 \(\:{\text{S}\text{O}}_{4}^{2-}\) (2) NO 2 (Gray) 2 \(\:{\text{N}\text{O}}_{2}\:\) (g) + 3 \(\:{\text{I}}^{-}\) → 2 \(\:{\text{N}\text{O}}_{2}^{-}\:\) + \(\:{\text{I}}_{3}^{-}\) (3) NH 3 (White) \(\:{\text{N}\text{H}}_{3}\) (g) + \(\:{\text{H}}^{\mp\:}\) → \(\:{\text{N}\text{H}}_{4}^{+}\) (4) O 3 (Gray-black) \(\:{\text{O}}_{3}\) (g) + \(\:{\text{N}\text{O}}_{2}^{-}\) → \(\:{\text{N}\text{O}}_{3}^{-}\) + \(\:{\text{O}}_{2}\) (5) 2.2.3 Detection limits and reproducibility The analytical performance of the INDAAF passive samplers was rigorously assessed by Adon et al. (2010), who determined the detection limits for each target gas based on the analysis of blank samplers, both those deployed in the field without exposure and those retained in the laboratory after fabrication. This approach enabled robust estimation of background contamination and analytical noise, ensuring reliable quantification thresholds. Based on a dataset of blanks produced between 1998 and 2007, the following detection limits were determined: 0.07 ± 0.03 parts per billion (ppb) for nitric acid (HNO₃), 0.2 ± 0.1 ppb for nitrogen dioxide (NO₂), 0.7 ± 0.2 ppb for ammonia (NH₃), 0.05 ± 0.03 ppb for sulphur dioxide (SO₂), and 0.1 ± 0.1 ppb for ozone (O₃). These low detection thresholds demonstrate the high sensitivity of the INDAAF passive sampling method, even under tropical atmospheric conditions where background levels can be very low. The reproducibility, as measured by the coefficient of variation between duplicate samplers, was found to be 20% for HNO₃, 9.8% for NO₂, 14.3% for NH₃, 16.6% for SO₂ and 10% for O₃. These results confirm the robustness of the INDAAF protocol for long-term atmospheric monitoring across diverse African ecosystems and indicate good analytical consistency. Given the proven sensitivity and reproducibility of INDAAF passive samplers, optimising the fabrication and preparation steps is crucial to ensure consistent performance at all monitoring sites. The sampler's configuration places particular emphasis on the quality and chemical integrity of its components, especially the cellulose filter impregnated with specific trapping solutions. 3. Optimization of INDAAF passive samplers preparation The INDAAF passive sampler consists of several mechanical and chemical components that can be grouped into two main categories. The first includes non-reusable elements, such as the cellulose filter (used as the reactive substrate impregnated with trapping solutions) and the PTFE (Teflon) filter. These are both replaced after each sampling period to prevent cross-contamination or chemical degradation. The second category comprises reusable components, including perforated and non-perforated plastic caps, metallic grids and PVC rings that form the sampler's structural body. To ensure subsequent measurements are reliable and reproducible, these reusable components must undergo strict cleaning and decontamination procedures before each deployment. 3.1 Cleaning and handling of reusable components The reusable parts of INDAAF passive samplers, including the plastic caps (with or without perforations), the PVC rings and the stainless-steel grids, are cleaned separately to avoid cross-contamination. All washing operations were performed using ultrapure water with a resistivity of ρ = 18.2 MΩ·cm, which was produced by an ELGA purification system (Fig. 3 a). Each component type was placed in a crystalliser or large beaker and completely immersed in ultrapure water. The parts were rinsed twice to remove dust particles and visible residues. Once cleaned, the rinse water is replaced with ultrapure water and the crystalliser is transferred to a thermostatically controlled ultrasonic bath (Fisher Scientific), which is equipped with a programmable timer (Fig. 3 b). The components are subjected to ultrasound for 10 minutes. The water is then changed, and the process is repeated once more to ensure the complete removal of contaminants and chemical residues. After ultrasonic cleaning, the components were rinsed twice more with ultrapure water and then dried for two hours under an IBERIS brand laminar flow hood with an air velocity of 1.2 m·s⁻¹ (Fig. 3 c). Once completely dry, all parts were stored in sterile plastic boxes to ensure full protection from airborne impurities, dust and residual moisture until further use. 3.2 Preparation of cellulose filters (cutting, cleaning, and drying) The filters used to trap gaseous pollutants are Whatman 'ashless' cellulose filters, which are originally 90 mm in diameter. To fit the INDAAF passive samplers, 21 mm diameter circular filters are cut using a precision punch. Typically, six to seven small filters can be obtained from one 90 mm filter. After cutting, the filters are cleaned using the same procedure as for the reusable components described previously. Each batch undergoes two 10-minute ultrasonic washes in ultrapure water, followed by a third 10-minute ultrasonic bath in methanol. Protective gloves must be worn during this step, as methanol is a toxic and flammable solvent. Once washed, the filters are placed on stainless steel trays and dried for approximately two hours under a laminar flow hood to allow complete evaporation of the methanol. They are then transferred to a MEMMERT drying oven (Fig. 4 a) and maintained at 30°C for 24 hours to ensure full dehydration. Finally, the clean, dry filters are stored in labelled, airtight plastic boxes with the preparation date clearly marked, to ensure traceability and quality control (Fig. 4 b). 3.3 Preparation of impregnation solutions A specific chemical trapping solution is prepared for each target gas to ensure selective absorption and stable retention on the cellulose filter during exposure. These impregnation solutions are freshly prepared prior to each field campaign to prevent degradation or chemical alteration. Once prepared, the solutions are stored in tightly sealed containers under refrigeration (typically at 4°C) until they are shipped to the measurement sites. To maintain consistency across sampling periods, the same volumetric flask is used for each solution type throughout the study. For each filter, a small amount of the trapping solution is put onto the cellulose surface. This is usually 50 µL. The trapping solution is put on using special Eppendorf micropipettes that have been calibrated before (Fig. 5 a). This controlled application ensures uniform impregnation and reproducible diffusion conditions within the passive samplers. Each solution is formulated to react with a specific reactive gas (NO₂, NH₃, SO₂, HNO₃ or O₃). The composition and preparation procedure of these trapping solutions are described in the following subsections. 3.3.1 Solution for Ammonia (NH₃) passive samplers For ammonia (NH₃) INDAAF passive samplers, the cellulose filter used is impregnated with 50 µL of a citric acid solution, which serves as the chemical trapping agent. This solution enables efficient absorption of gaseous ammonia through acid-base neutralization, forming ammonium ions (NH₄⁺) that are later quantified by ion chromatography. The citric acid solution is prepared by weighing 1 g of citric acid using an analytical electronic balance (Fig. 5 a). The weighed acid is then introduced into a 50 mL volumetric flask that already contains a small amount of methanol to aid dissolution. Methanol is subsequently added up to the calibration mark to reach the desired volume. The resulting solution is thoroughly homogenized using a magnetic stirrer (Fig. 5 b) to ensure complete dissolution of the solute and uniform chemical composition. Once prepared, the solution is transferred to an amber storage bottle to prevent photodegradation and kept refrigerated until use. The complete preparation workflow of the citric acid trapping solution for NH₃ passive samplers is illustrated in Fig. 6 . 3.3.2 Solution for Nitrogen Dioxide (NO₂) passive samplers For nitrogen dioxide (NO₂), the INDAAF gray samplers use cellulose filters impregnated with 50 µL of an alkaline solution composed of sodium hydroxide (NaOH) and sodium iodide (NaI). This chemical mixture facilitates the quantitative trapping of NO₂ through the formation of nitrite (NO₂⁻) and triiodide (I₃⁻) ions via redox reactions occurring on the filter surface. The trapping solution is prepared by accurately weighing 0.44 g of NaOH pellets and 3.95 g of NaI crystals using an analytical balance. Both reagents are then dissolved in 50 mL of methanol within a calibrated volumetric flask. Methanol is selected as the solvent for its ability to enhance solubility and ensure a uniform coating on the filter surface. The mixture is subsequently homogenized with a magnetic stirrer to obtain a clear and stable solution. Before impregnation, the pH of the solution is checked using a pH meter to confirm strong alkalinity (pH > 12), which is essential to guarantee complete conversion of NO₂ to its ionic products during exposure. The solution is then stored in an airtight, light-protected bottle and kept refrigerated until application. 3.3.3 Solution for Sulfur Dioxide (SO₂) and Nitric Acid (HNO₃) passive samplers The black INDAAF passive samplers are designed to trap acidic gases such as sulfur dioxide (SO₂) and nitric acid (HNO₃) through neutralization reactions on an alkaline cellulose filter. Each filter is impregnated with 50 µL of a sodium hydroxide (NaOH) solution, which serves as the trapping medium by converting these reactive gases into their corresponding anions (SO₄²⁻ and NO₃⁻). To prepare this solution, 0.5 g of NaOH pellets is carefully weighed using an analytical balance and dissolved in a few milliliters of deionized water to initiate solubilization. The mixture is then quantitatively transferred into a 50 mL volumetric flask, which is filled to the calibration mark with methanol. Methanol is used as a solvent to ensure uniform impregnation of the cellulose filter and to facilitate rapid drying. The resulting solution is thoroughly homogenized using a magnetic stirrer to obtain a clear and stable mixture. Before use, the pH is verified with a calibrated pH meter, ensuring that it remains above 12. This strong alkalinity is critical for the efficient absorption and neutralization of acidic gases during exposure. 3.3.4 Solution for Ozone (O₃) passive samplers For ozone measurements, the cellulose filter is impregnated with 50 µL of a trapping solution specifically designed to promote the oxidation of nitrite during exposure. The solution is prepared by weighing 0.25 g of sodium nitrite (NaNO₂) and 0.25 g of potassium carbonate (K₂CO₃), which are then introduced into a 50 mL volumetric flask containing a small volume of deionized water. Using a sterile disposable syringe, 0.5 mL of bidistilled glycerol is added to the mixture to enhance filter wetting and stabilize the impregnating solution during drying and storage. The volumetric flask is then filled to the 50 mL mark with ultrapure water. Finally, the solution is homogenized using a magnetic stirrer to ensure complete dissolution of the reagents and uniform distribution of the impregnating agents. 3.4 Impregnation of cellulose filters All trapping solutions used for the INDAAF passive samplers are freshly prepared and stored in a refrigerator until deployment in the field. Prior to impregnation, each cellulose filter is placed inside the lower (closed) plastic cap of the sampler. Using a calibrated Eppendorf micropipette, a precise volume of 50 µL of the corresponding trapping solution is carefully deposited onto the center of the filter to ensure uniform wetting (Fig. 7 ). This operation is carried out under a laminar flow hood to promote the controlled evaporation of methanol contained in the solution and to avoid contamination from ambient air. After impregnation, the filters are allowed to dry under the hood for approximately 30 minutes, until the solvent has fully evaporated and the reactive compounds are fully adsorbed onto the cellulose matrix. Once dry, the impregnated filters are immediately assembled with the remaining sampler components or stored in sterile, airtight containers to protect them from moisture and accidental exposure before field deployment. 4. Assembly and packaging of INDAAF passive samplers 4.1. Assembly of INDAAF Passive samplers The assembly of the passive samplers is carried out under clean laboratory conditions, using gloves and fine-tipped forceps to avoid contamination. Each sampler consists of six components (see Fig. 1 ). The impregnated cellulose filter is first placed inside the closed bottom cap. This cap is then fitted to the PVC ring. A PTFE (Teflon) membrane filter is carefully placed on top of the PVC ring using forceps, followed by the stainless-steel mesh grid. The assembly is then completed by securing the perforated top cap, which allows ambient air to diffuse into the sampler. 4.2 Packaging and storage of INDAAF passive sampler Once assembled, samplers are individually placed in labeled Minigrip® plastic bags and stored separately according to gas type to prevent handling confusion. Prior to field deployment, the individual sampler bags are transferred into clean, airtight plastic containers for shipment. Each container holds eight samplers, arranged as two samplers of each type (white for NH₃, gray for NO₂, black for SO₂/HNO₃, and gray-black for O₃). For NH₃ samplers, an additional sealed bottom cap is included in each bag to protect the filter before exposure. Control (blank) samplers are also prepared. These are stored in sealed containers and are either kept in the laboratory or shipped to the measurement sites without being exposed. Blank samplers are essential for determining background contamination and calculating detection limits. Figure 8 shows examples of packaged samplers stored in shipping containers. . Each container is labeled with the station name, city, country, and the planned exposure period (e.g., 2-week or monthly intervals). A field log sheet is included inside each container to record deployment and retrieval dates, and to document the mean ambient temperature, which is required to calculate atmospheric gas concentrations. An example of the field data sheet used for documenting the deployment, retrieval, and handling conditions of INDAAF passive samplers is presented in Fig. 9 . 4.3 Passive sampler shipment, deployment, and laboratory analysis 4.3.1 Shipment and field sampling protocol The prepared sampler boxes are sent to field sites using a rapid shipping service to minimize changes in humidity and temperature during transport. Upon arrival, field technicians follow standardized INDAAF operating procedures for installation, exposure, and return shipment. Upon reception at the deployment site, the passive samplers were stored in a refrigerator to prevent contamination or premature chemical reactions before exposure. At the beginning of each sampling period, two passive samplers of each gas type were mounted in duplicate on stainless-steel mounting rails, positioned at a height between 1.5 and 2.5 m above ground level, in accordance with atmospheric measurement standards to avoid direct ground influence and ensure representative ambient concentrations. To ensure consistent temporal coverage, each month was divided into two exposure periods of approximately 15 days: First exposure period: from the 1st day of the month to the morning of the 16th. Second exposure period: from the 16th of the month to the 1st day of the following month. At the end of each 15-day exposure, the deployed samplers were removed, immediately sealed in their individual storage bags, and placed back into a refrigerator to minimize post-exposure alteration. The next set of samplers was then installed to begin the following exposure period. Finally, all collected samplers were returned to the Laboratory of Aerology (Toulouse, France) for chemical extraction and analysis by ion chromatography (IC). All the sampling procedure is well described in bahino et al 2018. 4.3.2 Deployment of passive samplers From September 2013 to April 2017, a total of 5026 passive gas samplers were manufactured at the Aerology Laboratory and distributed to monitoring sites in several major African cities, including Bamako, Abidjan, Cotonou, Dakar, and Yaoundé. After the exposure period, all samplers were systematically returned to the laboratory for post-exposure conditioning and chemical analysis. A summary of the number of samplers manufactured, deployed, and analyzed is provided in Table 2 . Table 2 Overview of urban air quality monitoring campaigns using passive samplers in West and Central Africa, including sampling locations, exposure periods, and number of analyses (2013–2017). Measurement Campaign Measurement Site Sampling Period Number of Analyses Medium-term measurements Abidjan domestic fires January 2015 - March 2017 540 Abidjan traffic December 2014 - April 2017 550 Abidjan landfill fires December 2014 - March 2017 540 Cotonou traffic December 2014 - March 2017 580 Bamako traffic September 2013 - March 2017 850 Yaoundé traffic September 2013 - January 2017 680 Intensive campaigns Abidjan spatial monitoring 1 December 2015 - February 2016 760 Abidjan spatial monitoring 2 December 2016 - February 2017 800 Cotonou spatial monitoring December 2016 - February 2017 320 Total 5620 4.3.3. Chemical analysis of INDAAF passive samplers The Laboratory of Aerology (Toulouse, France) hosts a dedicated chromatography platform equipped with several Thermo Dionex ion chromatography (IC) systems (ICS-1000, ICS-1100, ICS-5000, and DX-500), allowing high-precision quantification of the ionic products formed on the impregnated filters. Each gaseous species is quantified indirectly through the ionic form resulting from its reaction with the trapping solution: ammonia (NH₃) is determined as ammonium (NH₄⁺), nitric acid (HNO₃) and ozone (O₃) are quantified as nitrate (NO₃⁻), sulfur dioxide (SO₂) as sulfate (SO₄²⁻), and nitrogen dioxide (NO₂) as nitrite (NO₂⁻). All IC systems were equipped with autosamplers, enabling continuous analytical sequences and reducing manual handling variability. Chromatographic data were processed using Chromeleon software, ensuring consistent peak identification, integration, and rigorous quality control. The ion chromatography analytical system used in this study has been extensively described in previous publications [ 6 , 18 , 19 ]. Table 3 Summary of ion chromatography systems and analytical configurations used at the Aerology Laboratory, including detected species, analytical columns, suppression systems, eluent compositions, and flow rates. Instrument System (Software) Analyzed Species Analytical Columns (4 mm) (Analysis Time) Suppression System Eluent Composition (Flow Rate) DIONEX ICS 1100 + AS50 Autosampler (Chromeleon 6.6) Cations: Na⁺, NH₄⁺, K⁺, Mg²⁺, Ca²⁺, Li⁺, Mn²⁺ Ion Exchange CG12A + CS12A (14 min) DIONEX CERS 500 Auto-Suppression Isocratic mode: 20 mM Methanesulfonic acid (MSA) (1 mL/min) DIONEX ICS 1000 + AS40 Autosampler (Chromeleon 6.6) Inorganic anions: Cl⁻, NO₂⁻, NO₃⁻, PO₄³⁻, SO₄²⁻ Ion Exchange AG4A-SC + AS4A-SC (14 min) DIONEX AERS 500 Auto-Suppression Isocratic mode: 1.8 mM CO₃²⁻ / 1.7 mM HCO₃⁻ (2 mL/min) DIONEX ICS 5000+ (Chromeleon 7.2) Anions including organic acids: Acetate, Propionate, Formate, Oxalate, Cl⁻, NO₂⁻, NO₃⁻, SO₄²⁻ Ion Exchange AG11 + AS11 (19 min) DIONEX AERS 500 Auto-Suppression Gradient mode: 90% H₂O + 10% NaOH (15 min) then 89% H₂O + 11% 100 mM NaOH (4 min) (1 mL/min) DIONEX ICS 5000+ (Chromeleon 7.2) Carbonate species Ion Exclusion ICE-ASI (15 min) No suppression Isocratic mode: 100% H₂O (1 mL/min) 5. Results of performance evaluation after optimization 5.1 Intercomparison WMO-GAW The implementation of clearly defined protocols for sensor fabrication and analytical procedures significantly improved the quality of results obtained by the Laboratoire d’Aérologie as part of the WMO-GAW intercomparison program. Performance results from the two evaluations conducted in 2017 (Study 56–2017 A and Study 57–2017 B) are presented in Fig. 10 . Overall, the results demonstrate excellent analytical performance from laboratory od Aerology under the reference 7000106 ( http://www.qasac-americas.org/ ). For the majority of samples, the "target plot" composed of green hexagons indicates that measured concentrations of major ions (calcium, magnesium, sodium, potassium, chloride, fluoride, sulfate, nitrate, and ammonium), as well as physicochemical parameters (pH, acidity, and conductivity), aligned well with reference values and fell within the accepted uncertainty range. These outcomes highlight the reliability of the analytical protocols employed, Mastery of calibration and quality assurance procedures, And the stability of sample preparation and treatment methods. This optimized workflow underscores the effectiveness of standardized processes in ensuring high reproducibility and accuracy in passive sampler performance. 5.2 Improvement of detection limits and analytical reproducibility Based on the optimization of the preparation protocol and the standardization of analytical procedures, the detection limits and reproducibility of the INDAAF passive samplers were re-evaluated using a dataset of field blanks and duplicate samplers collected between 2013 and 2017 across multiple African urban sites (Abidjan, Bamako, Dakar, Cotonou, and Yaoundé). These new performance metrics were compared with previously published values based on blanks produced between 1998 and 2007 by Adon et al.). Historically, the detection limits were 0.07 ± 0.03 ppb for HNO₃, 0.2 ± 0.1 ppb for NO₂, 0.7 ± 0.2 ppb for NH₃, 0.05 ± 0.03 ppb for SO₂, and 0.1 ± 0.1 ppb for O₃. The reproducibility (coefficient of variation between duplicates) ranged from 9.8% to 20% depending on the compound analyzed. After protocol optimization, a systematic decrease in detection limits was observed for all target gases. The new values are estimated to be approximately: 0.05 ± 0.02 ppb for HNO₃, 0.15 ± 0.07 ppb for NO₂, 0.5 ± 0.1 ppb for NH₃, 0.04 ± 0.02 ppb for SO₂, and 0.07 ± 0.05 ppb for O₃. Likewise, reproducibility improved significantly, with variability reduced to 12% for HNO₃, 7% for NO₂, 10% for NH₃, 12% for SO₂, and 8% for O₃. 5.3 Performance evaluation of INDAAF NH₃ passive samplers through co-location with ALPHA badges To assess the measurement performance of the INDAAF NH₃ passive samplers, a co-location experiment was conducted from 2015 to 2017 in Abidjan, where they were deployed simultaneously with CEH ALPHA badges considered as a reference passive sampler [ 20 ]. Figure 11 presents the linear regression plot comparing monthly NH₃ concentrations obtained from the two sampler types. The comparison between the two passive samplers shows a strong correlation, with a regression equation of Y = 0.75x + 3.28, a determination coefficient R² = 0.84, and a correlation coefficient r = 0.92. These values indicate a high degree of consistency between the INDAAF samplers and the ALPHA reference badges. The slope of 0.75 suggests that the INDAAF samplers tend to report slightly lower NH₃ concentrations compared to the reference, which is consistent with previous passive diffusion performance assessments under tropical conditions. The positive intercept (3.28 ppb) reflects a small baseline offset, likely associated with diffusion path micro-variability and environmental influences at the sampling site. Overall, the strong correlation (R = 0.92) confirms that the INDAAF passive samplers provide reliable and representative NH₃ concentration measurements suitable for long-term monitoring in West African urban environments. 6. Conclusion This study presents a standardised, optimised protocol for preparing, deploying and analysing INDAAF passive samplers for monitoring key reactive gases (NO₂, NH₃, HNO₃, O₃ and SO₂) in ambient air. By detailing every step of the workflow, from cleaning reusable components and preparing impregnated filters to handling in the field and conducting ion chromatography analyses, the protocol improves reproducibility, reduces the risk of contamination, and enhances comparability across monitoring sites. The optimised procedure enhances the reliability of passive sampling within the INDAAF network, enabling consistent long-term measurements in various climatic and urban environments where access to active monitoring instruments is often limited. Performance evaluations demonstrate clear improvements in analytical sensitivity and precision, with lower detection limits and better reproducibility across duplicate samplers. Intercomparison within the WMO-GAW framework confirms the reliability of the laboratory procedures and a co-location experiment with ALPHA NH₃ badges (R² = 0.84) validates the strong field performance of the optimised samplers. This protocol not only ensures methodological consistency, but also serves as a practical reference for laboratories, monitoring programmes and environmental agencies seeking cost-effective approaches to measuring atmospheric gases. Abbreviations DACCIWA: Dynamics-aerosol-chemistry-cloud interactions in West Africa EADN: Equatorial Africa Deposition Network INDAAF: International Network to study Deposition and Atmospheric chemistry in AFrica WMO: World Meteorological Organization GAW: Global Atmosphere Watch ALPHA: Adapted Low-cost Passive High Absorption Declarations Acknowledgements The authors wish to thank the Laboratoire d’Aérologie (CNRS – Université Toulouse III Paul Sabatier) for providing access to analytical facilities and protocols. We also acknowledge the SNO INDAAF for its continuous support in the deployment of passive samplers across African monitoring sites. Funding This work has received funding from the European Union 7th Framework Programme (FP7/2007-2013) under grant agreement no. 603502 (EU project DACCIWA: Dynamics-aerosol-chemistry-cloud interactions in West Africa). The authors would also like to acknowledge the AMRUGE-CI project (Appui à la Modernisation et à la Réforme des Universités et Grandes Ecoles de Côte d’Ivoire), which funded the research stays at the Laboratoire d’Aérologie in Toulouse. Data availability The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Author contributions JB led the fabrication of the passive samplers, coordinated their shipment to the monitoring sites, and performed the concentration calculations following laboratory analyses. JB also drafted the initial version of the manuscript. KS contributed to the field deployment of the passive samplers and participated in the review and correction of the manuscript. VY, as thesis supervisor, oversaw the research activities and contributed to the revision and editing of the manuscript. Competing interests The authors declare no competing interests. Ethics approval : not applicable Consent to participate: not applicable Consent to publish: not applicable Clinical trial number: not applicable. References Fowler D, Pilegaard K, Sutton MA, et al. Atmospheric composition change: Ecosystems–Atmosphere interactions. Atmos Environ. 2009;43:5193–267. https://doi.org/10.1016/j.atmosenv.2009.07.068 . Seinfeld JH, Pandis SN. (2016) Atmospheric chemistry and physics: from air pollution to climate change. John Wiley & Sons. FERM M, RODHE H. Measurements of Air Concentrations of SO2, NO2 and NH3 at Rural and Remote Sites in Asia. J Atmos Chem. 1997;27:17–29. https://doi.org/10.1023/A:1005816621522 . Ferm M, Svanberg P-A. Cost-efficient techniques for urban- and background measurements of SO2 and NO2. 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J Atmos Chem. 1998;30:319–43. https://doi.org/10.1023/A:1006027730377 . Hodgkins RE, Grzywacz CM, Garrell RL. (2011) An improved ion chromatography method for analysis of acetic and formic acid vapours. E-Preservation Science (e-PS) 8:74–80. Tang YS, Cape JN, Sutton MA. (2001) Development and Types of Passive Samplers for Monitoring Atmospheric NO2 and NH3 Concentrations. In: The Scientific World Journal. https://www.hindawi.com/journals/tswj/2001/396530/abs/ . Accessed 13 Oct 2017. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 30 Jan, 2026 Reviews received at journal 22 Jan, 2026 Reviews received at journal 19 Jan, 2026 Reviewers agreed at journal 14 Jan, 2026 Reviewers agreed at journal 12 Jan, 2026 Reviewers agreed at journal 17 Dec, 2025 Reviewers invited by journal 17 Nov, 2025 Editor assigned by journal 12 Nov, 2025 Submission checks completed at journal 12 Nov, 2025 First submitted to journal 09 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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14:08:51","extension":"html","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":99326,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/59dca5c1e5456eca3ed53162.html"},{"id":96818148,"identity":"0cead94a-d9e3-47e9-8d4e-0f4a61c11820","added_by":"auto","created_at":"2025-11-26 11:34:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":185573,"visible":true,"origin":"","legend":"\u003cp\u003eStructural components of the INDAAF passive sampler\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/a5455e64505e142466018a4e.png"},{"id":96818144,"identity":"fa575108-2dc2-4eb6-a47f-caabf618c31f","added_by":"auto","created_at":"2025-11-26 11:34:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":149269,"visible":true,"origin":"","legend":"\u003cp\u003eColor-coded INDAAF passive samplers used for the measurement of reactive gases (NH₃, NO₂, HNO₃, SO₂, and O₃) in ambient air. Each sampler is identified by a specific cap color to ensure clear distinction and prevent handling errors during field deployment\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/69140a263f21b0fa7036d00c.png"},{"id":96818145,"identity":"fb838ef8-9de7-448a-aa7d-a54abf02542b","added_by":"auto","created_at":"2025-11-26 11:34:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":148225,"visible":true,"origin":"","legend":"\u003cp\u003eRespectively illustrate a) the ELGA ultrapure water production system, b) the Fisher Scientific thermostated ultrasonic bath, and c) the IBERIS laminar flow hood used during the cleaning process.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/cfd376092479b3b510812fc9.png"},{"id":96918652,"identity":"1f2c257a-f9d6-41b7-aece-4338181a2da6","added_by":"auto","created_at":"2025-11-27 14:12:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":195739,"visible":true,"origin":"","legend":"\u003cp\u003ePreparation and storage of cellulose filters used in INDAAF passive samplers: (a) MEMMERT drying oven used for the 24-hour drying process at 30 °C; (b) airtight labeled boxes for storing clean and dry filters prior to impregnation\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/75a46e4ea268be1c2025d3a3.png"},{"id":96917647,"identity":"fc028475-c361-4afa-8569-6a06c755c372","added_by":"auto","created_at":"2025-11-27 14:10:19","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":102655,"visible":true,"origin":"","legend":"\u003cp\u003ePreparation of the citric acid trapping solution for NH₃ passive samplers: a) Weighing 1.000 g of citric acid on an analytical balance; b) Homogenization of the solution in a 50 mL volumetric flask using a magnetic stirrer before storage in an amber bottle\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/cc4448d1bbc3a2437f28cb38.png"},{"id":96818153,"identity":"980cda81-caae-4bad-a7af-c8def14c5cab","added_by":"auto","created_at":"2025-11-26 11:34:02","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":144418,"visible":true,"origin":"","legend":"\u003cp\u003ePreparation of the NH₃trapping solution, highlighting the weighing of 1 g citric acid, dissolution in methanol, filling to the 50 mL mark, and homogenization with a magnetic stirrer\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/31649e42a22771b557943eb0.png"},{"id":96818149,"identity":"cd8d1e2c-801f-4842-8dc1-588421f68254","added_by":"auto","created_at":"2025-11-26 11:34:02","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":164488,"visible":true,"origin":"","legend":"\u003cp\u003eMicropipettes used for the preparation and impregnation steps. (a) Eppendorf adjustable micropipettes (0.5–5 mL and 1–10 mL) used to measure and transfer trapping solutions during their preparation. (b) Micropipette (50 µL) used to deposit \u003cstrong\u003e50 µL \u003c/strong\u003eof trapping solution onto each cellulose filter during the impregnation step\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/a095916f8c6890bf86fd9ac5.png"},{"id":96919073,"identity":"08cce1d0-2f46-4a33-932d-ca900d61027e","added_by":"auto","created_at":"2025-11-27 14:13:05","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":229742,"visible":true,"origin":"","legend":"\u003cp\u003eStorage, packaging and shipment of INDAAF passive samplers, a) Storage of freshly prepared passive samplers in individual sealed Minigrip bags to avoid contamination, b) Example of a closed airtight shipping box labeled with site information (city, project, country, exposure period) and c) Open box showing the internal arrangement of samplers placed in duplicate for each gas type prior to dispatch to monitoring stations\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/7b3744fc6add578832af7b9d.png"},{"id":96917129,"identity":"362ff1b7-9634-4915-9a97-638825a97f94","added_by":"auto","created_at":"2025-11-27 14:09:17","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":221987,"visible":true,"origin":"","legend":"\u003cp\u003eField data sheet used for documenting the deployment, retrieval, and handling conditions of INDAAF passive samplers. The sheet records sampler identification, exposure dates and times, station coordinates, and mean temperature, ensuring consistent traceability and data quality across monitoring sites\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/e6516ca199b88bd26d741226.png"},{"id":96917811,"identity":"033decb2-abe6-4405-b696-e1fea5e35af7","added_by":"auto","created_at":"2025-11-27 14:10:35","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":272719,"visible":true,"origin":"","legend":"\u003cp\u003eRing diagrams showing the results of the Laboratoire d'Aérologie (LA) analytical laboratory in the last two WMO/GAW intercomparisons of 2017, based on 3 test samples\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/a1b8bef20514c1d868959576.png"},{"id":96917064,"identity":"3a7f11da-33a8-45da-a7a1-d5f6e9267b8d","added_by":"auto","created_at":"2025-11-27 14:09:13","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":74172,"visible":true,"origin":"","legend":"\u003cp\u003eLinear regression between NH₃concentrations measured by the INDAAF passive samplers and the CEH ALPHA reference badges during the co-location experiment conducted from 2015 to 2017 in (Abidjan, Côte d’Ivoire)\u003c/p\u003e","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/4e1239f0d214610ea78e6dd9.png"},{"id":97135652,"identity":"7d23cb6e-ef0b-4032-92a3-edd8c5b93ad9","added_by":"auto","created_at":"2025-12-01 09:52:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3123510,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8071359/v1/185edd23-3d02-4d28-b6c7-3115a22f84f5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eOptimization of passive sampler preparation for the detection of reactive gases (NO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, NH\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, HNO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, O\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, SO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e) in ambient air\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eReactive trace gases such as nitrogen dioxide (NO\u003csub\u003e2\u003c/sub\u003e), ammonia (NH\u003csub\u003e3\u003c/sub\u003e), sulfur dioxide (SO\u003csub\u003e2\u003c/sub\u003e), nitric acid (HNO\u003csub\u003e3\u003c/sub\u003e), and ozone (O\u003csub\u003e3\u003c/sub\u003e) play crucial roles in atmospheric chemistry by influencing air quality, nutrient deposition, and radiative forcing. Monitoring their ambient concentrations is essential for evaluating emission sources, understanding atmospheric processes, and assessing long-term environmental and health impacts [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In regions where continuous monitoring networks are scarce, particularly in tropical and subtropical Africa, passive sampling has become a reliable and affordable alternative to traditional active analysers [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Gaseous passive samplers are especially useful in distant and resource-constrained settings because they don't require electricity and rely on chemical trapping and molecular diffusion to collect gaseous species over long exposure times [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWithin the International Network for the Study of Atmospheric Deposition in Africa (INDAAF), passive samplers have been deployed since 1995 to measure major atmospheric gases across diverse African ecosystems. Based on Ferm's, (1991) pioneering design and validated under the World Meteorological Organization - Global Atmosphere Watch (WMO-GAW) standards, these samplers ensure high scientific reliability and comparability with other global networks such as the Equatorial Africa Deposition Network (EADN) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Their robustness, stability and precision under both rural and urban conditions has been demonstrated in numerous studies. Adon et al. (2010, 2013) confirmed their accuracy across humid savanna, dry savanna, and forest ecosystems, while Bahino (2018), Bahino et al. (2018) and Adon et al. (2016) validated their performance in urban settings such as Abidjan, Dakar, Bamako or Cotonou, where emission sources and pollutant gradients are more variable [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. More recently, Bahino et al. (2025), further confirmed the reliability and accuracy of INDAAF ammonia (NH₃) passive samplers under tropical urban conditions of Akouedo landfill in Abidjan [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These results reinforce the robustness of the INDAAF methodology, recognized internationally [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], while emphasizing the importance of continuous optimization in sampler fabrication, impregnation procedures, and analytical protocols to ensure consistent and high-quality data across monitoring sites.\u003c/p\u003e\u003cp\u003eThe main objective of this study is to present a comprehensive overview of the design, preparation, and field deployment of the INDAAF passive samplers, developed for monitoring key reactive gases in the atmosphere (NO\u003csub\u003e2\u003c/sub\u003e, NH\u003csub\u003e3\u003c/sub\u003e, HNO\u003csub\u003e3\u003c/sub\u003e, O\u003csub\u003e3\u003c/sub\u003e and SO\u003csub\u003e2\u003c/sub\u003e. This paper aims to standardise and optimise the production process to ensure high reproducibility, accuracy and comparability of atmospheric measurements at different monitoring sites. To this end, it documents the entire methodological workflow, from preparing impregnation solutions to assembling sensors and conditioning them in the field.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Design of INDAAF passive samplers\u003c/h2\u003e\u003cp\u003eThe INDAAF passive samplers consist of six main components which are a snap-on polythene cap, a snap-on polyhe cap with hole both with 29 mm diameter, a cellulose filter (21 mm diameter) impregnated with a selective trapping solution for each gas measured, a PVC ring, a PTFE membrane filter (25 mm, 1 \u0026micro;m pore size) that limits particle entry and reduces internal turbulence, and a stainless-steel protection grid. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrate the mains parts of a INDAAF passive sampler.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWithin the INDAAF network, four color-coded passive samplers are used to identify the target gases. The white caps are used for NH₃, the gray caps for NO₂, the black caps for HNO₃ and SO₂, and the gray-black caps are used for the O₃ samplers. This standardized color scheme ensures easy recognition, reduces handling errors, and improves consistency during both field deployment and laboratory analysis. An illustration of the INDAAF passive samplers and their corresponding color codes is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, highlighting their specific design and visual differentiation for monitoring reactive trace gases in ambient air.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Operating principle of INDAAF passive samplers\u003c/h2\u003e\u003cp\u003eAs mentioned previously, the design of the INDAAF passive gas samplers is based on the foundational work of Ferm [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Their reliability was subsequently confirmed through rigorous field evaluations by Adon et al. (2010, 2013) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These samplers operate based on two core principles that facilitate the capture and chemical fixation of reactive gases in the atmosphere.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 Molecular diffusion\u003c/h2\u003e\u003cp\u003eThis first principle relies on the physical process of molecular diffusion. It assumes that the mean concentration of the target gas in the surrounding ambient air is higher than inside the sampler. According to Fick's first law of diffusion, the gas molecules will naturally migrate from the region of higher concentration (the ambient air) to the region of lower concentration (inside the sampler). This passive diffusion process enables continuous airflow into the sampler, without the need for active pumping or an external power supply. This makes it ideal for long-term, low-maintenance monitoring campaigns in remote or resource-limited environments.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Chemical reaction mechanisms\u003c/h2\u003e\u003cp\u003eThe second principle involves a chemical reaction between diffused gas molecules and a trapping reactive agent impregnated onto a cellulose filter inside the sampler. Each reactive gas (NO₂, SO₂, HNO₃, NH₃ and O₃) reacts specifically with its respective absorbing solution to form stable ionic species that can be quantified in a laboratory, usually by ion chromatography. These chemical reactions have been demonstrated to be efficient and specific across various atmospheric conditions, ensuring the selective capture and quantitative determination of each gas [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The main trapping reactions used in INDAAF passive samplers are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eChemical reactions between reactive gases and trapping solutions\u003c/p\u003e \u003cdiv class=\"Credit\"\u003e\u003cp\u003e(adapted from Al-Ourabi, 2002)[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGas (Sampler color)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChemical reaction on filter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHNO\u003csub\u003e3\u003c/sub\u003e, SO\u003csub\u003e2\u003c/sub\u003e (Black)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{H}\\text{N}\\text{O}}_{3}\\)\u003c/span\u003e\u003c/span\u003e (g) + \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{O}\\text{H}}^{-}\\)\u003c/span\u003e\u003c/span\u003e\u0026rarr; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{N}\\text{O}}_{3}^{-}\\)\u003c/span\u003e\u003c/span\u003e + \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{H}}_{2}\\text{O}\\)\u003c/span\u003e\u003c/span\u003e ;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{S}\\text{O}}_{2}\\:\\)\u003c/span\u003e\u003c/span\u003e(g)\u0026thinsp;+\u0026thinsp;4\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{O}\\text{H}}^{-}\\)\u003c/span\u003e\u003c/span\u003e + \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{O}}_{2}\\)\u003c/span\u003e\u003c/span\u003e \u0026rarr; 2\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{H}}_{2}\\text{O}\\)\u003c/span\u003e\u003c/span\u003e + 2\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{S}\\text{O}}_{4}^{2-}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNO\u003csub\u003e2\u003c/sub\u003e (Gray)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{N}\\text{O}}_{2}\\:\\)\u003c/span\u003e\u003c/span\u003e(g)\u0026thinsp;+\u0026thinsp;3\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{I}}^{-}\\)\u003c/span\u003e\u003c/span\u003e \u0026rarr; 2\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{N}\\text{O}}_{2}^{-}\\:\\)\u003c/span\u003e\u003c/span\u003e + \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{I}}_{3}^{-}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNH\u003csub\u003e3\u003c/sub\u003e (White)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{N}\\text{H}}_{3}\\)\u003c/span\u003e\u003c/span\u003e (g) + \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{H}}^{\\mp\\:}\\)\u003c/span\u003e\u003c/span\u003e \u0026rarr; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{N}\\text{H}}_{4}^{+}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eO\u003csub\u003e3\u003c/sub\u003e (Gray-black)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{O}}_{3}\\)\u003c/span\u003e\u003c/span\u003e (g) + \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{N}\\text{O}}_{2}^{-}\\)\u003c/span\u003e\u003c/span\u003e \u0026rarr; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{N}\\text{O}}_{3}^{-}\\)\u003c/span\u003e\u003c/span\u003e+ \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{O}}_{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.2.3 Detection limits and reproducibility\u003c/h2\u003e\u003cp\u003eThe analytical performance of the INDAAF passive samplers was rigorously assessed by Adon et al. (2010), who determined the detection limits for each target gas based on the analysis of blank samplers, both those deployed in the field without exposure and those retained in the laboratory after fabrication. This approach enabled robust estimation of background contamination and analytical noise, ensuring reliable quantification thresholds. Based on a dataset of blanks produced between 1998 and 2007, the following detection limits were determined: 0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 parts per billion (ppb) for nitric acid (HNO₃), 0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 ppb for nitrogen dioxide (NO₂), 0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 ppb for ammonia (NH₃), 0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 ppb for sulphur dioxide (SO₂), and 0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 ppb for ozone (O₃). These low detection thresholds demonstrate the high sensitivity of the INDAAF passive sampling method, even under tropical atmospheric conditions where background levels can be very low.\u003c/p\u003e\u003cp\u003eThe reproducibility, as measured by the coefficient of variation between duplicate samplers, was found to be 20% for HNO₃, 9.8% for NO₂, 14.3% for NH₃, 16.6% for SO₂ and 10% for O₃. These results confirm the robustness of the INDAAF protocol for long-term atmospheric monitoring across diverse African ecosystems and indicate good analytical consistency.\u003c/p\u003e\u003cp\u003eGiven the proven sensitivity and reproducibility of INDAAF passive samplers, optimising the fabrication and preparation steps is crucial to ensure consistent performance at all monitoring sites. The sampler's configuration places particular emphasis on the quality and chemical integrity of its components, especially the cellulose filter impregnated with specific trapping solutions.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3. Optimization of INDAAF passive samplers preparation","content":"\u003cp\u003eThe INDAAF passive sampler consists of several mechanical and chemical components that can be grouped into two main categories. The first includes non-reusable elements, such as the cellulose filter (used as the reactive substrate impregnated with trapping solutions) and the PTFE (Teflon) filter. These are both replaced after each sampling period to prevent cross-contamination or chemical degradation. The second category comprises reusable components, including perforated and non-perforated plastic caps, metallic grids and PVC rings that form the sampler's structural body. To ensure subsequent measurements are reliable and reproducible, these reusable components must undergo strict cleaning and decontamination procedures before each deployment.\u003c/p\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Cleaning and handling of reusable components\u003c/h2\u003e\u003cp\u003eThe reusable parts of INDAAF passive samplers, including the plastic caps (with or without perforations), the PVC rings and the stainless-steel grids, are cleaned separately to avoid cross-contamination. All washing operations were performed using ultrapure water with a resistivity of ρ\u0026thinsp;=\u0026thinsp;18.2 MΩ\u0026middot;cm, which was produced by an ELGA purification system (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003eEach component type was placed in a crystalliser or large beaker and completely immersed in ultrapure water. The parts were rinsed twice to remove dust particles and visible residues. Once cleaned, the rinse water is replaced with ultrapure water and the crystalliser is transferred to a thermostatically controlled ultrasonic bath (Fisher Scientific), which is equipped with a programmable timer (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). The components are subjected to ultrasound for 10 minutes. The water is then changed, and the process is repeated once more to ensure the complete removal of contaminants and chemical residues. After ultrasonic cleaning, the components were rinsed twice more with ultrapure water and then dried for two hours under an IBERIS brand laminar flow hood with an air velocity of 1.2 m\u0026middot;s⁻\u0026sup1; (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). Once completely dry, all parts were stored in sterile plastic boxes to ensure full protection from airborne impurities, dust and residual moisture until further use.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Preparation of cellulose filters (cutting, cleaning, and drying)\u003c/h2\u003e\u003cp\u003eThe filters used to trap gaseous pollutants are Whatman 'ashless' cellulose filters, which are originally 90 mm in diameter. To fit the INDAAF passive samplers, 21 mm diameter circular filters are cut using a precision punch. Typically, six to seven small filters can be obtained from one 90 mm filter. After cutting, the filters are cleaned using the same procedure as for the reusable components described previously. Each batch undergoes two 10-minute ultrasonic washes in ultrapure water, followed by a third 10-minute ultrasonic bath in methanol. Protective gloves must be worn during this step, as methanol is a toxic and flammable solvent. Once washed, the filters are placed on stainless steel trays and dried for approximately two hours under a laminar flow hood to allow complete evaporation of the methanol. They are then transferred to a MEMMERT drying oven (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) and maintained at 30\u0026deg;C for 24 hours to ensure full dehydration. Finally, the clean, dry filters are stored in labelled, airtight plastic boxes with the preparation date clearly marked, to ensure traceability and quality control (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Preparation of impregnation solutions\u003c/h2\u003e\u003cp\u003eA specific chemical trapping solution is prepared for each target gas to ensure selective absorption and stable retention on the cellulose filter during exposure. These impregnation solutions are freshly prepared prior to each field campaign to prevent degradation or chemical alteration. Once prepared, the solutions are stored in tightly sealed containers under refrigeration (typically at 4\u0026deg;C) until they are shipped to the measurement sites. To maintain consistency across sampling periods, the same volumetric flask is used for each solution type throughout the study. For each filter, a small amount of the trapping solution is put onto the cellulose surface. This is usually 50 \u0026micro;L. The trapping solution is put on using special Eppendorf micropipettes that have been calibrated before (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). This controlled application ensures uniform impregnation and reproducible diffusion conditions within the passive samplers. Each solution is formulated to react with a specific reactive gas (NO₂, NH₃, SO₂, HNO₃ or O₃). The composition and preparation procedure of these trapping solutions are described in the following subsections.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1 Solution for Ammonia (NH₃) passive samplers\u003c/h2\u003e\u003cp\u003eFor ammonia (NH₃) INDAAF passive samplers, the cellulose filter used is impregnated with 50 \u0026micro;L of a citric acid solution, which serves as the chemical trapping agent. This solution enables efficient absorption of gaseous ammonia through acid-base neutralization, forming ammonium ions (NH₄⁺) that are later quantified by ion chromatography. The citric acid solution is prepared by weighing 1 g of citric acid using an analytical electronic balance (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). The weighed acid is then introduced into a 50 mL volumetric flask that already contains a small amount of methanol to aid dissolution. Methanol is subsequently added up to the calibration mark to reach the desired volume. The resulting solution is thoroughly homogenized using a magnetic stirrer (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb) to ensure complete dissolution of the solute and uniform chemical composition.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eOnce prepared, the solution is transferred to an amber storage bottle to prevent photodegradation and kept refrigerated until use. The complete preparation workflow of the citric acid trapping solution for NH₃ passive samplers is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2 Solution for Nitrogen Dioxide (NO₂) passive samplers\u003c/h2\u003e\u003cp\u003eFor nitrogen dioxide (NO₂), the INDAAF gray samplers use cellulose filters impregnated with 50 \u0026micro;L of an alkaline solution composed of sodium hydroxide (NaOH) and sodium iodide (NaI). This chemical mixture facilitates the quantitative trapping of NO₂ through the formation of nitrite (NO₂⁻) and triiodide (I₃⁻) ions via redox reactions occurring on the filter surface. The trapping solution is prepared by accurately weighing 0.44 g of NaOH pellets and 3.95 g of NaI crystals using an analytical balance. Both reagents are then dissolved in 50 mL of methanol within a calibrated volumetric flask. Methanol is selected as the solvent for its ability to enhance solubility and ensure a uniform coating on the filter surface. The mixture is subsequently homogenized with a magnetic stirrer to obtain a clear and stable solution.\u003c/p\u003e\u003cp\u003eBefore impregnation, the pH of the solution is checked using a pH meter to confirm strong alkalinity (pH\u0026thinsp;\u0026gt;\u0026thinsp;12), which is essential to guarantee complete conversion of NO₂ to its ionic products during exposure. The solution is then stored in an airtight, light-protected bottle and kept refrigerated until application.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e3.3.3 Solution for Sulfur Dioxide (SO₂) and Nitric Acid (HNO₃) passive samplers\u003c/h2\u003e\u003cp\u003eThe black INDAAF passive samplers are designed to trap acidic gases such as sulfur dioxide (SO₂) and nitric acid (HNO₃) through neutralization reactions on an alkaline cellulose filter. Each filter is impregnated with 50 \u0026micro;L of a sodium hydroxide (NaOH) solution, which serves as the trapping medium by converting these reactive gases into their corresponding anions (SO₄\u0026sup2;⁻ and NO₃⁻).\u003c/p\u003e\u003cp\u003eTo prepare this solution, 0.5 g of NaOH pellets is carefully weighed using an analytical balance and dissolved in a few milliliters of deionized water to initiate solubilization. The mixture is then quantitatively transferred into a 50 mL volumetric flask, which is filled to the calibration mark with methanol. Methanol is used as a solvent to ensure uniform impregnation of the cellulose filter and to facilitate rapid drying.\u003c/p\u003e\u003cp\u003eThe resulting solution is thoroughly homogenized using a magnetic stirrer to obtain a clear and stable mixture. Before use, the pH is verified with a calibrated pH meter, ensuring that it remains above 12. This strong alkalinity is critical for the efficient absorption and neutralization of acidic gases during exposure.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.3.4 Solution for Ozone (O₃) passive samplers\u003c/h2\u003e\u003cp\u003eFor ozone measurements, the cellulose filter is impregnated with 50 \u0026micro;L of a trapping solution specifically designed to promote the oxidation of nitrite during exposure. The solution is prepared by weighing 0.25 g of sodium nitrite (NaNO₂) and 0.25 g of potassium carbonate (K₂CO₃), which are then introduced into a 50 mL volumetric flask containing a small volume of deionized water. Using a sterile disposable syringe, 0.5 mL of bidistilled glycerol is added to the mixture to enhance filter wetting and stabilize the impregnating solution during drying and storage. The volumetric flask is then filled to the 50 mL mark with ultrapure water. Finally, the solution is homogenized using a magnetic stirrer to ensure complete dissolution of the reagents and uniform distribution of the impregnating agents.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Impregnation of cellulose filters\u003c/h2\u003e\u003cp\u003eAll trapping solutions used for the INDAAF passive samplers are freshly prepared and stored in a refrigerator until deployment in the field. Prior to impregnation, each cellulose filter is placed inside the lower (closed) plastic cap of the sampler. Using a calibrated Eppendorf micropipette, a precise volume of 50 \u0026micro;L of the corresponding trapping solution is carefully deposited onto the center of the filter to ensure uniform wetting (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). This operation is carried out under a laminar flow hood to promote the controlled evaporation of methanol contained in the solution and to avoid contamination from ambient air. After impregnation, the filters are allowed to dry under the hood for approximately 30 minutes, until the solvent has fully evaporated and the reactive compounds are fully adsorbed onto the cellulose matrix. Once dry, the impregnated filters are immediately assembled with the remaining sampler components or stored in sterile, airtight containers to protect them from moisture and accidental exposure before field deployment.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Assembly and packaging of INDAAF passive samplers","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Assembly of INDAAF Passive samplers\u003c/h2\u003e\u003cp\u003eThe assembly of the passive samplers is carried out under clean laboratory conditions, using gloves and fine-tipped forceps to avoid contamination. Each sampler consists of six components (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The impregnated cellulose filter is first placed inside the closed bottom cap. This cap is then fitted to the PVC ring. A PTFE (Teflon) membrane filter is carefully placed on top of the PVC ring using forceps, followed by the stainless-steel mesh grid. The assembly is then completed by securing the perforated top cap, which allows ambient air to diffuse into the sampler.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Packaging and storage of INDAAF passive sampler\u003c/h2\u003e\u003cp\u003eOnce assembled, samplers are individually placed in labeled Minigrip\u0026reg; plastic bags and stored separately according to gas type to prevent handling confusion. Prior to field deployment, the individual sampler bags are transferred into clean, airtight plastic containers for shipment. Each container holds eight samplers, arranged as two samplers of each type (white for NH₃, gray for NO₂, black for SO₂/HNO₃, and gray-black for O₃). For NH₃ samplers, an additional sealed bottom cap is included in each bag to protect the filter before exposure.\u003c/p\u003e\u003cp\u003eControl (blank) samplers are also prepared. These are stored in sealed containers and are either kept in the laboratory or shipped to the measurement sites without being exposed. Blank samplers are essential for determining background contamination and calculating detection limits. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows examples of packaged samplers stored in shipping containers.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e.\u003c/p\u003e\u003cp\u003eEach container is labeled with the station name, city, country, and the planned exposure period (e.g., 2-week or monthly intervals). A field log sheet is included inside each container to record deployment and retrieval dates, and to document the mean ambient temperature, which is required to calculate atmospheric gas concentrations. An example of the field data sheet used for documenting the deployment, retrieval, and handling conditions of INDAAF passive samplers is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Passive sampler shipment, deployment, and laboratory analysis\u003c/h2\u003e\u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\u003ch2\u003e4.3.1 Shipment and field sampling protocol\u003c/h2\u003e\u003cp\u003eThe prepared sampler boxes are sent to field sites using a rapid shipping service to minimize changes in humidity and temperature during transport. Upon arrival, field technicians follow standardized INDAAF operating procedures for installation, exposure, and return shipment. Upon reception at the deployment site, the passive samplers were stored in a refrigerator to prevent contamination or premature chemical reactions before exposure. At the beginning of each sampling period, two passive samplers of each gas type were mounted in duplicate on stainless-steel mounting rails, positioned at a height between 1.5 and 2.5 m above ground level, in accordance with atmospheric measurement standards to avoid direct ground influence and ensure representative ambient concentrations. To ensure consistent temporal coverage, each month was divided into two exposure periods of approximately 15 days:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eFirst exposure period: from the 1st day of the month to the morning of the 16th.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSecond exposure period: from the 16th of the month to the 1st day of the following month.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eAt the end of each 15-day exposure, the deployed samplers were removed, immediately sealed in their individual storage bags, and placed back into a refrigerator to minimize post-exposure alteration. The next set of samplers was then installed to begin the following exposure period. Finally, all collected samplers were returned to the Laboratory of Aerology (Toulouse, France) for chemical extraction and analysis by ion chromatography (IC). All the sampling procedure is well described in bahino et al 2018.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\u003ch2\u003e4.3.2 Deployment of passive samplers\u003c/h2\u003e\u003cp\u003eFrom September 2013 to April 2017, a total of 5026 passive gas samplers were manufactured at the Aerology Laboratory and distributed to monitoring sites in several major African cities, including Bamako, Abidjan, Cotonou, Dakar, and Yaound\u0026eacute;. After the exposure period, all samplers were systematically returned to the laboratory for post-exposure conditioning and chemical analysis. A summary of the number of samplers manufactured, deployed, and analyzed is provided in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOverview of urban air quality monitoring campaigns using passive samplers in West and Central Africa, including sampling locations, exposure periods, and number of analyses (2013\u0026ndash;2017).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeasurement Campaign\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMeasurement Site\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSampling Period\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber of Analyses\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eMedium-term measurements\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbidjan domestic fires\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eJanuary 2015 - March 2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e540\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbidjan traffic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecember 2014 - April 2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e550\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbidjan landfill fires\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecember 2014 - March 2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e540\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCotonou traffic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecember 2014 - March 2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e580\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBamako traffic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSeptember 2013 - March 2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e850\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYaound\u0026eacute; traffic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSeptember 2013 - January 2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e680\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eIntensive campaigns\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbidjan spatial monitoring 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecember 2015 - February 2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e760\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbidjan spatial monitoring 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecember 2016 - February 2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e800\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCotonou spatial monitoring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDecember 2016 - February 2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e320\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e5620\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003e4.3.3. Chemical analysis of INDAAF passive samplers\u003c/h2\u003e\u003cp\u003eThe Laboratory of Aerology (Toulouse, France) hosts a dedicated chromatography platform equipped with several Thermo Dionex ion chromatography (IC) systems (ICS-1000, ICS-1100, ICS-5000, and DX-500), allowing high-precision quantification of the ionic products formed on the impregnated filters. Each gaseous species is quantified indirectly through the ionic form resulting from its reaction with the trapping solution: ammonia (NH₃) is determined as ammonium (NH₄⁺), nitric acid (HNO₃) and ozone (O₃) are quantified as nitrate (NO₃⁻), sulfur dioxide (SO₂) as sulfate (SO₄\u0026sup2;⁻), and nitrogen dioxide (NO₂) as nitrite (NO₂⁻). All IC systems were equipped with autosamplers, enabling continuous analytical sequences and reducing manual handling variability. Chromatographic data were processed using Chromeleon software, ensuring consistent peak identification, integration, and rigorous quality control. The ion chromatography analytical system used in this study has been extensively described in previous publications [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of ion chromatography systems and analytical configurations used at the Aerology Laboratory, including detected species, analytical columns, suppression systems, eluent compositions, and flow rates.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInstrument System (Software)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnalyzed Species\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAnalytical Columns (4 mm)\u003c/p\u003e\u003cp\u003e(Analysis Time)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSuppression System\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEluent Composition (Flow Rate)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDIONEX ICS 1100\u0026thinsp;+\u0026thinsp;AS50 Autosampler (Chromeleon 6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCations: Na⁺, NH₄⁺, K⁺, Mg\u0026sup2;⁺, Ca\u0026sup2;⁺, Li⁺, Mn\u0026sup2;⁺\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIon Exchange CG12A\u0026thinsp;+\u0026thinsp;CS12A\u003c/p\u003e\u003cp\u003e(14 min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDIONEX CERS 500 Auto-Suppression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIsocratic mode: 20 mM Methanesulfonic acid (MSA) (1 mL/min)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDIONEX ICS 1000\u0026thinsp;+\u0026thinsp;AS40 Autosampler (Chromeleon 6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInorganic anions: Cl⁻, NO₂⁻, NO₃⁻, PO₄\u0026sup3;⁻, SO₄\u0026sup2;⁻\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIon Exchange AG4A-SC\u0026thinsp;+\u0026thinsp;AS4A-SC\u003c/p\u003e\u003cp\u003e(14 min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDIONEX AERS 500 Auto-Suppression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIsocratic mode: 1.8 mM CO₃\u0026sup2;⁻ / 1.7 mM HCO₃⁻ (2 mL/min)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDIONEX ICS 5000+ (Chromeleon 7.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnions including organic acids: Acetate, Propionate, Formate, Oxalate, Cl⁻, NO₂⁻, NO₃⁻, SO₄\u0026sup2;⁻\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIon Exchange AG11\u0026thinsp;+\u0026thinsp;AS11 (19 min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDIONEX AERS 500 Auto-Suppression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGradient mode: 90% H₂O\u0026thinsp;+\u0026thinsp;10% NaOH (15 min) then 89% H₂O\u0026thinsp;+\u0026thinsp;11% 100 mM NaOH (4 min) (1 mL/min)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDIONEX ICS 5000+ (Chromeleon 7.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCarbonate species\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIon Exclusion ICE-ASI\u003c/p\u003e\u003cp\u003e(15 min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo suppression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIsocratic mode: 100% H₂O (1 mL/min)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"5. Results of performance evaluation after optimization","content":"\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\u003ch2\u003e5.1 Intercomparison WMO-GAW\u003c/h2\u003e\u003cp\u003eThe implementation of clearly defined protocols for sensor fabrication and analytical procedures significantly improved the quality of results obtained by the Laboratoire d\u0026rsquo;A\u0026eacute;rologie as part of the WMO-GAW intercomparison program. Performance results from the two evaluations conducted in 2017 (Study 56\u0026ndash;2017 A and Study 57\u0026ndash;2017 B) are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e. Overall, the results demonstrate excellent analytical performance from laboratory od Aerology under the reference 7000106 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.qasac-americas.org/\u003c/span\u003e\u003cspan address=\"http://www.qasac-americas.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). For the majority of samples, the \"target plot\" composed of green hexagons indicates that measured concentrations of major ions (calcium, magnesium, sodium, potassium, chloride, fluoride, sulfate, nitrate, and ammonium), as well as physicochemical parameters (pH, acidity, and conductivity), aligned well with reference values and fell within the accepted uncertainty range. These outcomes highlight the reliability of the analytical protocols employed, Mastery of calibration and quality assurance procedures, And the stability of sample preparation and treatment methods. This optimized workflow underscores the effectiveness of standardized processes in ensuring high reproducibility and accuracy in passive sampler performance.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003e5.2 Improvement of detection limits and analytical reproducibility\u003c/h2\u003e\u003cp\u003eBased on the optimization of the preparation protocol and the standardization of analytical procedures, the detection limits and reproducibility of the INDAAF passive samplers were re-evaluated using a dataset of field blanks and duplicate samplers collected between 2013 and 2017 across multiple African urban sites (Abidjan, Bamako, Dakar, Cotonou, and Yaound\u0026eacute;). These new performance metrics were compared with previously published values based on blanks produced between 1998 and 2007 by Adon et al.). Historically, the detection limits were 0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 ppb for HNO₃, 0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 ppb for NO₂, 0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 ppb for NH₃, 0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 ppb for SO₂, and 0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 ppb for O₃. The reproducibility (coefficient of variation between duplicates) ranged from 9.8% to 20% depending on the compound analyzed. After protocol optimization, a systematic decrease in detection limits was observed for all target gases. The new values are estimated to be approximately: 0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 ppb for HNO₃, 0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 ppb for NO₂, 0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 ppb for NH₃, 0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 ppb for SO₂, and 0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 ppb for O₃. Likewise, reproducibility improved significantly, with variability reduced to 12% for HNO₃, 7% for NO₂, 10% for NH₃, 12% for SO₂, and 8% for O₃.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\u003ch2\u003e5.3 Performance evaluation of INDAAF NH₃ passive samplers through co-location with ALPHA badges\u003c/h2\u003e\u003cp\u003eTo assess the measurement performance of the INDAAF NH₃ passive samplers, a co-location experiment was conducted from 2015 to 2017 in Abidjan, where they were deployed simultaneously with CEH ALPHA badges considered as a reference passive sampler [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e presents the linear regression plot comparing monthly NH₃ concentrations obtained from the two sampler types.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe comparison between the two passive samplers shows a strong correlation, with a regression equation of Y\u0026thinsp;=\u0026thinsp;0.75x\u0026thinsp;+\u0026thinsp;3.28, a determination coefficient R\u0026sup2; = 0.84, and a correlation coefficient r\u0026thinsp;=\u0026thinsp;0.92. These values indicate a high degree of consistency between the INDAAF samplers and the ALPHA reference badges. The slope of 0.75 suggests that the INDAAF samplers tend to report slightly lower NH₃ concentrations compared to the reference, which is consistent with previous passive diffusion performance assessments under tropical conditions. The positive intercept (3.28 ppb) reflects a small baseline offset, likely associated with diffusion path micro-variability and environmental influences at the sampling site. Overall, the strong correlation (R\u0026thinsp;=\u0026thinsp;0.92) confirms that the INDAAF passive samplers provide reliable and representative NH₃ concentration measurements suitable for long-term monitoring in West African urban environments.\u003c/p\u003e\u003c/div\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis study presents a standardised, optimised protocol for preparing, deploying and analysing INDAAF passive samplers for monitoring key reactive gases (NO₂, NH₃, HNO₃, O₃ and SO₂) in ambient air. By detailing every step of the workflow, from cleaning reusable components and preparing impregnated filters to handling in the field and conducting ion chromatography analyses, the protocol improves reproducibility, reduces the risk of contamination, and enhances comparability across monitoring sites.\u003c/p\u003e\u003cp\u003eThe optimised procedure enhances the reliability of passive sampling within the INDAAF network, enabling consistent long-term measurements in various climatic and urban environments where access to active monitoring instruments is often limited. Performance evaluations demonstrate clear improvements in analytical sensitivity and precision, with lower detection limits and better reproducibility across duplicate samplers. Intercomparison within the WMO-GAW framework confirms the reliability of the laboratory procedures and a co-location experiment with ALPHA NH₃ badges (R\u0026sup2; = 0.84) validates the strong field performance of the optimised samplers. This protocol not only ensures methodological consistency, but also serves as a practical reference for laboratories, monitoring programmes and environmental agencies seeking cost-effective approaches to measuring atmospheric gases.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDACCIWA: Dynamics-aerosol-chemistry-cloud interactions in West Africa\u003c/p\u003e\n\u003cp\u003eEADN: Equatorial Africa Deposition Network\u003c/p\u003e\n\u003cp\u003eINDAAF: International Network to study Deposition and Atmospheric chemistry in AFrica\u003c/p\u003e\n\u003cp\u003eWMO: World Meteorological Organization\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGAW: Global Atmosphere Watch\u003c/p\u003e\n\u003cp\u003eALPHA: Adapted Low-cost Passive High Absorption\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank the Laboratoire d\u0026rsquo;A\u0026eacute;rologie (CNRS \u0026ndash; Universit\u0026eacute; Toulouse III Paul Sabatier) for providing access to analytical facilities and protocols. We also acknowledge the SNO INDAAF for its continuous support in the deployment of passive samplers across African monitoring sites.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work has received funding from the European Union 7th Framework Programme (FP7/2007-2013) under grant agreement no. 603502 (EU project DACCIWA: Dynamics-aerosol-chemistry-cloud interactions in West Africa).\u003c/p\u003e\n\u003cp\u003eThe authors would also like to acknowledge the AMRUGE-CI project (Appui \u0026agrave; la Modernisation et \u0026agrave; la R\u0026eacute;forme des Universit\u0026eacute;s et Grandes Ecoles de C\u0026ocirc;te d\u0026rsquo;Ivoire), which funded the research stays at the Laboratoire d\u0026rsquo;A\u0026eacute;rologie in Toulouse.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJB led the fabrication of the passive samplers, coordinated their shipment to the monitoring sites, and performed the concentration calculations following laboratory analyses. JB also drafted the initial version of the manuscript. KS contributed to the field deployment of the passive samplers and participated in the review and correction of the manuscript. VY, as thesis supervisor, oversaw the research activities and contributed to the revision and editing of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval :\u003c/strong\u003e not applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u003c/strong\u003e not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish:\u003c/strong\u003e not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFowler D, Pilegaard K, Sutton MA, et al. Atmospheric composition change: Ecosystems\u0026ndash;Atmosphere interactions. 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Accessed 13 Oct 2017.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-sensors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Sensors](https://link.springer.com/journal/44397)","snPcode":"44397","submissionUrl":"https://submission.nature.com/new-submission/44397/3","title":"Discover Sensors","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"passive sampler, ammonia, nitrogen dioxide, ozone, ion chromatography, INDAAF, air pollution, Africa","lastPublishedDoi":"10.21203/rs.3.rs-8071359/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8071359/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study conducted within the European DACCIWA FP7 program (2014–2017), presents an optimized protocol for the preparation, deployment, and laboratory analysis of International Network to study Deposition and Atmospheric chemistry in Africa (INDAAF) passive samplers used to monitor reactive gases (NO\u003csub\u003e2\u003c/sub\u003e, NH\u003csub\u003e3\u003c/sub\u003e, HNO\u003csub\u003e3\u003c/sub\u003e, O\u003csub\u003e3\u003c/sub\u003e, SO\u003csub\u003e2\u003c/sub\u003e)\u003cstrong\u003e \u003c/strong\u003ein ambient air. The updated procedure improves the cleaning of reusable components, the preparation of impregnation solutions, the controlled drying and storage of filters, and the standardization of field handling and ion chromatography analysis. From 2013 to 2017, a total of 5026 passive samplers were produced and deployed across urban monitoring sites in West and Central Africa. The protocol optimization led to a systematic enhancement in analytical performance. Detection limits were reduced to approximately 0.05 ± 0.02 ppb for HNO\u003csub\u003e3\u003c/sub\u003e, 0.15 ± 0.07 ppb for NO\u003csub\u003e2\u003c/sub\u003e, 0.5 ± 0.1 ppb for NH\u003csub\u003e3\u003c/sub\u003e, 0.04 ± 0.02 ppb for SO\u003csub\u003e2\u003c/sub\u003e, and 0.07 ± 0.05 ppb for O\u003csub\u003e3\u003c/sub\u003e. Reproducibility also improved, reaching 12% for HNO\u003csub\u003e3\u003c/sub\u003e, 7% for NO\u003csub\u003e2\u003c/sub\u003e, 10% for NH\u003csub\u003e3\u003c/sub\u003e, 12% for SO\u003csub\u003e2\u003c/sub\u003e, and 8% for O\u003csub\u003e3\u003c/sub\u003e, indicating greater measurement stability and consistency. Performance evaluation based on co-located NH\u003csub\u003e3\u003c/sub\u003e measurements using INDAAF samplers and CEH ALPHA reference badges showed strong agreement (R² = 0.84), confirming the reliability of the optimized method under real field conditions.\u003c/p\u003e","manuscriptTitle":"Optimization of passive sampler preparation for the detection of reactive gases (NO2, NH3, HNO3, O3, SO2) in ambient air","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-26 11:33:57","doi":"10.21203/rs.3.rs-8071359/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-30T11:16:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-22T10:18:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-19T14:32:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"120572040746793080993655272257733792243","date":"2026-01-14T14:38:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"145199562240461511301872676354724939091","date":"2026-01-13T01:00:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33403610529642636904641877231270135870","date":"2025-12-17T14:30:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-18T04:26:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-12T06:44:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-12T06:43:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Sensors","date":"2025-11-09T22:16:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-sensors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Sensors](https://link.springer.com/journal/44397)","snPcode":"44397","submissionUrl":"https://submission.nature.com/new-submission/44397/3","title":"Discover Sensors","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"066a86bf-4260-497d-af0f-9c440009f1c1","owner":[],"postedDate":"November 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-13T05:38:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-26 11:33:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8071359","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8071359","identity":"rs-8071359","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}