Jaime Gómez-Suárez

Patricia Arroyo

María Cerrato-Álvarez

Esther Hontañón

Sergio Masa

Philippe Menini

Lionel Presmanes

Raimundo Alfonso

Eduardo Pinilla-Gil

Jesús Lozano
email: jesuslozano@unex.es

Jaime Gómez-Suár

Esther Hontañ

Development and Field Validation of Low-Cost Metal Oxide Nanosensors for Tropospheric Ozone Monitoring in Rural Areas

Keywords: metal-oxide sensor, tin oxide nanofibers, graphene, air pollution, machine learning

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Tropospheric ozone, also referred to as ground-level or surface ozone (hereinafter ozone), is a secondary air pollutant that results from a complex set of chemical processes involving precursor gases, namely methane (CH 4 ), carbon monoxide (CO), and volatile organic compounds (VOCs), both of natural and anthropogenic origin, in the presence of nitrogen oxides (NO x ) and sunlight [START_REF] Warneck | Ozone in the trophosphere[END_REF]. Ozone has negative effects on human health [START_REF] Agrawal | Tropospheric Ozone: A Hazard for Vegetation and Human Health[END_REF][START_REF] Ryffel | Ozone Pollution: A Major Health Hazard Worldwide[END_REF][START_REF]Health Risks of Ozone from Long-Range Transboundary Air Pollution; WHO Regional Office for Europe[END_REF] and is the second most harmful pollutant (after particulate matter) in terms of human mortality and morbidity [START_REF] Nuvolone | The effects of ozone on human health[END_REF][START_REF] Malley | Updated Global Estimates of Respiratory Mortality in Adults ≥30 Years of Age Attributable to Long-Term Ozone Exposure[END_REF]. In addition, ozone is hazardous to sensitive vegetation such as forests, crops, and grasslands [START_REF] Agrawal | Tropospheric Ozone: A Hazard for Vegetation and Human Health[END_REF][START_REF] Grulke | Ozone effects on plants in natural ecosystems[END_REF][START_REF] Emberson | Effects of ozone on agriculture, forests and grasslands[END_REF][START_REF] Jakovljević | Impact of ground-level ozone on Mediterranean forest ecosystems health[END_REF][START_REF] Wang | Reductions in crop yields across China from elevated ozone[END_REF][START_REF] Sharps | Ozone-induced effects on leaves in African crop species[END_REF][START_REF] Dolker | Negative impacts of elevated ozone on dominant species of semi-natural grassland vegetation in Indo-Gangetic plain[END_REF] and is a greenhouse gas that contributes to climate change [START_REF] Ainsworth | The Effects of Tropospheric Ozone on Net Primary Productivity and Implications for Climate Change[END_REF][START_REF] Shindell | Role of tropospheric ozone increases in 20th-century climate change[END_REF]. The World Health Organization (WHO) has established a limit value of 100 µg•m -3 for the Maximum Daily 8 h Averaged (MDA8) concentration of ozone for the protection of human health, never to be exceeded [START_REF]WHO Global Air Quality Guidelines: Particulate Matter (PM2.5 and PM10), Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide[END_REF]. The European air quality directive 2008/50/EC [START_REF] Karpus | Implementation of directive 2008/50/EC of 21 May 2008 on Ambient Air Quality and Cleaner Air for Europe in Polish environmental law[END_REF] is less restrictive as it sets a target value of 120 µg•m -3 for the MDA8 concentration of ozone for the protection of human health, which can be exceeded up to 25 days per year averaged over 3 years. For protecting vegetation, the European directive uses the Accumulated Ozone over Threshold of 40 ppb (AOT40) metrics, which is the sum of hourly exceedances above 40 ppb (80 µg•m -3 ) over the daylight hours during the growing season, and sets a target value of 18,000 µg•m -3 •h and a long-term objective of 6000 µg •m -3 •h for 5 years averaged AOT40. The Europe-averaged AOT40 showed a declining trend in the period of 2000-2014 [START_REF] Cooper | Global distribution and trends of tropospheric ozone: An observation-based review[END_REF], which is attributed to the successful strategies to reduce ozone precursor emissions that have been put in place in Europe since the 1990s [START_REF] Proietti | Trends in tropospheric ozone concentrations and forest impact metrics in Europe over the time period 2000-2014[END_REF]. However, ozone trends differ largely between regions in Europe depending on aspects such as the location, population density, economic activity, orography, climate, and meteorology of the zone under study [START_REF]Air Quality in Europe-2020 Report[END_REF][START_REF] Viana | Ozone in Southern Europe-Assessment and Effectiveness of Measures[END_REF][START_REF] Querol | -2012 trends on air quality in Spain[END_REF][START_REF] García | Analysis of ozone concentrations between 2002-2020 in urban air in Northern Spain[END_REF][START_REF] Adame | Surface ozone trends over a 21-year period at El Arenosillo observatory (Southwestern Europe)[END_REF]. In 2019, [START_REF] Viana | Ozone in Southern Europe-Assessment and Effectiveness of Measures[END_REF] European countries (from a total of 32 reporting states based on 1665 air quality stations) registered ozone concentrations above the target value for the protection of health set by the European directive more than 25 times, and almost all rural background stations recorded ozone concentrations in excess of the limit recommended by the WHO [START_REF]Air Quality in Europe-2020 Report[END_REF]. It is well known that southwestern European countries are particularly exposed to exceedances of the ozone target value in summer due to the frequent anticyclones and clear-sky conditions, favoring photochemical ozone formation in the troposphere; the long-range transport of pollution from Europe, Asia, and even North America; and the own emission of ozone precursors from large urban agglomerations [START_REF] Pay | Ozone source apportionment during peak summer events over southwestern Europe[END_REF][START_REF] Cristofanelli | Background ozone in the southern Europe and Mediterranean area: Influence of the transport processes[END_REF]. This explains the growing interest in air quality monitoring systems as distributed and localized monitoring of air pollution is crucial to determine the sources and causes of pollution and, hence, to provide solutions.

The standardized analyzers currently used for the monitoring of air quality for regulatory purposes are sophisticated pieces of equipment that are operated in thermally conditioned weatherproof cabins. The high acquisition, operational, and maintenance costs of the analyzers severely limit their massive deployment. As an example, the air quality network in Spain consists of around 4000 analyzers (for the monitoring of all regulated air pollutants) installed in about 600 stations distributed over an area of 506,000 km 2 . There is a need for reliable and accurate air quality data of higher temporal and spatial resolution and representativeness than the official air quality networks, to efficiently control pollutant emissions [START_REF] Maiheu | Assessing the Spatial Representativeness of Air Quality Sampling Points-Literature Review[END_REF][START_REF] Galán-Madruga | Chapter 3: Importance of Air Quality Networks in Controlling Exposure to Air Pollution[END_REF]. To this aim, the number of commercial products and research prototypes for atmospheric surveillance that rely on low-cost sensors and are easy to deploy in the field has multiplied in recent years, thanks to advanced manufacturing technologies that allow for a high level of integration of miniaturized sensors in ever smaller, lighter, and more simplified devices [START_REF] Castell | Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates?[END_REF][START_REF] Liu | Low-cost sensors as an alternative for long-term air quality monitoring[END_REF][START_REF] Karagulian | Review of the Performance of Low-Cost Sensors for Air Quality Monitoring[END_REF]. These are paving the way for environmental monitoring through Wireless Sensor Networks (WSNs) and Internet of Things (IoT) devices capable of processing the data gathered by the WSN and transmitting them over long distances [START_REF] Majid | Applications of Wireless Sensor Networks and Internet of Things Frameworks in the Industry Revolution 4.0: A Systematic Literature Review[END_REF]. However, there are still many concerns about the quality assurance of air pollution data obtained by using low-cost sensors, especially from the regulatory bodies [START_REF] Clements | Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary)[END_REF][START_REF] Williams | Low Cost Sensor Networks: How Do We Know the Data Are Reliable? ACS Sens[END_REF][START_REF] Lewis | Validate personal air-pollution sensors[END_REF].

Among the variety of sensor technologies for the detection of gas pollutants on the market, resistive sensors based on gas-sensitive layers of metal-oxide semiconductors (MOS) are the ones that are receiving the most attention [35]. The resistance of the pre-heated MOS layer varies depending on the concentration of the target gas in the air, generating a proportional current flow in the circuit. The pros and cons of the MOS sensors compared to their main competitors in the market, the electrochemical sensors, have been widely discussed [START_REF] Narayana | Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art[END_REF]. The inherent advantages of the MOS sensors are its ability to work at high temperature while maintaining a longer service life compared to other types of gas sensors (e.g., electrochemical sensors); its high sensitivity and fast response; its low cost, capability for large-scale manufacturing, and potential for miniaturization (e.g., sensors based on Micro-Electro-Mechanical Systems or MEMS sensors) and integration into IoT devices, smart gadgets, and wearable and mobile consumer devices [START_REF] Gomes | IoT-Enabled Gas Sensors: Technologies, Applications, and Opportunities[END_REF][START_REF] Rüffer | New Digital Metal-Oxide (MOx) Sensor Platform[END_REF]. Its major drawbacks are the need to heat the MOS layer, requiring a relatively high operating power; the crosssensitivity to ambient temperature and humidity, and to gases other than the target gas present in the air; and the loss of sensitivity of the MOS surface over time [START_REF] Ji | Gas sensing mechanisms of metal oxide semiconductors: A focus review[END_REF][START_REF] Kamarudin | Cross-sensitivity of metal oxide gas sensor to ambient temperature and humidity: Effects on gas distribution mapping[END_REF][START_REF] Wang | Metal Oxide Gas Sensors: Sensitivity and Influencing Factors[END_REF]. Intensive research is being conducted on MOS nanomaterials of all dimensionalities and of tailored surface properties (e.g., composition, micro/nanostructure, and porosity) with the aim of improving the low-temperature sensing performance (e.g., limit of detection, sensitivity, and selectivity toward specific gases, response, and recovery times) of the MOS sensors [START_REF] Isaac | Metal oxide semiconducting nanomaterials for air quality gas sensors: Operating principles, performance, and synthesis techniques[END_REF][START_REF] Liu | Semiconductor Gas Sensor for Triethylamine Detection[END_REF][START_REF] Xue | Improving Gas-Sensing Performance Based on MOS Nanomaterials: A Review[END_REF][START_REF] Fazio | Metal-Oxide Based Nanomaterials: Synthesis, Characterization and their Applications in Electrical and Electrochemical Sensors[END_REF][START_REF] Li | Advances in designs and mechanisms of semiconducting metal oxide nanostructures for high-precision gas sensors operated at room temperature[END_REF][START_REF] Rickerby | Chapter 21: Nanostructured Metal Oxides for Sensing Toxic Air Pollutants[END_REF][START_REF] Masuda | Recent advances in SnO 2 nanostructure based gas sensors[END_REF][START_REF] Que | Progress in ZnO Nanosensors[END_REF]. Ideally, they should work at room temperature and have zero power consumption, which will enable its large-scale deployment in WSNs for air quality applications [START_REF] Yi | A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems[END_REF]. MOS sensors are widely used for measuring ozone in air [START_REF] Ando | Development of Technologies for Sensing Ozone in Ambient Air[END_REF]. Generally, commercial ozone sensors use thick or thin films of tungsten oxide (WO 3 ), indium and tin oxide (ITO), and other oxides, which are deposited by sputtering, and the power consumption ranges from 40 to 400 mW [START_REF] Sironi | Evaluation of Metal Oxides Sensors for the Monitoring of O 3 in Ambient Air at Ppb Level[END_REF][START_REF] Spinelle | Field calibration of a cluster of low-cost available sensors for air quality monitoring. Part A: Ozone and nitrogen dioxide[END_REF][START_REF] Williams | Validation of low-cost ozone measurement instruments suitable for use in an air-quality monitoring network[END_REF][START_REF] Peterson | Practical Use of Metal Oxide Semiconductor Gas Sensors for Measuring Nitrogen Dioxide and Ozone in Urban Environments[END_REF]. In addition, engineered functional nanomaterials obtained by mixing, doping, or surface-decoration of MOS with other oxides, noble metal nanoparticles, or carbon nanomaterials have been demonstrated for sensing ozone in the laboratory [START_REF] Gautam | Nanostructured metal oxide semiconductorbased sensors for greenhouse gas detection: Progress and challenges[END_REF].

In this work, self-developed microsensors using nanostructured gas-sensitive layers of two types: thin films of zinc oxide doped with gallium (ZnO:Ga), and nanofibrous layers of tin dioxide, pure (SnO 2 ), and doped with graphene (SnO 2 :G), were used for real-time measurement of ozone in ambient air in a rural area in southwestern Europe (Monfragüe natural park, Spain). For this purpose, automated multisensor devices were designed and fabricated: one device for each of the two types of MOS microsensors under study, and one more device for a set of commercial MOS sensors commonly used in air quality applications.

Materials and Methods

Metal Oxide Gas Sensors

The air pollutant sensors used in this work were electrically transduced sensors of the resistive type with MOS as the gas-sensitive material. Both commercial sensors and home-made sensor prototypes, the latter including nanostructured MOS layers, were used here to monitor ozone in the air in a natural park.

Commercial Sensors

A total of eight commercial sensors of models MiCS 2714, 4514, and 6814 (SGX Sen-sorTech Ltd., Corcelles-Cormondreche, Switzerland) and SP3-61 (Nissha FIS, Inc., Osaka, Japan) were used in this study. As this multisensor device was not built with a specific area of study in mind, it integrates sensors for different target pollutants. The MiCS sensors consist of a silicon substrate including a micro-machined diaphragm with an embedded heater and a MOS layer on top. The SP3-61 sensor is composed of an alumina substrate with a printed heater (bottom) and electrodes (top) and a thin film of ITO on the electrodes. Table 1 shows the concentration range of the target gases covered by the sensors and their rated power, as reported by the manufacturers. In the past, these sensors have been used to monitor air quality in urban areas for different purposes [START_REF] Sironi | Evaluation of Metal Oxides Sensors for the Monitoring of O 3 in Ambient Air at Ppb Level[END_REF][START_REF] Spinelle | Field calibration of a cluster of low-cost available sensors for air quality monitoring. Part A: Ozone and nitrogen dioxide[END_REF][START_REF] Williams | Validation of low-cost ozone measurement instruments suitable for use in an air-quality monitoring network[END_REF][START_REF] Peterson | Practical Use of Metal Oxide Semiconductor Gas Sensors for Measuring Nitrogen Dioxide and Ozone in Urban Environments[END_REF][START_REF] Sales-Lérida | An Approximation for Metal-Oxide Sensor Calibration for Air Quality Monitoring Using Multivariable Statistical Analysis[END_REF][START_REF] Spinelle | Field calibration of a cluster of low-cost commercially available sensors for air quality monitoring[END_REF].

Nanostructured Sensors

Sensors using MOS nanostructures as the active material, henceforth referred to as nanosensors, were manufactured. In the first place, four ultrathin dielectric membranes were processed on a silicon substrate by MEMS technology. Each membrane contains a heating resistor and two interdigitated electrodes that are isolated from each other and from the heating resistor. The assembly is known as a microhotplate. Then, the electrodes were coated with MOS nanostructures to be electrically measured. The materials, geometries, and manufacture process of the microhotplates have been described elsewhere [START_REF] Yoboué | An industrializable silicon-based microhotplate for metal oxides gas sensors[END_REF][START_REF] Dufour | Technological Improvements of a Metal Oxide Gas Multi-Sensor Based on a Micro-Hotplate Structure and Inkjet Deposition for an Automotive Air Quality Sensor Application[END_REF][START_REF] Presmanes | Integration of P-CuO Thin Sputtered Layers onto Microsensor Platforms for Gas Sensing[END_REF]. Two different microhotplate structures were used in this work. The first one had heating and measuring electrodes on the same level and was used for materials deposited by the electrospinning deposition process (Figure 1). To avoid the problem of the high SiO 2 step to be covered for very thin (25 nm to 50 nm) sputtered layers, another design was used in which the measuring electrode was moved to a level above (Figure 2). This last configuration allowed the reduction in the inter-electrode space from 60 µm to 15 µm, which also permitted the measurement of higher-resistive materials.

different purposes [START_REF] Sironi | Evaluation of Metal Oxides Sensors for the Monitoring of O 3 in Ambient Air at Ppb Level[END_REF][START_REF] Spinelle | Field calibration of a cluster of low-cost available sensors for air quality monitoring. Part A: Ozone and nitrogen dioxide[END_REF][START_REF] Williams | Validation of low-cost ozone measurement instruments suitable for use in an air-quality monitoring network[END_REF][START_REF] Peterson | Practical Use of Metal Oxide Semiconductor Gas Sensors for Measuring Nitrogen Dioxide and Ozone in Urban Environments[END_REF][START_REF] Sales-Lérida | An Approximation for Metal-Oxide Sensor Calibration for Air Quality Monitoring Using Multivariable Statistical Analysis[END_REF][START_REF] Spinelle | Field calibration of a cluster of low-cost commercially available sensors for air quality monitoring[END_REF].

Nanostructured Sensors

Sensors using MOS nanostructures as the active material, henceforth referred to as nanosensors, were manufactured. In the first place, four ultrathin dielectric membranes were processed on a silicon substrate by MEMS technology. Each membrane contains a heating resistor and two interdigitated electrodes that are isolated from each other and from the heating resistor. The assembly is known as a microhotplate. Then, the electrodes were coated with MOS nanostructures to be electrically measured. The materials, geometries, and manufacture process of the microhotplates have been described elsewhere [START_REF] Yoboué | An industrializable silicon-based microhotplate for metal oxides gas sensors[END_REF][START_REF] Dufour | Technological Improvements of a Metal Oxide Gas Multi-Sensor Based on a Micro-Hotplate Structure and Inkjet Deposition for an Automotive Air Quality Sensor Application[END_REF][START_REF] Presmanes | Integration of P-CuO Thin Sputtered Layers onto Microsensor Platforms for Gas Sensing[END_REF]. Two different microhotplate structures were used in this work. The first one had heating and measuring electrodes on the same level and was used for materials deposited by the electrospinning deposition process (Figure 1). To avoid the problem of the high SiO2 step to be covered for very thin (25 nm to 50 nm) sputtered layers, another design was used in which the measuring electrode was moved to a level above (Figure 2). This last configuration allowed the reduction in the inter-electrode space from 60 μm to 15 μm, which also permitted the measurement of higher-resistive materials. Two types of nanostructured sensing layers were prepared on the top surface of the microhotplates. On the one hand, thin films of zinc oxide doped with gallium (ZnO:Ga) were grown by magnetron sputtering under pure argon from a self-made oxide target [START_REF] Presmanes | Ga doped ZnO thin films deposited by RF sputtering for NO 2 sensing[END_REF] on microhotplates, as shown in Figure 2. On the other hand, highly porous mats of nanofibers of tin dioxide (SnO2) were deposited by electrospinning a polymeric solution containing a tin salt and eventually graphene (G) followed by calcination [START_REF] Masa | Chemiresistive sensors based on electrospun tin oxide nanofibers for detecting NO2 at the sub-0.1 ppm level[END_REF] on microhotplates, as displayed in Figure 1.

Three multisensor platforms (each platform contains 4 microhotplates) were coated with thin films of ZnO:Ga. One multisensor platform was coated with nanofibers of SnO2

Nanostructured Sensors

Sensors using MOS nanostructures as the active material, henceforth referred to nanosensors, were manufactured. In the first place, four ultrathin dielectric membra were processed on a silicon substrate by MEMS technology. Each membrane contain heating resistor and two interdigitated electrodes that are isolated from each other a from the heating resistor. The assembly is known as a microhotplate. Then, the electrod were coated with MOS nanostructures to be electrically measured. The materials, geom tries, and manufacture process of the microhotplates have been described elsewhere [START_REF] Presmanes | Integration of P-CuO Thin Sputtered Layers onto Microsensor Platforms for Gas Sensing[END_REF]. Two different microhotplate structures were used in this work. The first one had he ing and measuring electrodes on the same level and was used for materials deposited the electrospinning deposition process (Figure 1). To avoid the problem of the high S step to be covered for very thin (25 nm to 50 nm) sputtered layers, another design w used in which the measuring electrode was moved to a level above (Figure 2). This l configuration allowed the reduction in the inter-electrode space from 60 μm to 15 μ which also permitted the measurement of higher-resistive materials. Two types of nanostructured sensing layers were prepared on the top surface of microhotplates. On the one hand, thin films of zinc oxide doped with gallium (ZnO:G were grown by magnetron sputtering under pure argon from a self-made oxide target [ on microhotplates, as shown in Figure 2. On the other hand, highly porous mats of na fibers of tin dioxide (SnO2) were deposited by electrospinning a polymeric solution c taining a tin salt and eventually graphene (G) followed by calcination [START_REF] Masa | Chemiresistive sensors based on electrospun tin oxide nanofibers for detecting NO2 at the sub-0.1 ppm level[END_REF] on microh plates, as displayed in Figure 1.

Three multisensor platforms (each platform contains 4 microhotplates) were coa with thin films of ZnO:Ga. One multisensor platform was coated with nanofibers of Sn Two types of nanostructured sensing layers were prepared on the top surface of the microhotplates. On the one hand, thin films of zinc oxide doped with gallium (ZnO:Ga) were grown by magnetron sputtering under pure argon from a self-made oxide target [START_REF] Presmanes | Ga doped ZnO thin films deposited by RF sputtering for NO 2 sensing[END_REF] on microhotplates, as shown in Figure 2. On the other hand, highly porous mats of nanofibers of tin dioxide (SnO 2 ) were deposited by electrospinning a polymeric solution containing a tin salt and eventually graphene (G) followed by calcination [START_REF] Masa | Chemiresistive sensors based on electrospun tin oxide nanofibers for detecting NO2 at the sub-0.1 ppm level[END_REF] on microhotplates, as displayed in Figure 1.

Three multisensor platforms (each platform contains 4 microhotplates) were coated with thin films of ZnO:Ga. One multisensor platform was coated with nanofibers of SnO 2 and three platforms were coated with nanofibers of SnO 2 loaded with different graphene materials (SnO 2 :G): reduced graphene oxide (RGO, E800, Abalonyx AS, Oslo, Norway), pristine graphene (PG, 900561, Sigma-Aldrich, Saint Louis, MO, USA), and graphene nanoplatelets (GNPL, 900407, Sigma-Aldrich, Saint Louis, MO, USA). The gas (NO 2 and O 3 ) detection behavior of the nanosensors was tested in the lab and the ones that showed the best performance are summarized in Table 2 (two nanosensors from each platform). There were a total of fourteen nanosensors using ZnO:Ga films of 25 nm and 50 nm thickness, nanofibrous layers of SnO 2 , and nanofibrous layers of SnO 2 :G. Lab measurements were conducted with the MOS sensors and mixtures of ozone in air (25-500 ppb). The sensors using SnO 2 nanofibers were very sensitive to ozone over a broad temperature range (20-400 • C). The optimal working temperature (at which the sensor response reached a maximum) was 350 • C (SnO 2 ) and 200 • C (SnO 2 :G) [START_REF] Masa | Graphene-Tin Oxide Composite Nanofibers for Low Temperature Detection of NO 2 and O 3[END_REF]. It was decided then to operate the nanosensors of SnO 2 in the continuous heating mode at 14.5 mW (~100 • C) and 41 mW (~350 • C). On the other hand, the sensors based on ZnO:Ga were measured by heating the microhotplate between 100 • C and 400 • C. The best response was obtained at 25 mW (~205 • C). For a heating power equal to or greater than 35 mW (~305 • C), a drift in the sensor response was found. Two measuring modes were used for these nanosensors: a classical continuous heating mode at 25 mW (~250 • C) and an alternating heating mode in which the sensor was heated alternately between 5 mW and 25 mW for 3 min.

Figure 3a,b display the commercial sensors used in this work. They are encapsulated and the housings have openings that allow access of the gas to the MOS film inside. Figure 2c shows the selected arrangement for the nanosensors. The multisensor platform is bonded to the top surface of a standard TO-8 header and the electrodes and heater of the microhotplates are wired to the pins of the header.

nanofibrous layers of SnO2, and nanofibrous layers of SnO2:G. Lab measurements were conducted with the MOS sensors and mixtures of ozone in air (25-500 ppb). The sensors using SnO2 nanofibers were very sensitive to ozone over a broad temperature range (20-400 °C). The optimal working temperature (at which the sensor response reached a maximum) was 350 °C (SnO2) and 200 °C (SnO2:G) [START_REF] Masa | Graphene-Tin Oxide Composite Nanofibers for Low Temperature Detection of NO 2 and O 3[END_REF]. It was decided then to operate the nanosensors of SnO2 in the continuous heating mode at 14.5 mW (~100 °C) and 41 mW (~350 °C). On the other hand, the sensors based on ZnO:Ga were measured by heating the microhotplate between 100 °C and 400 °C. The best re sponse was obtained at 25 mW (~205 °C). For a heating power equal to or greater than 35 mW (~305 °C), a drift in the sensor response was found. Two measuring modes were used for these nanosensors: a classical continuous heating mode at 25 mW (~250 °C) and an alternating heating mode in which the sensor was heated alternately between 5 mW and 25 mW for 3 min.

Figure 3a,b display the commercial sensors used in this work. They are encapsulated and the housings have openings that allow access of the gas to the MOS film inside. Figure 2c shows the selected arrangement for the nanosensors. The multisensor platform is bonded to the top surface of a standard TO-8 header and the electrodes and heater of the microhotplates are wired to the pins of the header.

Air Pollution Monitoring Devices 2.2.1. Device Design

We developed and manufactured multisensor devices for measuring air pollution in real-time, each one using a different type of MOS sensor. The devices were labeled CO (commercial sensors), CS (nanosensors based on nanofibers of SnO 2 or SnO 2 :G), and CN (nanosensors using thin films of ZnO:Ga). Sensor holder PCBs were specifically designed for each type of sensor. Each PCB could host up to 8 gas sensors of the same type and a temperature and humidity sensor (SHT21, Sensirion AG, Stäfa, Switzerland). The devices were controlled by the low-power, RISC-based, 8-bit ATMega2650 microcontroller (Microchip Technology Inc., Chandler, AZ, USA). This met the needs of the device, with features such as 256 KB of ISP flash memory, 8 KB of SRAM, 4 KB of EEPROM, 86 general-purpose I/O lines, 32 general-purpose working registers, a PWM, four USARTs, a 16-channel 10-bit A/D converter, and a JTAG interface for on-chip debugging. The device achieved a performance of 16 MIPS at 16 MHz. Readout of the sensors was performed via an external low-power 24-bit, 8-channel analog-digital converter, which allowed the acquisition of up to 15 samples per second. Three selectable bias voltages (5 V, 3.3 V, and 2.5 V) were implemented for added versatility. In addition, two measuring ranges were implemented to optimize the resolution of the measurements. These were automatically selected by the implemented program according to the measured sensor resistance. In addition, the voltage supplied to the sensor heating elements was controlled by two 12-bit, 4-channel digital-to-analog converters. In order to track the control of heaters, the current was measured with a current shunt monitor. Regarding communications, the device implements a USB port (modbus-RTU by default), Ethernet, and WiFi. Moreover, the system stores the data in a local µSD card. A real-time clock is included in the design to allow the user to know the time when there is no internet connection. With respect to the pneumatic design, the unit is equipped with an active sampling system. It includes a pneumatic pump with variable control, which produces a 0.5 L min-1 airflow to the sensors, and an electrovalve that allows the system to switch from two gas sample inlets. Moreover, a resin cell was developed to encase the sensors. The whole device was powered by a 230 VAC 50 Hz power supply. Figure 4 shows a picture of one of the devices and some key parts.

temperature and humidity sensor (SHT21, Sensirion AG, Stäfa, Switzerland). The devices were controlled by the low-power, RISC-based, 8-bit ATMega2650 microcontroller (Microchip Technology Inc., Chandler, AZ, USA). This met the needs of the device, with features such as 256 KB of ISP flash memory, 8 KB of SRAM, 4 KB of EEPROM, 86 generalpurpose I/O lines, 32 general-purpose working registers, a PWM, four USARTs, a 16-channel 10-bit A/D converter, and a JTAG interface for on-chip debugging. The device achieved a performance of 16 MIPS at 16 MHz. Readout of the sensors was performed via an external low-power 24-bit, 8-channel analog-digital converter, which allowed the acquisition of up to 15 samples per second. Three selectable bias voltages (5 V, 3.3 V, and 2.5 V) were implemented for added versatility. In addition, two measuring ranges were implemented to optimize the resolution of the measurements. These were automatically selected by the implemented program according to the measured sensor resistance. In addition, the voltage supplied to the sensor heating elements was controlled by two 12-bit, 4-channel digital-to-analog converters. In order to track the control of heaters, the current was measured with a current shunt monitor. Regarding communications, the device implements a USB port (modbus-RTU by default), Ethernet, and WiFi. Moreover, the system stores the data in a local μSD card. A real-time clock is included in the design to allow the user to know the time when there is no internet connection. With respect to the pneumatic design, the unit is equipped with an active sampling system. It includes a pneumatic pump with variable control, which produces a 0.5 L min-1 airflow to the sensors, and an electrovalve that allows the system to switch from two gas sample inlets. Moreover, a resin cell was developed to encase the sensors. The whole device was powered by a 230 VAC 50 Hz power supply. Figure 4 shows a picture of one of the devices and some key parts.

Laboratory Measurements

Measurements were performed in the laboratory with the multisensor devices and ozone-air mixtures from a commercial ozone source (model 714 NO2/NO/O3 Calibration Source, 2B Technologies, Boulder, CO, USA), which generates ozone by photolysis of molecular oxygen in the air. The concentration of ozone was increased from 0 ppb to 200 ppb in 5 steps of a duration of 10 min each. The measurements were repeated 3 times on different days in order to assess the sensor performance and the repeatability of the results. Figure 5 shows the results corresponding to the three devices (CO, CN, and CS). For simplicity, only one sensor of each kind is shown.

Source, 2B Technologies, Boulder, CO, USA), which generates ozone by photolysis of mo lecular oxygen in the air. The concentration of ozone was increased from 0 ppb to 200 ppb in 5 steps of a duration of 10 min each. The measurements were repeated 3 times on dif ferent days in order to assess the sensor performance and the repeatability of the results Figure 5 shows the results corresponding to the three devices (CO, CN, and CS). For sim plicity, only one sensor of each kind is shown. in 5 steps of a duration of 10 min each. The measurements were repeated 3 times on dif ferent days in order to assess the sensor performance and the repeatability of the results Figure 5 shows the results corresponding to the three devices (CO, CN, and CS). For sim plicity, only one sensor of each kind is shown. Historical air quality data reveal that ozone concentrations beyond the target value for the protection of human health occur more than 25 times every year at Monfragüe National Park. For instance, 32 exceedances were recorded in 2020 for ozone [START_REF]Ministerio para la Transición Ecológica y el Reto Demográfico[END_REF], despite the noticeable reduction in air pollution observed globally as a result of the COVID-19 pandemic. It is also usually in summer that ozone is at its highest level. This is explained by the large emissions of VOCs (mainly of natural origin), high temperatures, and intense solar radiation prevailing in summer in Extremadura [START_REF] Cerrato-Alvarez | Synoptic circulation patterns and local sources associated to high concentrations of tropospheric ozone in rural and suburban areas in southwestern Spain[END_REF][START_REF] Escudero | Assessment of the variability of atmospheric pollution in National Parks of mainland Spain[END_REF]. On the other hand, the concentrations of other gas pollutants (e.g., NO 2 and CO) remain very low throughout the year, well below the limit values for protecting health. This situation makes Monfragüe National Park an ideal environment to assess the detection performance of the MOS sensors toward ozone, without interferences from other gases.

Field Campaign

Field Campaign

The multisensor devices were collocated next to the air quality station at Monfragüe National Park, which was used as a reference. It supplies hourly average values of the concentration in air of all pollutants regulated by the European directive. Specifically, the station includes a UV photometer (model 49i-B3ZAA, Thermo Fisher Scientific, Waltham, MA, USA) as an ozone analyzer. The devices were synchronized with the station and recorded pollutant concentration values every 5 s. After the field campaign, the data from the devices were averaged over 1 h periods. Figure 7 displays the response of the MOS sensors after applying normalization (0,1) and linear drift counteraction. Commercial sensors CO3 and CO7 exhibited anomalous behavior and their data were dismissed.

pandemic. It is also usually in summer that ozone is at its highest level. This is ex by the large emissions of VOCs (mainly of natural origin), high temperatures, and solar radiation prevailing in summer in Extremadura [START_REF] Cerrato-Alvarez | Synoptic circulation patterns and local sources associated to high concentrations of tropospheric ozone in rural and suburban areas in southwestern Spain[END_REF][START_REF] Escudero | Assessment of the variability of atmospheric pollution in National Parks of mainland Spain[END_REF]. On the other hand, t centrations of other gas pollutants (e.g., NO2 and CO) remain very low through year, well below the limit values for protecting health. This situation makes Mo National Park an ideal environment to assess the detection performance of the M sors toward ozone, without interferences from other gases.

The multisensor devices were collocated next to the air quality station at Mo National Park, which was used as a reference. It supplies hourly average value concentration in air of all pollutants regulated by the European directive. Specifica station includes a UV photometer (model 49i-B3ZAA, Thermo Fisher Scientific, W MA, USA) as an ozone analyzer. The devices were synchronized with the station a orded pollutant concentration values every 5 s. After the field campaign, the da the devices were averaged over 1 h periods. Figure 7 displays the response of th sensors after applying normalization (0,1) and linear drift counteraction. Commerc sors CO3 and CO7 exhibited anomalous behavior and their data were dismissed.

Sensor Calibration

In order to calibrate the multisensor devices to measure ozone, we built a m learning model. This model was a SVR with a polynomial kernel. For each devi CS, and CN), the sensors response was split into two sets (training and test) by ra selecting 30% of the data for training and the remaining 70% for testing. It is well that MOS sensors are affected by ambient temperature and humidity and, thus, th rameters were also measured and used as inputs to the model [START_REF] Sales-Lérida | An Approximation for Metal-Oxide Sensor Calibration for Air Quality Monitoring Using Multivariable Statistical Analysis[END_REF][START_REF] Kim | ML-based humidity and temperature calibration system for heterogeneous mox sensor array in ppm-level BTEX monitoring[END_REF].

By feeding the training set and the corresponding reference values into the S model was fitted. Then, using the test set, the model was able to calculate three v the ozone concentration, one for each device. To assess the goodness of the ozo

Sensor Calibration

In order to calibrate the multisensor devices to measure ozone, we built a machine learning model. This model was a SVR with a polynomial kernel. For each device (CO, CS, and CN), the sensors response was split into two sets (training and test) by randomly selecting 30% of the data for training and the remaining 70% for testing. It is well known that MOS sensors are affected by ambient temperature and humidity and, thus, these parameters were also measured and used as inputs to the model [START_REF] Sales-Lérida | An Approximation for Metal-Oxide Sensor Calibration for Air Quality Monitoring Using Multivariable Statistical Analysis[END_REF][START_REF] Kim | ML-based humidity and temperature calibration system for heterogeneous mox sensor array in ppm-level BTEX monitoring[END_REF].

By feeding the training set and the corresponding reference values into the SVR, the model was fitted. Then, using the test set, the model was able to calculate three values of the ozone concentration, one for each device. To assess the goodness of the ozone data achieved with each device, the coefficient of determination (R 2 ) and the Root-Mean-Squared Error (RMSE) were used, as well as the parameters from the least squares regression line.

Data Uncertainty

The uncertainty of the data from the multisensor devices was calculated following the protocol recommended by the EC Working Group on Guidance for the Demonstration of Equivalence [START_REF]Guidance to the Demonstration of Equivalence of Ambient Air Monitoring Methods Report by an EC Working Group on Guidance for the Demonstration of Equivalence[END_REF], which is based on the orthogonal regression of the sensor data against the reference data. The relative expanded uncertainty (at the limit value) was calculated by [START_REF] Warneck | Ozone in the trophosphere[END_REF], where a and b are the intercept and slope of the orthogonal regression, respectively, n is the number of measurements results, u 2 (x i ) is the uncertainty of the reference analyzer, and RSS is the sum of squares of relative residuals (2) or absolute residuals (3). More details on the calculation of the relative expanded uncertainty can be found in the Guide to the demonstration of equivalence [START_REF]Guidance to the Demonstration of Equivalence of Ambient Air Monitoring Methods Report by an EC Working Group on Guidance for the Demonstration of Equivalence[END_REF].

U r (y i ) = 2 • RSS (n-2) -u 2 (x i ) + [a + (b -1)x i ] 2 y i (1)
RSS = ∑ n i=1 (y i -a -bx i ) 2 when (y i -a -bx i ) 2 is constant (2) RSS = (a + bx i ) 2 ∑ n i=1 y i a + bx i -1 2 when y i a + bx i -1 2 is constant (3)

Results and Discussion

Sensor Calibration

Figure 8 shows the results of the calibration of the devices' CO, CS, and CN against the ozone analyzer. The scatter plots show the distribution of the measured ozone concentration values as well as the values of R 2 , RMSE, and a and b regression coefficients. This values are also summarized in Table 3.

the protocol recommended by the EC Working Group on Guidance for the Demon of Equivalence [START_REF]Guidance to the Demonstration of Equivalence of Ambient Air Monitoring Methods Report by an EC Working Group on Guidance for the Demonstration of Equivalence[END_REF], which is based on the orthogonal regression of the sensor data the reference data. The relative expanded uncertainty (at the limit value) was cal by [START_REF] Warneck | Ozone in the trophosphere[END_REF], where a and b are the intercept and slope of the orthogonal regression, respe 𝑛 is the number of measurements results, 𝑢 𝑥 is the uncertainty of the referen lyzer, and RSS is the sum of squares of relative residuals (2) or absolute residuals (3 details on the calculation of the relative expanded uncertainty can be found in the to the demonstration of equivalence [START_REF]Guidance to the Demonstration of Equivalence of Ambient Air Monitoring Methods Report by an EC Working Group on Guidance for the Demonstration of Equivalence[END_REF].

𝑈 𝑦 2 • 𝑅𝑆𝑆 𝑛 2 𝑢 𝑥 𝑎 𝑏 1 𝑥 𝑦 𝑅𝑆𝑆 ∑ 𝑦 𝑎 𝑏𝑥 when 𝑦 𝑎 𝑏𝑥 is constant 𝑅𝑆𝑆 𝑎 𝑏𝑥 ∑ 1 when 1 is constant

Results and Discussion

Sensor Calibration

Figure 8 shows the results of the calibration of the devices' CO, CS, and CN the ozone analyzer. The scatter plots show the distribution of the measured ozo centration values as well as the values of R 2 , RMSE, and a and b regression coef This values are also summarized in Table 3. The devices based on MOS nanosensors showed a moderate correlation with the reference analyzer, with values of R 2 of 0.70 and 0.69 for CS and CN, respectively. This was also the case for the device based on commercial MOS sensors (R 2 of 0.67 for CO). The RMSE values were 13.50 µg•m -3 , 13.61 µg•m -3 , and 14.03 µg•m -3 for the devices' CS, CN, and CO, respectively. The maximum deviation in RMSE was 7% for CN, and it was less than 5% for the devices' CS and CO. Moreover, if the CS and CN devices are directly compared with the commercial sensors (Figure 9), satisfactory performances of CS and CN are assessed. μg•m . The devices based on MOS nanosensors showed a moderate correlation with erence analyzer, with values of R 2 of 0.70 and 0.69 for CS and CN, respectively. T also the case for the device based on commercial MOS sensors (R 2 of 0.67 for C RMSE values were 13.50 μg•m -3 , 13.61 μg•m -3 , and 14.03 μg•m -3 for the devices' C and CO, respectively. The maximum deviation in RMSE was 7% for CN, and it w than 5% for the devices' CS and CO. Moreover, if the CS and CN devices are compared with the commercial sensors (Figure 9), satisfactory performances of CN are assessed.

Data Uncertainty

To evaluate the performance of the multisensor devices, the measurement tainty was calculated following the methodology described in Section 3.

Table 4 shows relevant statistical parameters of the orthogonal regression relative expanded uncertainty for each multisensor device. Regarding statistical a of the CO, CN, and CS devices, a positive systematic error was detected in the in as 0 was not included between the 95% confidence limits. A systematic error w detected for the slope as the value of 1 was not between the 95% confidence lim relative expanded uncertainties (at limit value) were 20.41%, 19.39%, and 19.45% CN, and CS devices, respectively, which means better results were obtained with C CS devices compared to CO. However, in all cases, the uncertainty values were le 30%, thus meeting the uncertainty requirement of European directive 2008/520/CE dicative measurements [START_REF] Karpus | Implementation of directive 2008/50/EC of 21 May 2008 on Ambient Air Quality and Cleaner Air for Europe in Polish environmental law[END_REF].

Data Uncertainty

To evaluate the performance of the multisensor devices, the measurement uncertainty was calculated following the methodology described in Section 3.

Table 4 shows relevant statistical parameters of the orthogonal regression and the relative expanded uncertainty for each multisensor device. Regarding statistical analysis of the CO, CN, and CS devices, a positive systematic error was detected in the intercept, as 0 was not included between the 95% confidence limits. A systematic error was also detected for the slope as the value of 1 was not between the 95% confidence limits. The relative expanded uncertainties (at limit value) were 20.41%, 19.39%, and 19.45% for CO, CN, and CS devices, respectively, which means better results were obtained with CN and CS devices compared to CO. However, in all cases, the uncertainty values were less than 30%, thus meeting the uncertainty requirement of European directive 2008/520/CE for indicative measurements [START_REF] Karpus | Implementation of directive 2008/50/EC of 21 May 2008 on Ambient Air Quality and Cleaner Air for Europe in Polish environmental law[END_REF].

Figure 1 .

 1 Figure 1. Microhotplate gas sensor with heater and sensing electrodes at the same metallization level: (a) chip top view; (b) cross-sectional view.

Figure 2 .

 2 Figure 2. Microhotplate gas sensor with encapsulated heater and very close sensing electrodes at the surface: (a) chip top view; (b) cross-sectional view.

Figure 1 .

 1 Figure 1. Microhotplate gas sensor with heater and sensing electrodes at the same metallization level: (a) chip top view; (b) cross-sectional view.

Figure 1 .

 1 Figure 1. Microhotplate gas sensor with heater and sensing electrodes at the same metallizat level: (a) chip top view; (b) cross-sectional view.

Figure 2 .

 2 Figure 2. Microhotplate gas sensor with encapsulated heater and very close sensing electrode the surface: (a) chip top view; (b) cross-sectional view.

Figure 2 .

 2 Figure 2. Microhotplate gas sensor with encapsulated heater and very close sensing electrodes at the surface: (a) chip top view; (b) cross-sectional view.

Figure 3 .

 3 Figure 3. OEM sensors: (a) MiCS 2714 (5.5 × 7.5 × 2.5 mm) and (b) SP3-61 (Ø 14 mm, h 13 mm), and (c) bare TO-8 header (Ø 15.25 mm, h 1.5 mm) with self-designed multisensor silicon platform (4 nanosensors) on top.

Figure 3 .

 3 Figure 3. OEM sensors: (a) MiCS 2714 (5.5 × 7.5 × 2.5 mm) and (b) SP3-61 (Ø 14 mm, h 13 mm), and (c) bare TO-8 header (Ø 15.25 mm, h 1.5 mm) with self-designed multisensor silicon platform (4 nanosensors) on top.

Figure 4 .

 4 Figure 4. The multisensor device for the monitoring of air pollution and its main components.

Figure 4 .

 4 Figure 4. The multisensor device for the monitoring of air pollution and its main components.

Figure 5 .

 5 Figure 5. Response of commercial nanosensors (CO), ZnO:Ga based sensors (CN), and SnO2 nano fibrous layer sensors (CS), to an increasing concentration of ozone in air under laboratory condi tions.

2. 3 . 1 .

 31 Monfragüe National Park The devices for the monitoring of air pollution by means of MOS sensors were de ployed during the summer of 2021 in Monfragüe National Park, a protected natural zone (Natural Park and Biosphere Reserve) located in the province of Cáceres (Extremadura in Spain. It covers an area of 179 km 2 and has an air quality station from the Air Quality Protection and Research Network of Extremadura (REPICA) inside (Figure 6).

Figure 6 .

 6 Figure 6. Map of the Spanish National Parks. The inset shows the air quality station (ES1616A) a Monfragüe National Park.

Figure 5 .

 5 Figure 5. Response of commercial nanosensors (CO), ZnO:Ga based sensors (CN), and SnO 2 nanofibrous layer sensors (CS), to an increasing concentration of ozone in air under laboratory conditions.

2. 3 .

 3 Field Campaign 2.3.1. Monfragüe National Park The devices for the monitoring of air pollution by means of MOS sensors were deployed during the summer of 2021 in Monfragüe National Park, a protected natural zone (Natural Park and Biosphere Reserve) located in the province of Cáceres (Extremadura) in Spain. It covers an area of 179 km 2 and has an air quality station from the Air Quality Protection and Research Network of Extremadura (REPICA) inside (Figure 6).

Figure 5 .

 5 Figure 5. Response of commercial nanosensors (CO), ZnO:Ga based sensors (CN), and SnO2 nano fibrous layer sensors (CS), to an increasing concentration of ozone in air under laboratory cond tions.

2. 3 . 1 .

 31 Monfragüe National ParkThe devices for the monitoring of air pollution by means of MOS sensors were de ployed during the summer of 2021 in Monfragüe National Park, a protected natural zon (Natural Park and Biosphere Reserve) located in the province of Cáceres (Extremadura in Spain. It covers an area of 179 km 2 and has an air quality station from the Air Qualit Protection and Research Network of Extremadura (REPICA) inside (Figure6).

Figure 6 .

 6 Figure 6. Map of the Spanish National Parks. The inset shows the air quality station (ES1616A) a Monfragüe National Park.

Figure 6 .

 6 Figure 6. Map of the Spanish National Parks. The inset shows the air quality station (ES1616A) at Monfragüe National Park.

Figure 7 .

 7 Figure 7. Normalized response of MOS sensors (CO, CS, and CN) during the summer cam Monfragüe National Park.

Figure 7 .

 7 Figure 7. Normalized response of MOS sensors (CO, CS, and CN) during the summer campaign at Monfragüe National Park.

Figure 8 .

 8 Figure 8. Calibration scatterplots for ozone concentration: Multisensor devices' CO, CS, and reference analyzer. Light orange dots represent the individual points sensor-reference, th

Figure 8 .

 8 Figure 8. Calibration scatterplots for ozone concentration: Multisensor devices' CO, CS, and CN vs. reference analyzer. Light orange dots represent the individual points sensor-reference, the orange line is the least squares regression line, and the black line represents the x = y line. Units are in µg•m -3 .

Figure 9 .

 9 Figure 9. Correlation scatterplots for ozone concentration: Nanosensors CS (left) and CN (r commercial sensors CO. Units in μg•m -3 .

Figure 9 .

 9 Figure 9. Correlation scatterplots for ozone concentration: Nanosensors CS (left) and CN (right) vs. commercial sensors CO. Units in µg•m -3 .

Table 1 .

 1 Commercial Sensors.

	#	Model	Pollutant	Range (pbb)	Power (mW)
	CO1 CO2 CO3	MiCS 2714 (OX) MiCS 4514 (OX) MiCS 4514 (RED)	NO 2 NO 2 CO	50-10 4 50-10 4 10 3 -10 6	43 43 76
	CO4 CO5	MiCS 6814 (OX) MiCS 6814 (RED)	NO 2 CO	50-10 4 10 3 -10 6	43 76
	CO6 CO7	MiCS 6814 (OX) MiCS 6814 (RED)	NO 2 CO	50-10 4 10 3 -10 6	43 76
	CO8	FIS SP3-61	O 3	2-10 3	400

Table 2 .

 2 Nanosensors.

		ZnO:Ga Thin-Film			SnO 2 :G Nanofibrous Layer
	#	Film Thicknes (nm)	Power (mW)	#	Graphene Type	Power (mW)
	CN1	25	25	CS1	RGO	41
	CN2	25	5-25	CS2	RGO	41
	CN3	50	25	CS3	PG	14.5
	CN4	50	5-25	CS4	PG	41
	CN5	50	25	CS5	GNPL	14.5
	CN6	50	5-25	CS6	GNPL	41
	-	-	-	CS7	-	14.5
	-	-	-	CS8	-	14.5

Table 2 .

 2 Nanosensors.

		ZnO:Ga Thin-Film		SnO2:G Nanofibrous Layer
	#	Film Thicknes (nm)	Power (mW)	#	Graphene Type	Power (mW)
	CN1	25	25	CS1	RGO	41
	CN2	25	5-25	CS2	RGO	41
	CN3	50	25	CS3	PG	14.5
	CN4	50	5-25	CS4	PG	41
	CN5	50	25	CS5	GNPL	14.5
	CN6	50	5-25	CS6	GNPL	41
	-	-	-	CS7		14.5
	-	-	-	CS8		14.5

Table 3 .

 3 Calibration metrics. Sensor vs, Reference.

		CO	CS		CN
		Value	Value	%CO	Value	%CO
	R 2	0.67	0.70	104.5	0.69	103.0
	RMSE (µg m -3 )	14.03	13.50	96.2	13.61	97.0
	Slope	0.68	0.71	104.4	0.71	104.4
	Intercept (µg m -3 )	27.26	25.44	93.3	25.11	92.1

Table 3 .

 3 Calibration metrics. Sensor vs, Reference.

		CO	CS		CN
		Value	Value	%CO	Value	%C
	R 2	0.67	0.70	104.5	0.69	10
	RMSE (μg m -3 )	14.03	13.50	96.2	13.61	97
	Slope	0.68	0.71	104.4	0.71	10
	Intercept (μg m -3 )	27.26	25.44	93.3	25.11	92

Funding: This research was funded by the European Regional Development Fund (European Commission) through the V Interreg Sudoe Programme under GA SOE2/P1/E0569-NanoSen-AQM project.

Institutional Review Board Statement: Not applicable.

Informed Consent Statement: Not applicable.

Acknowledgments: Authors want to thank the EU for supporting the NanoSen-AQM (SOE/P1/E0569) project and the Spanish Ministry of Science and Innovation for supporting the NEOGAS project (PID2019-107697RB). This work was partly supported by LAAS-CNRS micro and nano technolgies platform member of the French RENATECH network.

Other authors have conducted similar studies with MOS sensors (commercial or prototype devices). For example, [START_REF] Djedidi | Accurate detection and discrimination of pollutant gases using a temperature modulated MOX sensor combined with feature extraction and support vector classification[END_REF] used SVR to calibrate an array of sensors and classify the data after extracting features based on the Relief method. On the other hand, [START_REF] Bruno | Embedded Artificial Intelligence Approach for Gas Recognition in Smart Agriculture Applications Using Low Cost MOX Gas Sensors[END_REF] built a neural network to process the data acquired from an array of MOS sensors to evaluate the impact of NO 2 , NH 3 , and CH 4 in agriculture applications. Even though both papers showed promising results, neither of them (as with many others in the literature) performed the measurement uncertainty calculation shown in this work, which we believe should play a relevant role in sensor performance evaluation, e.g., the European regulation on air quality includes maximum uncertainty requirements to validate air pollution monitoring equipment.

Conclusions

In this work, we have demonstrated the real-world applicability of newly developed resistive sensors using MOS nanostructures as gas-sensitive material (nanosensors) for the purpose of measuring ozone in ambient air. One type of nanosensor is based on ZnO:Ga thin films, while another type is formed by nanofibers of SnO 2 or SnO 2 :G. The performance of the MOS nanosensors and of a selected commercial MOS sensor for ozone was assessed against a reference analyzer in a field measurement campaign in a natural environment characterized by a low pollution level. Both the nanosensors and the commercial sensor performed similarly and showed a moderate correlation with the reference (R 2 of 0.67-0.7) and a deviation in terms of RMSE of 13.50-14.03 µg•m -3 , which is about 10% of the maximum ozone concentration. Furthermore, the nanosensors exhibited a great performance when compared with the commercial sensor (R 2 of 0.94 and 0.95, RMSE of 5.21 µg• m -3 and 4.83 µg•m -3 , and offset of 1.44 µg•m -3 and 0.37 µg•m -3 ), while the former operated at powers at least a factor of 10 lower than the latter. In addition, for the first time, we calculated the uncertainty in the sensor measurements using a recognized method, which resulted in uncertainty values of less than 30% for both the nanosensors and the commercial sensor. This is a promising result toward the adoption of low-cost sensors for indicative air quality measurements.


Remadji Rirongarti
email: rirongarti_85@yahoo.fr

Christine Cocquyt

Christine Paillès

Christine Pailles

Florence Sylvestre

Staurophora ouniangaensis spec.nov. (Bacillariophyceae, Anomoeoneidaceae), a new diatom from the Ounianga Lakes in the Sahara, Chad

Keywords: Africa, Cymbella obtusa, mesosaline waters, new species, taxonomy

published or not. The documents may come     Staurophora ouniangaensis sp. nov. (Bacillariophyceae, Anomoeoneidaceae), a new diatom from the Ounianga Lakes in the Sahara, Chad

Introduction

The lakes of Ounianga are a UNESCO World Heritage Site (UNESCO 2015) and form a unique hydrological system in the world [START_REF] Kröpelin | The Saharan lakes of Ounianga Serir -a unique hydrogeological system[END_REF]. This exceptional value comes from the existence of a series of lakes and oases in the Chadian Sahara, one of the most arid part of the world. Featuring peculiar geological structures-Nubian Sandstone-the different types of landscape have undoubted beauty (Figure 1).

Their current diatom communities have not yet been the subject of extensive studies. Two earlier studies (Round 1961a, b) were carried out on a few samples from the Chadian Sahara, the Ennedi and some of the Ounianga lakes, and listed the main diatom species observed in these environments. More recently, [START_REF] Kröpelin | Climate-driven ecosystem succession in the Sahara: the last 6000 years[END_REF] studied climate changes in the Sahara during the last 6,000 years, including a salinity reconstruction, based on the African diatom database [START_REF] Gasse | Diatom-based transfer functions for inferring past hydrochemical chatacteristics of African lakes[END_REF] and modern diatom assemblages in the lakes of Ounianga. During the wet mid-Holocene period, the fossil diatom flora was characterized by the significant abundance of freshwater species (mainly Aulacoseira Thwaites (1848: 167) and Synedra Ehrenberg (1830: 40) s.l.). An increase in salinity (300 µS.cm -1 to 500 µS.cm -1 ) occurred between 4,200 and 3,900 years B.P. [START_REF] Kröpelin | Climate-driven ecosystem succession in the Sahara: the last 6000 years[END_REF]) and favoured the development of salt tolerant diatoms such as Nitzschia fonticola (Grunow) Grunow (in Van Heurck 1881: pl. 69, figs 15-20), N. cf. elliptica Hustedt (1949: 148), Rhopalodia gibberula (Ehrenberg) O. Müller (1899: 97) and Stauroneis Ehrenberg (1843: 45) at the expense of Aulacoseira species. A recent study conducted in each lake of the Ounianga system by Rirongarti (2019) and Rirongarti et al. (submitted) revealed many more species than previously listed (Round 1961a, b, Kropelin et al. 2008), including some Staurophora Mereschkowsky (1903: 45, 142) taxa.

The genus Staurophora is a small entity consisting of only fifteen species and one accepted variety (Guiry in Guiry & Guiry 2020). In addition, the taxonomic status of S. gregoryi Mereschkowsky (1903: 22) and S. vilamae Maidana, Seeligann & Morales (2009: 269) is uncertain (Guiry in Guiry & Guiry 2020). Staurophora species are characterised by linear or lanceolate valves, a gently curved valve face merging sometimes steeply into the mantle, a central area expanded in a fascia reaching the margins with 2 to 3 shortened striae, and one single chloroplast [START_REF] Round | The Diatoms. Biology and Morphology of the Genera[END_REF]). Most of the species are found epipelic in marine and brackish waters. However, some taxa such as Staurophora caljonii Cocquyt (Cocquyt 2004: 40) are reported from inland waters with elevated conductivities.

Sampling sites

The region of Ounianga, located between 19°N and 20°E, is one of the most arid parts of the Chadian Sahara (Figure 1A). Situated between the volcanic ranges of Tibesti and Ennedi and is backed by the sandstone plateaus of the Erdis, it is characterized by a hyper arid Saharan climate marked by long periods of drought and practically no rain. Average precipitation recorded in the 1960s was less than 5 mm per year while potential evaporation was around 6 m per year [START_REF] Capot-Rey | Borkou et Ounianga: étude de géographie régionale[END_REF].

The particularity of this region of northeastern Chad is the presence of splendid lake complexes located in narrow sandstone escarpments formed by the wind (Figure 1E). These lake complexes, considered to be the largest lake system in the Sahara, are divided into two group (Figure 1C). To the west, at 19.055°N and 20.505°E, the group of Ounianga Kebir consists of Lakes Yoa, Uma, Mioji, Jabou and Forodone (Figure 1D). Fifty kilometers to the east, at 18.929°N and 20.850°E, the group of Ounianga Serir is aligned in a north-east/south-west direction in a depression thought to be of aeolian origin. The Ounianga Serir group consists of Lakes Ardjou, Edem, Teli, Hogou, Agouta, Djara, Bedrim and Bokou, aligned parallel to each other and separated by sand dunes (Figure 1E). They spread on about 10 km. All these lakes are currently fed by the fossil waters of the Nubian Sandstone Aquifer System (NSAS), which enable the lakes to persist under arid climate [START_REF] Kröpelin | The Saharan lakes of Ounianga Serir -a unique hydrogeological system[END_REF][START_REF] Poulin | Bilan hydrologique et étude de la recharge de trois systèmes lac-aquifère du Bassin du lac Tchad par une approche géochimique multi traceurs[END_REF].

The geomorphological configuration means that the lakes of Ounianga Kebir are all strongly saline, with conductivities ranging from 64,000 µS.cm -1 to 352,000 µS.cm -1 , whereas the spring water that feeds them is fresher (217 µS.cm -1 and 623 µS.cm -1) . Lake Yoa is the largest and deepest Ounianga Kebir lake with an area of 3.58 km 2 and a maximum depth of 27 m. Furthermore, it never dried out for the last 6,000 years [START_REF] Kröpelin | Climate-driven ecosystem succession in the Sahara: the last 6000 years[END_REF].

The Ounianga Serir lakes are located in a 10 km-wide depression and display a specific hydrological functioning because of their parallel alignment and their 'staircase' position at different elevations. The topography allows that lake water can flow through sand dunes from one lake into the other. Consequently, water becomes gradually more saline as it reaches the central Lake Teli which is located at the lowest point of the depression [START_REF] Poulin | Bilan hydrologique et étude de la recharge de trois systèmes lac-aquifère du Bassin du lac Tchad par une approche géochimique multi traceurs[END_REF]. The mechanism results in an increasing salinity gradient from the peripheral to the central lakes: from Lake Bokou in the east (326 µS.cm -1 ) and Lake Ardjou in the west (2880 µS.cm -1 ) to the central extremely saline Lake Teli (112,100 µS.cm -1 ). The intense evaporation affecting the large (4.36 km²) and shallow (maximum depth of 5 m) Lake Teli is compensated by groundwater input from the NSAS and by a steady flow from the neighbouring lakes through the dunes [START_REF] Poulin | Bilan hydrologique et étude de la recharge de trois systèmes lac-aquifère du Bassin du lac Tchad par une approche géochimique multi traceurs[END_REF]. Thus the water level in the lakes is constant throughout the year (Van der [START_REF] Van Der Meeren | Les lacs d'Ounianga: mieux comprendre leur dynamique hydrologique et écologique à long terme à travers l''étude intégrée de leurs archives sédimentaires et de la limnologie et l'écologie aquatique actuelles[END_REF]. Numerous springs ae presents on the shores of the lakes which are partially or totally covered with macrophyte vegetation.

Material and methods

Samples from the Ounianga lakes for diatom investigation were collected during two field trips, in December 2015 and December 2016. For each sampling site, the water-sediment interface was collected using a sediment grab-sampler (Ponar, Rickly Hydrological Co.). Planktonic diatoms were collected with a phytoplankton net of 5 µm mesh while epyphytic species were scraped off submerged parts of macrophytes. All samples were preserved with ethanol. Physico-chemical parameters were measured in situ and major ionic composition was determined in the laboratory at CEREGE (Aix-en-Provence, France) (Table 1). In total, twenty-six samples were collected at Ounianga Kebir and seventeen samples at Ounianga Serir.

The preparation of permanent microscopic slides for diatom analyses was carried out at the Laboratoire Préparation Micropaléontologie at CEREGE in Aix-en-Provence (France). Water and surface sediments were successively treated with hot hydrochloric acid and hydrogen peroxide. After several rinsing/decanting periods with distilled water, an aliquot of the cleaned material was mounted in Naphrax to obtain permanent slides for light microscopy (LM). In CEREGE, diatom observations were done with a Nikon 80i light microscope, equipped with Differential Interference Contrast (Normarski) and an Optiflex digital camera, using a 100x immersion oil objective. Additionally, at Meise Botanic Garden (Belgium), diatoms slides were observed with an Olympus BX 51 microscope, equipped with Differential Interference Contrast (Normarski) and an Olympus UC30 digital camera, using an 100x oil immersion objective.

For scanning electron microscopy (SEM), aliquots of the oxidized material were mounted on aluminium stubs, air-dried and sputter-coated with 50 nm of gold (Balzers Union SCD 020). The stubs were studied at the Meise Botanic Garden with a Jeol JSM-7100FLV Field Emission Scanning Electron Microscope operating at 1 kV and 6.9 mm working distance. Frustules slightly constricted mid-valve and weakly twisted along the transapical axis. Valves lanceolate with slightly rostrate apices, length 20.5-59.5 µm (n = 100), width: 4.3-8.6 (10.5) µm (n = 70). Axial area narrow becoming somewhat wider towards the middle of the valve. Central area variable, asymmetric, expanded to the edge of the valve face and valve mantle on the secondary side. On the primary side, the central area can be absent with a single median stria more widely spaced, or can be present and then of variable width with one to three shortened striae of variable length and more widely spaced than the other striae. Raphe straight, filiform with weakly enlarged central raphe endings and deflected terminal raphe endings to the same direction (primary side). Striae weakly radiate, becoming convergent towards the poles; about (15) 16-19 striae (mean of 17) in 10 µm near the central area, and (17) 18-24 striae (mean of 20) towards the poles. Type: -CHAD. Borkou-Ennedi-Tibesti Region (BET): Ounianga Sérir, Lake Jabou, 19.00425°N, 20.53079°E, December 2016 (holotype BR!4635, Meise Botanic Garden, Belgium, the valve representing the holotype is here illustrated in Fig. 11). Registration : http://phycobank.org/102704 Ethymology: -The specific epithet "ouniangaensis" refers to the region of Ounianga, where the new species was first observed.

Ecology and distribution:

-This taxon was represented in Lakes Yoa, Mioji, Jabou, Teli, Agouta, Djara, Bedrim and Bokou. The conductivity in these lakes varies from 326 to 124,000 µS.cm -1 and the pH from 6.98 to 10.2.

SEM observations (Figs 20-31):

-Frustule weakly twisted along the transapical axis (Figs 23,24). Smooth transition between the valve face and the valve mantle. Striae uniseriate, 16-18 in 10 µm, becoming somewhat denser, 22 striae in 10 µm, near the apex, and continuous on the valve mantle. Striae weakly radiate throughout the largest part of the valve and becoming parallel near the apex. Voight discordance sometimes very distinct (Fig. 21, arrow). On the valve mantle of large valves, an additional stria is present in between most of the striae. Striae composed of slightly transapically elongated areolae, about 45 in 10 µm. Internally, areolae occluded by a hymen . Occasionally, a stria becomes biseriate near the axial area (Fig. 25, arrow). Axial area narrow, slightly widening towards the central area. Central area rectangular and of variable width, sometimes with a complete stauros (Fig. 22) but most often asymmetric and delimited by one to three striae. Shortened striae on the primary side longer than on the secondary side (Fig. 20); in the smallest valves sometimes not shortened at all (Fig. 25). Small isolated rounded areolae may be present in the central area on the secondary side (Fig. 25, arrows). Raphe straight, filiform. Central raphe endings externally straight, not enlarged (Fig. 25), internally bent towards the primary side, forming almost a right angle (Figs 30,31). Externally, terminal raphe endings broadly curved towards the primary side and continuing on the valve mantle with a slightly enlarged fissure 26); internally ending in a small helictoglossa (Figs. 28,29). Two girdle bands present. The valvocopula ornamented with a single row of small slightly elongated poroids, about 55 in 10 µm. (Figs 24,27). The other band bears also one row of poroids which are distinctly elongated (Fig. 27).

Discussion

The valves of the new species resemble very well the valves of Cymbella obtusa Gregory (1856: 5) as depicted by Round (1961b). Based on Round's drawing and assuming a magnification of 1000x, we found valves length of 22-43 µm, valve width of 7-8.5 µm and 11-14 striae in 10 µm mid-valve, becoming somewhat denser near the poles to (12) 14-16 striae in 10 µm. However, the valves represented by Round's drawings (Round 1961b) do not belong to Cymbella obtusa. Gregory (1856, p. 5, pl. 1 fig. 19) described Cymbella obtusa from Lochleven, Banffshire, Lanarkshire, Argyllshire, etc. in Scotland, United Kingdom. The taxon is regarded as a synonym of Cymbella aequalis W.Smith (in Greville 1855: 255) (Guiry & Guiry 2020), and is currently accepted as Kurtkrammeria aequalis (W.Smith) Bahls (2015: 173). Cymbella aequalis was also described from Scotland, namely from Ben-na-Muic-Dhui, Braemer. The girdle views as depicted by Round (1961b, Figs 44, 46) have the typical form of representatives of the genus Staurophora [START_REF] Cocquyt | Staurophora caljonii spec. nov. (Bacillariophyceae Anomoeoneidaceae), new halophilic diatom species from sub-recent lake deposits in Kenya[END_REF]). Moreover, the valve outline of Cymbella obtusa is totally different from the valves observed during our investigation and from the drawing in Round (1961b). On the other hand, Cymbella obtusa, of which valves are somewhat resembling the valves in studied material from Chad, was reported from Bornholm in Denmark by Foged (1982, Pl. 28 fig. 5).

Differences can be noted in the striation which is much coarser (12-13 striae in 10 µm) in Cymbella obtusa compared to the 16-19 striae in 10 µm in Staurophora ouniangaensis (Table 2).

Staurophora ouniangaensis

Staurophora vilamae Staurophora caljonii

Valve length (µm) 20.4-59.5 37. 1-48.3 17.5-39.4 Valve width (µm) 4.3-8.6 (10.5) 9.4-11. Table 2. Comparison of some morphological features in Staurophora ouniangaensis spec. nov. and morphologically related taxa according to this study and literature data.

The characteristics given by [START_REF] Desianti | Examination of the type materials of diatoms described by Hohn and Hellerman from the Atlantic Coast of the USA[END_REF] in their argumentation for the transfer of Navicula agmastriata Hohn & Helleman (1966: 125) to Staurophora, e.g., valve length and width, radiate striae composed of circular to transapically elongated areolae and an expanded central area into a transverse facia, are all presented in our new species. Moreover, the frustules are slightly twisted along the transapical axis, as was also observed in Staurophora caljonii [START_REF] Cocquyt | Staurophora caljonii spec. nov. (Bacillariophyceae Anomoeoneidaceae), new halophilic diatom species from sub-recent lake deposits in Kenya[END_REF].

Of the fifteen Staurophora species, only six have been reported from Africa (Guiry & Guiry 2020): S. amphioxys (W.Gregory) D.G.Mann as Stauroneis amphioxys W.Gregory from Gambia (Foged 1986); S. salina (W. Smith) Mereschkowsky as Stauroneis salina W.Smith from Gambia (Foged 1986) and South Africa (Giffen 1967); S. soodensis (Krasske) Bahls as Navicula soodensis Krasske from Gambia (Foged 1986) and South Africa (Giffen 1967); S. tackei (Hustedt) Bahls as Stauroneis palustris Hustedt from Sudan (Reinhold 1937); S. wislouchii (Poretzsky & Anisimoca) D.G.Mann from Ghana (Smith et al. 2015) and as Stauroneis wislouchii from Ghana (Foged 1966). S. caljonii is the only species which has actually not been reported from other sites than its type locality (Lake Sonachi) in Kenya [START_REF] Cocquyt | Staurophora caljonii spec. nov. (Bacillariophyceae Anomoeoneidaceae), new halophilic diatom species from sub-recent lake deposits in Kenya[END_REF].

Representativeness in present and past Ounianga Lakes

Today, Staurophora ouniangaensis is observed in lakes from Ounianga Kebir and Serir (Figure 32). From the forty-three samples collected in all lakes from the system, S. ouniangaensis is present in sixteen samples (Figure 32). It is well represented (> 40%) in Lakes Mioji, Jabou, Teli and Bokou (Figure 32). In Lake Teli, frustule preservation of S. ouniangaensis is poor and shows signs of dissolution, whereas in the others lakes, the frustules are well preserved. In these lakes, S. ouniangaensis is mainly associated with Gogorevia exilis (Kützing) [START_REF] Kulikovskiy | Gogorevia, a new monoraphid diatom genus for Achnanthes exigua and allied taxa (Achnanthidiaceae) described on the basis of an integrated molecular and morphological approach[END_REF]: 1610 (= Achnanthidium exiguum (Grunow) Czarnecki (1994:157)), Navicula globulifera Hustedt (1927: 164), Neidium dubium (Ehrenberg) Cleve (1894: 70), Nitzschia pusilla Grunow (1862: 579), Encyonopsis subminuta Krammer & E. Reichardt (in Krammer 1997: 96), Aulacoseira granulata (Ehrenberg) Simonsen (1979: 58), Anomoeoneis vitrea (Grunow) R.Ross (in Patrick & Reimer 1966: 380), A. sphaerophora Pfitzer (1871: 77), Mastogloia smithii Thwaites ex W.Smith 1856: 65), Gomphonema gracile Ehrenberg (1838: 217), Ulnaria ulna (Nitzsch) Compère (2001: 100) and Navicula radiosa Kützing (1844: 91). Staurophora ouniangaensis is also observed in Lake Yoa between few isolated valves (<1%) and 19% of the assemblages. It is mainly associated with Rhopalodia acuminata Krammer (in Lange-

0 25 50 75 100 Y o a -A 1 m Y O l 2 -1 6 Y O l 3 -1 6 M i o j -B m M i o j -C m M J l 1 -1 6 M J l 2 -1 6 M J l 3 -1 6 J A B l 1 -1 6 J A B l 2 -1 6 T L l 1 -1 6 A g o u -B m A G l 1 -1 5 D J l 1 -1 6 B e d -B m B o k -B m
Staurophora ouniangaensis (%)

Samples

Ounianga Kebir Ounianga Serir Bertalot & Krammer 1987: 75), Nitzschia pusilla and Anomoeoneis sphaerophora. In Lakes Bedrim, Agouta and Djara, only a few valves (<1%) were observed. From Ounianga lake district, Lakes Teli and Mioji are the most saline lakes, with conductivity measured at 124,000 µS.cm -1 and 105,100 µS.cm -1 respectively (Table 1). Lakes Jabou and Yoa present lower conductivity at 82,700 µS.cm -1 and 64,900 µS.cm -1 respectively, whereas Lake Bokou is the freshest lake at 326 µS.cm -1 (except spring water conductivity for instance sample Yoa-A1m, Table 1). This suggests that this species has a wide tolerance to water conductivity. Staurophora ouniangaensis is observed in the surface sediments of all lakes. In Lakes Yoa, Mioji, Agouta, Bedrim and Bokou, the new taxon is observed in different habitats, and in samples collected on macrophyths, and in Lake Bokou its was present in the water column (Table 1).

Based on the fourty three samples collected in all lakes from Ounianga, a transfer function was developed based on the relationships between the distribution of diatom species and environmental parameters using multivariate analysis (Remadji et al., in review). Conductivity is the variable explaining most of the variance in the diatom flora, allowing to reconstruct for each species their optimum and tolerance towards conductivity. For Staurophora ouniangaensis, its inferred optimum is estimated at 93,600 ± 6690 µS.cm -1 .

This species was also observed in the fossil record. Fossil diatom analysis conducted on four cores drilled in Lakes Yoa, Teli, Edem and Agouta (Kropelin et al., 2008;[START_REF] Van Der Meeren | Les lacs d'Ounianga: mieux comprendre leur dynamique hydrologique et écologique à long terme à travers l''étude intégrée de leurs archives sédimentaires et de la limnologie et l'écologie aquatique actuelles[END_REF] revealed that Staurophora ouniangaensis is only present in the upper half meter of the core in Lake Teli. In this section the frustules are progressively dissolved downwards. Thereafter, from 0.6 m up to the end of the core (3.8 m) S. ouniangaensis is absent. It is probably completely dissolved due to increased salinity.

The Ounianga region in Chad, being unique by lying in the widest and hottest desert in the world, preserved several lakes because of groundwater discharge from nubian sandstone. The lakes span a wide range of conductivity from fresh to hypersaline waters. Investigations in their modern diatom content (water column and surface sediments) evidenced a new species, described as Staurophora ouniangaensis. This species is observed in a wide range of conductivity today (326 to 124,000 µS.cm-1), whereas during the past, it is up to no preserved only in one of the highest saline lake. Since not all Ounianga lakes have been drilled, it is quite possible that Staurophora ouniangaensis can also be observed elsewhere in these unique aquatic environments.

Figure 1 .

 1 Figure 1. Location of Ounianga lakes district and studied area. A. Locations Lakes Ounianga in Chad. B. Picture of Lake Yoa (December 2016, @ F. Sylvestre). C. Location of the two groups of lakes. D. The lakes of Ounianga Kebir and location of studied sites (red dots). E. The lakes of Ounianga Serir and location of studied sites (red dots). Drawings based on satellite images (Google Earth Pro 2021).

Figures 2 -

 2 Figures 2-19. Staurophora ouniangaensis Rirongarti, Cocquyt, Paillès & Sylvestre sp. nov. LM, DIC. Valves and frustules from type material from Lake Jabou, Ouinanga Sérir, Chad, holotype slide BR4635. Figs 2-15. Valves views showing the size diminution series. Figs 16-19. Frustules in girdle views. The valve shown in Fig. 11 represents the holotype. Scale bar = 10 µm.

Figures 20 -

 20 Figures 20-25. Staurophora ouniangaensis Rirongarti, Cocquyt, Paillès & Sylvestre sp. nov. SEM, from type material from Lake Jabou, Ouinanga Sérir, Chad, external views. Figs. 20-23. Valves views showing the uniseriate striae, the narrow axial area which is slightly widening towards the rectangular central area. Fig. 21. Valve with distinct Voight discordance (arrow). Figs 23, 24. weakly twisted frustules along the transapical axis. Fig. 25. Detail of the central area, and the uniseriate striae; rarely a stria is partly biseriate (arrow). Scale bar fig. 25 = 1 µm, figs 20-24 = 10 µm.

  , expanded to the valve face edge on the secondary side Absent with a single median more widely spaced stria, if present variable width with one to three more widely spaced striae of variable length Highly variable

Figure 32 .

 32 Figure 32. Relative abundance (%) of Staurophora ouniangaensis sp. nov. in Lakes Yoa (Yoa, YO), Mioji (Mioj), Jabou (JAB), Teli (TL), Agouta (Agou, AG), Djara (DJ), Bedrim (Bed) Bokou (Bok).

TABLE 1 .

 1 Studied samples in which Staurophora ouniangaensis sp. nov. was observed, with sample name and type of sample (M: macrophytes, S: surface sediment), location (latitude, longitude), month/year of sampling, physical parameters measured in the field (conductivity in µS•cm -1 , pH, and lake water temperature in °C) and chemical parameters analysed in the laboratory (alkalinity, major ions)

	Lake		Yoa	Mioji	Jabou	Teli	Agouta	Djara	Bedrim	Bokou
	Sample name	Yoa-A1m (M) YOl2-16(S)	Mioj-Bm (M)	JABl1-16 (S)	TL1-16 (S) Agou-Bm (M)	AGl1-15 (S) DJl1-16 (S)	Bed-Bm(M) Bok-Bm (M)
	(sample type)		YOl3-16(S)	Mioj-Cm (M)	JABl2-16 (S)
				MJl1-16 (S)
				MJl2-16 (S)
				MJl3-16 (S)
	Latitude (°N)	19.047562	19.047562	19.01072	19.00425	18.91893	18.921258	18.921258	18.917662	18.91709	18.91546
	Longitude (°E)	20.492858	20.492858	20.51639	20.53079	20.87196	20.88858	20.88858	20.89364	20.90261	20.91156
	Month/Year	12/2016	12/2015	12/2016	12/2016	12/2015	12/2016	12/2016	12/2016	12/2016	12/2016
	sampling
	Alkalinity	84	48800	25956	118177	46726	62	1013	71	29	126
	(mol.L -1 )
	Cl (mg.L -1 )	47	9656	21557	105867	23817	250	2221	126	65	12
	SO4 (mg.L -1 )	37	15744	10606	79075	12750	129	142	4	63	27
	Ca (mg.L -1 )	11	159	231	159	159	30	37	26	43	44
	Mg (mg.L -1 )	5	19	19	19	19	69	47	48	15	6
	Na (mg.L -1 )	50	22425	29467	140192	34500	209	202	127	60	12
	K (mg.L -1 )	4	3186	2899	25935	10920	46	47	32	10	2
	Conductivity	344	64900	124000	82700	105100	1807	1833	1343	737	326
	(µS•cm -1 )
	pH	6.98	10.11	9.03	8.2	10.2	8.33	8.1	7.97	8.03	7.77
	Temperature	31.2	26.6	23.76	30.84	25	23.6	17.4	23.1	24	23.3
	(°C)

Acknowledgements

This works was carried out within the framework of the program 'Grands Ecosystèmes Lacustres Tchadiens' (GELT) funded by the French Ministry of Foreign Affairs and coordinated by the French Embassy in Chad and the Centre National de Recherche et du Développement in Chad (CNRD). We also thank IRD for having partly funded this work. We thank the French Embassy in Chad, the Centre National de Recherche et Développement (CNRD) in Chad and the University of N'Djamena for their logistic and technical aid during field missions.