Search

In the present study, Au-surfactant core-shell colloidal nanoparticles (NPs) with controlled dimension and composition were synthesized by sacrificial anode electrolysis. Transmission electron microscopy (TEM) revealed that Au NPs core diameter is between 8 and 12 nm, as a function of the electrosynthesis conditions. Moreover, surface spectroscopic characterization by X-ray photoelectron spectroscopy (XPS) analysis confirmed the presence of nanosized gold phase. Controlled amounts of Au NPs were then deposited electrophoretically on carbon nanotube (CNT) networked films. The resulting hybrid materials were morphologically and chemically characterized using TEM, SEM (scanning electron microscopy) and XPS analyses, which revealed the presence of nanoscale gold, and its successful deposition on CNTs. Au NP/CNT networked films were tested as active layers in a two-pole resistive NO2 sensor for sub-ppm detection in the temperature range of 100–200 °C. Au NP/CNT exhibited a p-type response with a decrease in the electrical resistance upon exposure to oxidizing NO2 gas and an increase in resistance upon exposure to reducing gases (e.g. NH3). It was also demonstrated that the sensitivity of the Au NP/CNT-based sensors depends on Au loading; therefore, the impact of the Au loading on gas sensing performance was investigated as a function of the working temperature, gas concentration and interfering gases.

Controlled amounts of colloidal Au nanoparticles (NPs), electrochemically presynthesized, were directly deposited on MWCNTs sensor devices by electrophoresis. Pristine and Au-functionalized MWCNT networked films were tested as active layers in resistive gas sensors for detection of pollutant gases. Au-modified CNT-chemiresistor demonstrated higher sensitivity to NO2 detecting up to sub-ppm level compared to pristine one. The investigation of the cross-sensitivity towards other pollutant gases revealed the decrease of the sensitivity to NO2 with the increase of Au content, and, on the other side, the increase of that to H2S; therefore the fine tune of the metal loading on CNTs has allowed to control not only the gas sensitivity but also the selectivity towards a specific gaseous analyte. Finally, the sensing properties of Audecorated CNT sensor seem to be promising in environmental and automotive gas sensing applications, based on low power consumption and moderate operating temperature. © 2015 Materials Research Society.

In this paper we report on Surface Acoustic Wave (SAW) gas sensors based on quartz two-port resonators configured as oscillators at resonant frequency of 915 MHz. Nanowires (NW) of semiconducting tin dioxide (SnO 2 ) have been grown by Vapor Phase (VP) process and used as filler in a nanocomposite layer to fabricate a highly-sensitive nanomaterial for gas detection, at room temperature. The nanocomposite layer consisting of an organic host-matrix of cadmium arachidate (CdA) and a weight-tailored filler of SnO 2 NW has been deposited as thin film onto SAW resonators by means of the molecular engineering Langmuir-Blodgett (LB) technique. SAW gas sensors performance was investigated in presence of ppm-level of ethanol, methanol, ethylacetate, toluene, at room temperature. The results demonstrate good sensitivity to vapors under test at ppm-level and a SAW gas response tuned by the weight-content of filler of SnO 2 NW in the LB nanocomposite layer.

International audience

In recent years, several research projects have investigated the use of low-cost devices for air pollution monitoring. As a result of these activities, various air quality monitoring systems have been developed following diverse approaches and methods. However, in most cases, these monitoring systems lack flexibility, extendibility, and openness. The device presented in this article provides a cost-effective, expandable, flexible, open-source solution. SentinAir has been designed to act as a portable air quality monitoring unit and also for facilitating the on-field evaluation and calibration of air quality sensors. The high grade of flexibility featuring this tool enables the data acquisition from heterogeneous kinds of devices deployed far from the laboratory facilities, even in areas featured by a weak or unstable Internet connection. Moreover, the system proposed in this article provides a reasonably easy way to integrate a wide range of sensors or devices produced by diverse manufacturers, offering a tool that is not bound to the use of a limited and fixed set of sensors or devices. The modularity approach followed in SentinAir design constitutes another key factor to consider: it allows each user to easily adapt this device to his requirements. This system is therefore capable of providing a robust framework for environmental monitoring activities to researchers or low-skilled end-users.

Atmospheric pollution is one of the biggest concerns for public health. Air quality monitoring is currently performed by expensive and cumbersome monitoring stations. For this reason, they are sparse, and therefore, inadequate to provide enough accurate information on the personal exposure to pollutant gases. The current worldwide trend to address this issue consists in the use of low-cost small gas sensors, already available on the market, with a wide range of costs and performances. However, the performance of these sensors is heavily affected by the environmental conditions of the specific location used for their deployment. For this reason, it is of fundamental importance to test them in real-world scenarios. Field evaluation of sensor performance could be a challenging task because, on the one hand, they have heterogeneous output signals, and on the other hand, there is no widely shared evaluation protocol. The SentinAir system has been designed and developed to facilitate this task. It can carry out performance evaluations for any type of sensor thanks to its configurable and adaptable sensing capability, multiple wireless sensor network compatibility, flexibility, and usability. In order to evaluate SentinAir capabilities and functionalities, the performances of CO2, NO2, and O3 sensors were tested in real-world scenarios against reference instruments. To the best of our knowledge, there is no previous study providing information about the performance of SP-61 (O3 sensor), IRC-A1 (CO2 sensor), and TDS5008 (CO2 sensor) achieved during on-field tests. On the contrary, results obtained by OXB431 (O3 sensor) and NO2B43F (NO2 sensor) are consistent with the ones shown in previous studies carried out in similar conditions. During validation tests, we have found R2=0.507 for the best performing NO2 sensor, and R2=0.668 for the best O3 sensor. Concerning the indoor experiment, the best CO2 sensor performance showed an excellent R2=0.995. In conclusion, the effectiveness of this tool in evaluating the performance of heterogeneous gas sensors in different real-world scenarios has been demonstrated. Therefore, we anticipate that the use of SentinAir will facilitate researchers to carry out these challenging tasks.

SentinAir system has been designed and developed to perform data acquisition from heterogeneous devices, sensors, or instruments. Although designed for facilitating the on-field evaluation and calibration of air quality sensors, it can also be used to acquire data from various kinds of devices deployed far from the laboratory where the Internet connection is weak or unstable. SentinAir, written in Python, can be expanded and used with a wide range of sensors or devices for a variety of field experiments.

The EuNetAir Joint Exercise focused on the evaluation and assessment of environmental gaseous, particulate matter (PM) and meteorological microsensors versus standard air quality reference methods through an experimental urban air quality monitoring campaign. This work presents the second part of the results, including evaluation of parameter dependencies, measurement uncertainty of sensors and the use of machine learning approaches to improve the abilities and limitations of sensors. The results confirm that the microsensor platforms, supported by post processing and data modelling tools, have considerable potential in new strategies for air quality control. In terms of pollutants, improved correlations were obtained between sensors and reference methods through calibration with machine learning techniques for CO (r = 0.13–0.83), NO (r = 0.24–0.93), O (r = 0.22–0.84), PM10 (r = 0.54–0.83), PM2.5 (r = 0.33–0.40) and SO (r = 0.49–0.84). Additionally, the analysis performed suggests the possibility of compliance with the data quality objectives (DQO) defined by the European Air Quality Directive (2008/50/EC) for indicative measurements.

A thin-film bulk acoustic resonator (TFBAR) based on a vibrating membrane of AlN/Si3N4 has been fabricated onto a silicon substrate and functionally characterized as gas sensor at a resonating frequency of 1.045 GHz. This novel TFBAR-based gas sensor has been functionalized by a sensing nanocomposite layer, prepared by a Langmuir-Blodgett (LB) technique, of single-walled carbon nanotubes (SWCNTs) embedded in a host matrix of organic material of cadmium arachidate. High-performance gas detection at room temperature of a SWCNT-coated TFBAR sensor has been reported. The sensing device exhibits high sensitivity (e.g., acetone: 12 kHz/ppm; ethylacetate: 17.3 kHz/ ppm), fast response (within 2-3 min), slow reversibility (within 1 h), and good repeatability (≤5% variation) of response toward tested organic vapors of acetone, ethylacetate, and toluene. © 2008 IEEE.

This work presents the “City Dynamics and Smart Environment” activities of the Smart Ring project, a model for the smart city, based on the integration of sustainable urban transport services and environmental monitoring over a 4–5-km circular path, the “Smart Ring”, around the historical center of l’Aquila (Italy). We describe our pilot experience performed during an experimental on-demand public service electric bus, “SmartBus”, which was equipped with a multi-parametric air quality low-cost gas electrochemical sensor platform, “NASUS IV”. For five days (28–29 August 2014 and 1–3 September 2014), the sensor platform was installed inside the SmartBus and measured air quality gas compounds (nitrogen dioxide, carbon oxide, sulfur dioxide, hydrogen sulfide) during the service. Data were collected and analyzed on the bases of an air quality index, which provided qualitative insights on the air status potentially experienced by the users. The results obtained are in agreement with the synoptic meteorological conditions, the urban background air quality reference measurements and the potential traffic flow variations. Furthermore, they indicated that the air quality status was influenced by the gas component NO 2 , followed by H 2 S, SO 2 and CO. We discuss the features of our campaign, and we highlight the potential, limitations and key factors to consider for future project designs.

The 1st EuNetAir Air Quality Joint Intercomparison Exercise organized in Aveiro (Portugal) from 13th–27th October 2014, focused on the evaluation and assessment of environmental gas, particulate matter (PM) and meteorological microsensors, versus standard air quality reference methods through an experimental urban air quality monitoring campaign. The IDAD-Institute of Environment and Development Air Quality Mobile Laboratory was placed at an urban traffic location in the city centre of Aveiro to conduct continuous measurements with standard equipment and reference analysers for CO, NOx, O3, SO2, PM10, PM2.5, temperature, humidity, wind speed and direction, solar radiation and precipitation. The comparison of the sensor data generated by different microsensor-systems installed side-by-side with reference analysers, contributes to the assessment of the performance and the accuracy of microsensor-systems in a real-world context, and supports their calibration and further development. The overall performance of the sensors in terms of their statistical metrics and measurement profile indicates significant differences in the results depending on the platform and on the sensors considered. In terms of pollutants, some promising results were observed for O3 (r2: 0.12–0.77), CO (r2: 0.53–0.87), and NO2 (r2: 0.02–0.89). For PM (r2: 0.07–0.36) and SO2 (r2: 0.09–0.20) the results show a poor performance with low correlation coefficients between the reference and microsensor measurements. These field observations under specific environmental conditions suggest that the relevant microsensor platforms, if supported by the proper post processing and data modelling tools, have enormous potential for new strategies in air quality control. © 2016 Elsevier Ltd, The authors would like to acknowledge the support of COST Action TD 1105 – European Network on New Sensing Technologies for Air-Pollution Control and Environmental Sustainability – EuNetAir. The authors would like to acknowledge the support of the Municipality of Aveiro. The authors wish to acknowledge the support of M. Gerboles of the Institute for Environment and Sustainability of the Joint Research Centre of the European Commission on the evaluation of the sensors. The UCL authors acknowledge the FP7 EU SOIHITS project for funding (grant agreement no 288481 ) and especially the partners UCAM (F. Udrea), CCMOSS (S. Z. Ali, F. Chowdhury) and UCL (D. Flandre). The IDAEA-CSIC authors would like to acknowledge AQMesh for kindly providing the AQMesh pods. Support is acknowledged to Generalitat de Catalunya 2014 SGR33 . The NILU authors would like to acknowledge ENVIRA Ingenieros Asesores for participating in the campaign with the NanoEnvi platform. Appendix A

This paper gives a brief report on preliminary real-world measurements by low-cost gas sensorsystems for air quality monitoring in the framework of the Italian national project RES-NOVAE - Networks Buidings Streets: New Challenging Objectives for Environment and Energy. Measurements were performed by low-cost electrochemical gas sensors (CO, NO2, O3, SO2), optical particle counter/detector (PM1.0, PM2.5, PM10), NDIR infrared sensor (CO2), photo-ionisation detector (total VOCs), including miniaturized sensors for meteorological parameters (temperature, relative humidity). The sensors are running and installed in the city of Bari (Italy) to assess the performance during a campaign of several months of operation in the framework of sustainable innovation and citizen science in the smart cities. The first results indicate that these solutions are promising for air quality monitoring to address data quality objective of Indicative Measurements (Directive 2008/50/EC) [1].