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Crowd-sourced air quality studies: A review of the literature & portable sensors
Abstract
Development of low-cost, portable, and low-power devices for monitoring airborne pollutants is a crucial step towards developing improved air quality models and better quantitating the health effects of human and animal exposure. This review article summarizes recent developments in the field within the context of the establishment/expansion of high spatial and temporal resolution air quality monitoring networks. Current ‘crowd-sourced’ monitoring efforts are summarized, and recent advances in chemical sensors required for these networks are described. No ‘perfect’ sensing platform, that meets the requirements of low-cost, portability, selectivity, and sensitivity has yet been achieved. This highlights the need for investment in the fundamental analytical chemistry of the sensing platforms required to achieve such ‘smart-cities.’ Such investment should include the development of new sensor technologies, and provide for calibration and performance validation for systems enacted. In addition to summarizing the current state-of-the-art, reflections on future needs are also offered.
... Furthermore, MOS and electrochemical gas sensors, which have miniaturized size, low power consumption and cost, are suitable for indoor air evaluation (White et al., 2012). Non-dispersive infrared sensor can detect gases with infrared activity, such as CH 4 and CO 2 (Thompson, 2016). Photo ionization detectors (PID) are commonly used for VOCs detection due to its low detection limits (ppb to ppm) (Thompson, 2016;Pang et al., 2019). ...
... Non-dispersive infrared sensor can detect gases with infrared activity, such as CH 4 and CO 2 (Thompson, 2016). Photo ionization detectors (PID) are commonly used for VOCs detection due to its low detection limits (ppb to ppm) (Thompson, 2016;Pang et al., 2019). ...
People generally spend most of their time indoors, making indoor air quality be of great significance to human health. Large spatiotemporal heterogeneity of indoor air pollution can be hardly captured by conventional filter-based monitoring but real-time monitoring. Real-time monitoring is conducive to change air assessment mode from static and sparse analysis to dynamic and massive analysis, and has made remarkable strides in indoor air evaluation. In this review, the state of art, strengths, challenges, and further development of real-time sensors used in indoor air evaluation are focused on. Researches using real-time sensors for indoor air evaluation have increased rapidly since 2018, and are mainly conducted in China and the USA, with the most frequently investigated air pollutants of PM2.5. In addition to high spatiotemporal resolution, real-time sensors for indoor air evaluation have prominent advantages in 3-dimensional monitoring, pollution peak and source identification, and short-term health effect evaluation. Huge amounts of data from real-time sensors also facilitate the modeling and prediction of indoor air pollution. However, challenges still remain in extensive deployment of real-time sensors indoors, including the selection, performance, stability, as well as calibration of sensors. In future, sensors with high performance, long-term stability, low price, and low energy consumption are welcomed. Furthermore, more target air pollutants are also expected to be detected simultaneously by real-time sensors in indoor air monitoring.
... The development of low-cost chemical and physical sensors for air quality monitoring has been pursued using a variety of approaches [10][11][12]. Solid-state sensors can be classified as metal oxide (MOX) semiconductors (e.g., Aeroqual Air Quality Devices) and amperometric sensors [13]. The interactions with the analyte lead to changes in the device's electrical conductivity or output current. ...
... Additionally, these sensors are easily attached to electronic devices to store and transmit the obtained data. In this sense, many recently published papers have proposed deploying solid-state sensors to build an automated air quality network [11,[15][16][17]. The main drawbacks of MOX sensors rely on the operating temperature (usually higher than 200 • C), the time required to achieve signal stability, the influence of relative humidity variations, and the lack of calibrations [14]. ...
Air quality monitoring networks are challenging to implement due to the bulkiness and high prices of the standard instruments and the low accuracy of most of the described low-cost approaches. This paper presents a low-cost, automated, self-powered analytical platform to determine the hourly levels of O3 and NO2 in urban atmospheres. Atmospheric air was sampled at a constant airflow of 100 mL min−1 directly into vials containing 800 µL of indigotris sulfonate and the Griess–Saltzman reagent solutions for ozone and nitrogen dioxide, respectively. The analysis holder, containing a light-emitting diode and a digital light sensor, enabled the acquisition of the analytical signal on-site and immediately after the sampling time. The data were transmitted to a laptop via Bluetooth, rendering remote hourly monitoring. The platform was automated using two Arduino Uno boards and fed with a portable battery recharged with a solar panel. The method provided a limit of detection of 5 and 1 ppbv for O3 and NO2, respectively, which is below the maximum limit established by worldwide regulatory agencies. The platform was employed to determine the levels of both pollutants in the atmosphere of two Brazilian cities, in which one of them was equipped with an official air quality monitoring station. Comparing the results of both techniques revealed suitable accuracy for the proposed analytical platform. Information technology (IT) allied to reliable chemical methods demonstrated high potential to create air quality monitoring networks providing valuable information on pollutants’ emissions and ensuring safety to the population.
... A necessary condition for using catalytic bead sensors is the presence of oxygen, since it is required for the burning process. With less than 10 seconds, the response time of catalytic bead sensors is relatively short [15]. The average lifetime of these sensors is commonly 5 years [16], which can be significantly reduced by catalyst poisoning, whereby the catalysts are partially or completely deactivated by gases containing sulfides, halides, and silicones [15]. ...
... With less than 10 seconds, the response time of catalytic bead sensors is relatively short [15]. The average lifetime of these sensors is commonly 5 years [16], which can be significantly reduced by catalyst poisoning, whereby the catalysts are partially or completely deactivated by gases containing sulfides, halides, and silicones [15]. A disadvantage is their low sensitivity in the percentage range, since relatively high gas concentrations are necessary for a sufficiently high heat release. ...
Chemical, analytical and biological laboratories use a variety of different solvents and gases. Many of these compounds are harmful or even toxic to laboratory personnel. Permanent monitoring of the air quality is therefore of great importance regarding the greatest possible occupational safety and the detection of dangerous situations in the work process. An increasing need exists for the development and application of small and portable sensor solutions that enable personal monitoring and that can be flexibly adapted to different environments and situations. Different sensor principles are available for the detection of gases and solvent vapors, which differ in terms of their selectivity and sensitivity. Besides simple sensing elements, integrated sensors and smart sensors are increasingly available, which, depending on their scope of functions, require a distinct effort in integration. This chapter gives an overview of available sensors and their integration options, and describes ready-to-use sensor systems for personal monitoring in life science laboratories.
... An increasing number of evaluations of MCS and LCS as well as of networks based on such sensors are being performed, and conclusions are available from these studies such as Thompson (2016), Morawska et al. (2018), and Karagulian et al. (2019). It is well-known that these sensors suffer from drift and ageing (Brattich et al., 2020). ...
... Applications of LCS as well as networks based on such sensors have increased over the past decade (e.g. Thompson, 2016;Karagulian et al., 2019;Barmpas et al., 2020;Schäfer et al., 2021). These applications have also highlighted the need for proper evaluation, quality control, and calibration of these sensors. ...
This review provides a community's perspective on air quality
research focusing mainly on developments over the past decade. The article
provides perspectives on current and future challenges as well as research
needs for selected key topics. While this paper is not an exhaustive review
of all research areas in the field of air quality, we have selected key
topics that we feel are important from air quality research and policy
perspectives. After providing a short historical overview, this review
focuses on improvements in characterizing sources and emissions of air
pollution, new air quality observations and instrumentation, advances in air
quality prediction and forecasting, understanding interactions of air
quality with meteorology and climate, exposure and health assessment, and
air quality management and policy. In conducting the review, specific
objectives were (i) to address current developments that push the boundaries
of air quality research forward, (ii) to highlight the emerging prominent
gaps of knowledge in air quality research, and (iii) to make recommendations to guide the direction for future research within the wider
community. This review also identifies areas of particular importance for
air quality policy. The original concept of this review was borne at the
International Conference on Air Quality 2020 (held online due to the COVID
19 restrictions during 18–26 May 2020), but the article incorporates a wider
landscape of research literature within the field of air quality science. On
air pollution emissions the review highlights, in particular, the need to
reduce uncertainties in emissions from diffuse sources, particulate matter
chemical components, shipping emissions, and the importance of considering
both indoor and outdoor sources. There is a growing need to have integrated
air pollution and related observations from both ground-based and remote
sensing instruments, including in particular those on satellites. The research
should also capitalize on the growing area of low-cost sensors, while
ensuring a quality of the measurements which are regulated by guidelines.
Connecting various physical scales in air quality modelling is still a
continual issue, with cities being affected by air pollution gradients at
local scales and by long-range transport. At the same time, one should allow
for the impacts from climate change on a longer timescale. Earth system
modelling offers considerable potential by providing a consistent framework
for treating scales and processes, especially where there are significant
feedbacks, such as those related to aerosols, chemistry, and meteorology.
Assessment of exposure to air pollution should consider the impacts of
both indoor and outdoor emissions, as well as application of more sophisticated,
dynamic modelling approaches to predict concentrations of air pollutants in
both environments. With particulate matter being one of the most important
pollutants for health, research is indicating the urgent need to understand,
in particular, the role of particle number and chemical components in terms
of health impact, which in turn requires improved emission inventories and
models for predicting high-resolution distributions of these metrics over
cities. The review also examines how air pollution management needs to
adapt to the above-mentioned new challenges and briefly considers the
implications from the COVID-19 pandemic for air quality. Finally, we provide recommendations for air quality research and support for policy.
... An increasing number of evaluations of MCS and LCS as well as of networks based on such sensors are being performed and conclusions are available from these studies such as Thompson (2016), Morawska et al. suppl., (2018), Karagulian et al., (2019). It is well-known that these sensors suffer from drift and aging (Brattich et al., 2020). ...
... Applications of LCS as well as networks based on such sensors have increased over the past decade (e.g., Thompson 2016, Karagulian et al., 2019, Schäfer et al., 2021. These applications have also highlighted the need for proper evaluation, quality control and calibration of these sensors. ...
This review provides a community's perspective on air quality research focussing mainly on developments over the past decade. The article provides perspectives on current and future challenges as well as research needs for selected key topics. While this paper is not an exhaustive review of all research areas in the field of air quality, we have selected key topics that we feel are important from air quality research and policy perspectives. After providing a short historical overview, this review 40 focuses on improvements in characterising sources and emissions of air pollution, new air quality observations and instrumentation, advances in air quality prediction and forecasting, understanding interactions of air quality with meteorology https://doi.org/10.5194/acp-2021-581 Preprint. Discussion started: 23 September 2021 c Author(s) 2021. CC BY 4.0 License. 2 and climate, exposure and health assessment, and air quality management and policy. In conducting the review, specific objectives were (i) to address current developments that push the boundaries of air quality research forward, (ii) to highlight the emerging prominent gaps of knowledge in air quality research and (iii) and to make recommendations to guide the direction 45 for future research within the wider community. This review also identifies areas of particular importance for air quality policy. The original concept of this review was borne at the International Conference on Air Quality 2020 (held online due to the COVID 19 restrictions during 18-26 May 2020), but the article incorporates a wider landscape of research literature within the field of air quality science. On air pollution emissions the review highlights, in particular, the need to reduce uncertainties in emissions from diffuse sources, particulate matter chemical components, shipping emissions and the importance of considering 50 both indoor and outdoor sources. There is a growing need to have integrated air pollution and related observations from both ground based and remote sensing instruments, including especially those on satellites. The research should also capitalize on the growing area of lower cost sensors, while ensuring a quality of the measurements which are regulated by guidelines. Connecting various physical scales in air quality modelling is still a continual issue, with cities being affected by air pollution gradients at local scales and by long range transport. At the same time, one should allow for the impacts from climate change 55 on a longer timescale. Earth system modelling offers considerable potential by providing a consistent framework for treating scales and processes, especially where there are significant feedbacks, such as those related to aerosols, chemistry and meteorology. Assessment of exposure to air pollution should consider both the impacts of indoor and outdoor emissions, as well as application of more sophisticated, dynamic modelling approaches to predict concentrations of air pollutants in both environments. With particulate matter being one of the most important pollutants for health, research is indicating the urgent 60 need to understand, in particular, the role of particle number and chemical components in terms of health impact, which in turn requires improved emission inventories and models for predicting high resolution distributions of these metrics over cities. The review also examines, how air pollution management needs to adapt to the above-mentioned new challenges and briefly considers the implications from the COVID-19 pandemic for air quality. Finally, we provide recommendations for air quality research and support for policy. 65 Dedication We wish to dedicate this article to the following eminent scientists who made immense contributions to the science of air quality and its impacts: Paul
... Most of the published reviews focused on the analysis of the behaviour of LC sensors during the calibration/validation processes (e.g., Alfano et al., 2020;Borrego et al., 2016;Delaine et al., 2019;Karagulian et al., 2019;McKercher et al., 2017;Rai et al., 2017), often highlighting the use of advanced statistical techniques (e.g., machine-learning algorithms) to improve their performance (e.g., Concas et al., 2021;Liang, 2021;Maag et al., 2018;Narayana et al., 2022). A number of reviews also described the characteristics of LC sensors/monitors for measuring particulate matter (e.g., Lung et al., 2022;Snyder et al., 2013;Yi et al., 2015) or gaseous pollutants (e.g., Baron & Saffell, 2017;Spinelle et al., 2017), or focused on crowd-sourced air quality studies (Thompson, 2016). Other reviews offered an overview of the relevant applications involving LC sensors or monitors (e.g., Clements et al., 2017;Kumar et al., 2015), or of the advances reached in their implemented technology (Idrees & Zheng, 2020;Mao et al., 2019;Morawska et al., 2018). ...
The application of low‐cost air quality monitoring networks has substantially grown over the last few years, following the technological advances in the production of cheap and portable air pollution sensors, thus potentially greatly increasing the limited spatial information on air quality conditions provided by traditional stations. However, the use of low‐cost air quality sensors still presents many limitations, mostly related to the reliability of their measurements. Despite the increasing number of papers focusing on these issues, some of the challenges connected to the use of low‐cost air quality sensors are still poorly investigated and understood, considering in particular those related to long‐term applications of low‐cost air quality networks and their integration within the reference air quality monitoring system. The present review aims at filling this gap, by analysing the characteristics of low‐cost air quality monitoring networks that were run across long‐term field campaigns, including their geographical location, the pollutants monitored, the type and number of stations employed, and the length of the field campaign, with a particular attention on assessing the aims for their deployment and on the evaluation of their integration within official air quality monitoring networks. Moreover, a critical analysis of the most insightful suggestions and recommendations delivered in the literature, as well as of the relevant critical issues, is presented, highlighting still open research areas and outlining future challenges.
... [68] An overview of VOCs detection sensors, discussing their designs, performance parameters, and future improvements. [69] This article highlights the progress and future demands in creating affordable, portable air pollutant monitors, underlining the role of crowdsourced monitoring and sensor technology in advancing 'smart cities'. [70] This review paper analyzes how various factors alter the sensitivity of conductometric semiconducting metal oxide gas sensors. ...
... [68] An overview of VOCs detection sensors, discussing their designs, performance parameters, and future improvements. [69] This article highlights the progress and future demands in creating affordable, portable air pollutant monitors, underlining the role of crowdsourced monitoring and sensor technology in advancing 'smart cities'. [70] This review paper analyzes how various factors alter the sensitivity of conductometric semiconducting metal oxide gas sensors. ...
Air pollution has become a significant health, environmental and economic problem worldwide. The conventional approach of deploying fixed high-end air quality monitoring stations provides accurate measurements but can be expensive to deploy and maintain. As a result, the stations are typically deployed in a few strategic locations with various spatial interpolation or prediction models to estimate the air quality values from unsampled points. Recently, drive-by air quality sensing has emerged as a popular approach due to its dynamic nature, high spatial coverage, and low operational costs while providing high-resolution data. At the same time, drive-by sensing has introduced a range of novel research challenges in terms of spatial and temporal coverage, mobile sensor calibration, and deployment strategies. This paper provides a systematic review and analysis of the recent work in this area, focusing on vehicular platforms, deployment strategies, primary challenges, and promising research directions.
... However, these devices are time-consuming, expensive and unwieldy. Moreover, many measurement devices are needed to characterize the spread of aerosols in large rooms in detail [15][16][17][18][19][20]. ...
The measurement and assessment of indoor air quality in terms of respirable particulate constituents is relevant, especially in light of the COVID-19 pandemic and associated infection events. To analyze indoor infectious potential and to develop customized hygiene concepts, the measurement monitoring of the anthropogenic aerosol spreading is necessary. For indoor aerosol measurements usually standard lab equipment is used. However, these devices are time-consuming, expensive and unwieldy. The idea is to replace this standard laboratory equipment with low-cost sensors widely used for monitoring fine dust (particulate matter—PM). Due to the low acquisition costs, many sensors can be used to determine the aerosol load, even in large rooms. Thus, the aim of this work is to verify the measurement capability of low-cost sensors. For this purpose, two different models of low-cost sensors are compared with established laboratory measuring instruments. The study was performed with artificially prepared NaCl aerosols with a well-defined size and morphology. In addition, the influence of the relative humidity, which can vary significantly indoors, on the measurement capability of the low-cost sensors is investigated. For this purpose, a heating stage was developed and tested. The results show a discrepancy in measurement capability between low-cost sensors and laboratory measuring instruments. This difference can be attributed to the partially different measuring method, as well as the different measuring particle size ranges. The determined measurement accuracy is nevertheless good, considering the compactness and the acquisition price of the low-cost sensors.
... The system can achieve a 50 ppt detection limit with a 4.7 W power [17]. The development of using NDIR to measure nitrides was summarized in detail in JE Thompson's work [18]. In 2020, Fei Zheng et al. demonstrated a TDLAS-based nitric oxide (NO) gas sensor with a quantum cascade laser and reached a detection limit of 28 ppb over 180 s integration time [19]. ...
In this paper, a compact ambient gas sensor with an optimized photoacoustic cell is reported. The relationship between the geometric dimensions (usually radius and length) of the photoacoustic cell (PAC) and the acoustic signal was studied through theoretical and finite element analysis. Then an optimized H-type PAC with a volume of 80 mm × 30 mm × 30 mm was machined out. The gas capacity is only 18.85 millilitres. The performance of the photoacoustic cell has been verified experimentally by the detection of nitrogen dioxide (NO2) standard gas. With an electret microphone and an economically self-designed 450 nm laser module, the detection of NO2 concentration was executed. The experimental results show good linearity with a fitting R-square of 0.9991. With an SNR (signal-to-noise ratio) of 41.247, the minimum detection limit (MDL) of the system can reach 4.85 ppb (1σ). With an analysis of allan variance, the MDL can achieve 0.11 ppb with a 228 s integration time. By replacing the light source, the system shows great potential for sensitive and compact detectors for other ambient gasses as well.
... Non-expert groups of citizens can fund the projects to become the major stakeholders in such monitoring and, theoretically, to contribute to the AQ solutions based on individual knowledge (Ermolaeva et al., 2020). Although more than ten crowdfunding-based projects on investigating AQ based on low-cost technology were initiated in the 2010s (Thompson, 2016), it is unclear whether such initiatives can change the current paradigm of AQ monitoring by shifting traditional governmental responsibilities in AQ monitoring to third parties, as indicated by Snyder et al. (2013). ...
Researchers have warned that the paradigm about who should measure air quality (AQ) in cities can change as low-cost commercial sensors for monitoring atmospheric composition gain global popularity. The new paradigm implies the expansion of the traditionally governmental responsibilities for AQ monitoring (to collect, interpret, and explain the data) to previously uninvolved actors. This study reports a first practical example of such changed AQ paradigm that occurred in a large industrial city of Krasnoyarsk (Russia). We describe how severe problems with urban AQ and a limited access to the AQ data from governmental sensors triggered decentralization of the AQ monitoring in the city. The decentralization is manifested by the fact that both governmental network and crowdfund-based activist AQ network, are being used for scientific and, to some extent, advisory purposes. The decentralization was foremost established due to the ambiguous quantitative information about AQ provided to users by the governmental network, exacerbated by efficient alternatives for alleviating this gap, offered by the activists. The unique decentralization of AQ monitoring in Krasnoyarsk can transform into the synergy between the government and citizen action aimed on easing air pollution as the governmental organizations can efficiently reinforce the resources (funds and manpower), and provide legal and technical support, while civic action groups with established audience can consolidate targeted groups of citizens for formulating efficient city-wide strategies in AQ management. Such synergy can become an inspiring example for the cities with degraded AQ, where the official monitoring is plagued by financial or technological limitations.
... At present, gas sensors are usually assigned to monitor a large number of poisonous and harmful gases in the environment and industries [21]. And also these are used in food quality assessment [22], air quality monitoring [23]. in more response, which results low detection limit and (d) are often more thermally and chemically stable [2][3][4][5][6] MOFs gained the huge interest among the researchers for the development of a selective and sensitive sensor for detection of a gas. ...
In the present work, we fabricated 1:1 bimetallic ZnCu(NA); ZnCd(NA); and ZnCo(NA) metal organic frameworks (MOFs) using nicotinic acid (NA) as organic linker by solvothermal method. Fourier-transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET) analysis, X-Ray Photoelectron Spectroscopy (XPS), and scanning electron microscopy (SEM) were used to describe all bimetallic MOF topologies. These compounds were used to develop chemiresistive sensor devices for sensing of formaldehyde vapor at room temperature. Drop-casting method was used to make the sensing device on a glass plate with silver electodes. The resulting bimetallic sensors exhibited excellent sensitivity, good linearity and more stability in the detection of formaldehyde at 1 to 50 ppm concentrations. ZnCo(NA) exhibited more response towards formaldehyde vapor than other bimetallic MOFs. Transient response analysis was used to determine response and recovery times, as well as stability over time. These findings prove the application prospects of bimetallic Zn/Cu, Zn/Cd and Zn/Co MOFs in the selective and sensitive detection of formaldehyde at room temperature.
... Low maintenance requirements and ease/affordability of replacing damaged sensors make CGS ideal for these networks which can help to supplement sparse, pre-existing air pollution networks [12,13]. Furthermore, the cost barrier to work with CGS is significantly lower which opens up possibilities for community-driven science [14,15]. ...
Indoor Air Quality (IAQ) monitoring is essential to assess occupant exposure to the wide range of pollutants present in indoor environments. Accurate research-grade monitors are often used to monitor IAQ but the expense and logistics associated with these devices often limits the temporal and spatial scale of monitoring efforts. More affordable consumer-grade sensors – frequently referred to as low-cost sensors – can provide insight into IAQ conditions across greater scales but their accuracy and calibration requirements need further evaluation. In this paper, we present the Building EnVironment and Occupancy (BEVO) Beacon. The BEVO Beacon is entirely open-source, including the software, hardware, and design schematics which are all provided on GitHub. We created 20 of these standalone, stationary devices which measure up to 24 parameters at a one-minute resolution of which we focus on carbon dioxide, carbon monoxide, total volatile organic compounds, temperature, and size-resolved particulate matter. We investigated the efficacy of two different calibration approaches – device-specific and environment-averaged – for these sensors as well as also provide an extensive discussion considerations for each of the sensors. Calibrated sensors performed well when compared to reference monitors or calibrated gas standards. The CO sensors yielded the best agreement (r2=0.98-0.99), followed by temperature (r2=0.89-0.99), CO
(r2=0.62-0.99), and PM2.5 (r2=-0.13-0.91). In all cases, the device-specific calibration approach yielded the most accurate results. We evaluated our devices through a successful 11-week field study where we monitored the IAQ in participants’ bedrooms. The work we present on consumer-grade sensors adds to the existing literature by considering sensor-specific calibration techniques and analysis. The BEVO Beacon adds to the successful line of similarly developed devices by providing an open-source framework that researchers can readily adapt and modify to their own applications.
... It can provide high-precision spatial measurements. The use of low-cost devices should be associated with field calibration to ensure reliable results, and calibration is performed using reference devices [15][16][17]. ...
Few air pollution studies have been applied in the State of Palestine and all showed an increase in particulate matter concentrations above WHO guidelines. However, there is no clear methodology for selecting monitoring locations. In this study, a methodology based on GIS and locally calibrated low-cost sensors was tested. A GIS-based weighted overlay summation process for the potential sources of air pollution (factories, quarries, and traffic), taking into account the influence of altitude and climate, was used to obtain an air pollution hazard map for Nablus, Palestine. To test the methodology, eight locally calibrated PM sensors (AirUs) were deployed to measure PM2.5 concentrations for 55 days from 7 January to 2 March 2022. The results of the hazard map showed that 82% of Nablus is exposed to a high and medium risk of PM pollution. Sensors’ readings showed a good match between the hazard intensity and PM concentrations. It also shows an elevated PM2.5 concentrations above WHO guidelines in all areas. In summary, the overall average for PM2.5 in the Nablus was 48 µg/m3. This may indicate the effectiveness of mapping methodology and the use of low-cost, locally calibrated sensors in characterizing air quality status to identify the potential remediation options.
... It can provide high-precision spatial measurements. The use of low-cost devices should be associated with field calibration to ensure reliable results, and calibration is performed using reference devices [15][16][17]. ...
Few air pollution studies have been applied in the State of Palestine and all showed an increase in particulate matter concentrations above WHO guidelines. However, there is no clear methodology for selecting monitoring locations. In this study, a methodology based on GIS and locally calibrated low-cost sensors was tested. A GIS-based weighted overlay summation process for the potential sources of air pollution (factories, quarries, and traffic), taking into account the influence of altitude and climate, was used to obtain an air pollution hazard map for Nablus, Palestine. To test the methodology, eight locally calibrated PM sensors (AirUs) were deployed to measure PM2.5 concentrations for 55 days from 7 January to 2 March 2022. The results of the hazard map showed that 82% of Nablus is exposed to a high and medium risk of PM pollution. Sensors’ readings showed a good match between the hazard intensity and PM concentrations. It also shows an elevated PM2.5 concentrations above WHO guidelines in all areas. In summary, the overall average for PM2.5 in the Nablus was 48 µg/m3. This may indicate the effectiveness of mapping methodology and the use of low-cost, locally calibrated sensors in characterizing air quality status to identify the potential remediation options.
... Generally, the term LCS implies inexpensive sensor nodes costing less than 100 US dollars (Chojer et al., 2020;Morawska et al., 2018;Rai et al., 2017). LCS are a portable, user-friendly and economical solution that can provide near real-time air quality analysis while offering scalability and widespread availability (Castell et al., 2013;Thompson, 2016;White et al., 2012). They spearhead the paradigm shift in air quality monitoring Snyder et al. (2013) by being a potential supplement to the enormous, expensive traditional monitoring methods by implementing relatively cheaper technologies such as electrochemical cell (EC), metal oxide semiconductor (MOS), nondispersive infrared (NDIR), nephelometry, and optical particle counters (OPC) among others (Hagan and Kroll, 2020;White et al., 2012). ...
Poor indoor air quality has adverse health impacts. Children are considered a risk group, and they spend a significant time indoors at home and in schools. Air quality monitoring has traditionally been limited due to the cost and size of the monitoring stations. Recent advancements in low-cost sensors technology allow for economical, scalable and real-time monitoring, which is especially helpful in monitoring air quality in indoor environments, as they are prone to sudden peaks in pollutant concentrations. However, data reliability is still a considerable challenge to overcome in low-cost sensors technology. Thus, following a monitoring campaign in a nursery and primary school in Porto urban area, the present study analyzed the performance of three commercially available low-cost IoT devices for indoor air quality monitoring in real-world against a research-grade device used as a reference and developed regression models to improve their reliability. This paper also presents the developed on-field calibration models via machine learning technique using multiple linear regression, support vector regression, and gradient boosting regression algorithms and focuses on particulate matter (PM1, PM2.5, PM10) data collected by the devices. The performance evaluation results showed poor detection of particulates in classrooms by the low-cost devices compared to the reference. The on-field calibration algorithms showed a considerable improvement in all three devices' accuracy (reaching up to R² > 0.9) for the light scattering technology based particulate matter sensors. The results also show the different performance of low-cost devices in the lunchroom compared to the classrooms of the same school building, indicating the need for calibration in different microenvironments.
... The main advantage of electrochemical sensors lies in the simple portability and low price, which contributes to the ability to easily monitor selected gases within the different platforms, such as "Smart-cities" [5,6,7]. Development of low-cost, portable, and low-power devices for monitoring airborne pollutants is a crucial step towards developing improved air quality models and better quantitating the health effects of human and animal exposure [8,9,10]. ...
The paper presents the designed system to measurements of gas sensor transient characteristics. Electrochemical oxygen sensor SK-25F was selected for measurements from point of view application in health care and ensuring human safety in industrial production facilities and laboratories. The aim of this work is to design an automatic system for measuring the transient function G(s) of electrochemical sensors and to identify the mathematic model from a sample of sensors. The automatic measurement system based on a microcontroller for the measurements of dynamical characteristics of gas sensors was designed and developed. The result is transfer function with fit to estimation data higher as 99.48 %. The bandwidth of gas sensors was calculated on average at 0.0285763 Hz with a maximum deviation of 0.34 %. Finally, an algorithm for detecting the exceeding of the frequency range of an electrochemical gas sensor is proposed. Its application is in speed control UAV with the aim of accurate measurements of gases in the air by electrochemical sensors.
... Thus, comprehensive studies on air quality are vital to understanding the problems associated with it. Previous reviews have clearly highlighted a relationship between a realistic air quality measure and the sensor quality, mode of transport, local exposure, and big data analysis (Cepeda et al. 2017;Commodore et al. 2017;Thompson 2016). Nevertheless, the rapid development of sensors for mobile devices and epidemiological studies based on crowdsensing data make necessary a summary concerning all the recent advances. ...
The spatiotemporal heterogeneity of the air pollutants complicates appropriate monitoring. The collective measures or crowdsensing is a promising approach to achieve a better air pollution assessment because it includes the local concentration of pollutants, as well as the position and mobility of people. Thus, compared to traditional static monitoring, the participatory sensing data by low-cost sensors can avoid the misclassification of exposition to air pollutants, enabling a comprehensive understanding of their health effects. This systematic review integrates each core part of what is required to achieve crowdsensing for air pollution: sensors, portable devices, and data models. Despite the limitations of sensors in terms of sensitivity and selectivity, it has been possible to use portable air monitors to determine pollution hotspots around the world. However, limited models for data processing, performance issues when using low-cost devices, in addition to lack of community engagement, are the challenges to overcome for the feasibility of air pollution assessment with portable monitors.
Graphical abstract
... While the implementation of portable sensing techniques is promising, researchers should keep in mind the current limitations of these techniques. One of the main limitations is their inferior quality (Thompson, 2016). Compared to static sensors (e.g., those installed at environmental monitoring stations), portable sensors tend to be less accurate and reliable due to technological constraints posed by their size and limited power availability (i.e., they are often dependent on battery power). ...
Portable sensing, in which lightweight mobile sensors are used to measure stimuli, events, and human behavior, is a new and disruptive data collection paradigm. It has several methodological advantages compared to traditional methods and is suitable for investigating the dynamism of increasingly mobile and urban societies. In this article, we discuss the motivations behind the use of portable sensing and reflect upon the advances, limitations, and future of the field. Although portable sensing is still in its infancy, we foresee that its utilization will grow in the coming years. For portable sensing to become a prevalent and legitimate methodological approach, it is essential to have conceptually strong study designs that are grounded in suitable ethical procedures and comply with data protection regulations.
... With the availability of integrated low-cost air environment monitoring solutions, it is clear that the technology for real-time citizen sensing is advancing rapidly. However, such solutions have some major limitations, including project setup, validation [39], data reliability [40], security [16] and accessible tools for data analysis. AirKit aims to create an accurate, open and reliable air quality monitoring system, while investigating the role of low-cost sensors and digital monitoring technologies in facilitating and organising new types of environmental engagement. ...
Increasing urbanisation and a better understanding of the negative health effects of air pollution have accelerated the use of Internet of Things (IoT)-based air quality sensors. Low-cost and low-power sensors are now readily available and commonly deployed by individuals and community groups. However, there are a wide range of such IoT devices in circulation that differently focus on problems of sensor validation, data reliability, or accessibility. In this paper, we present AirKit, which was developed as an integrated and open source “social IoT technology.” AirKit enables a comprehensive approach to citizen-sensing air quality through several integrated components: (1) the Dustbox 2.0, a particulate matter sensor; (2) Airsift, a data analysis platform; (3) a reliable and automatic remote firmware update system; (4) a “Data Stories” method and tool for communicating citizen data; and (5) an AirKit logbook that provides a guide for designing and running air quality projects, along with instructions for building and using AirKit components. Developed as a social technology toolkit to foster open processes of research co-creation and environmental action, Airkit has the potential to generate expanded engagements with IoT and air quality by improving the accuracy, legibility and use of sensors, data analysis and data communication.
Lithium‐ion battery leakage indicates battery malfunction. In an electric vehicle, the evolving vapors can pose a risk to the health of the passengers. Early detection of a leakage reduces this risk and can prevent further damage. In this review, gas detection techniques such as detector tubes, portable gas chromatography, infrared spectroscopy, gas sensors, and laser spectroscopy are discussed in relation to their capacity of detecting airborne compounds coming from the evaporation of a leaked battery electrolyte. Possible scenarios in which battery leakage can occur are introduced that are partially based on the Global Technical Regulation on Electric Vehicle Safety: parked, driving, charging, postcrash (accident), rescue, and stationary application. The applicability for a potential early warning system using the discussed gas detection techniques is assessed and because no off‐the‐shelf solution could be found overlaps of the capabilities of the techniques with the needs of each scenario are identified and opportunities for further development are pointed out.
This paper aims to review the engineering controls for indoor air quality (IAQ) from a systems design perspective. As a result of the review, we classify the literature content into three categories: (1) indoor air treatments, (2) dissemination control strategies, and (3) information technology. Indoor air treatments can be generally interpreted as the “cleaning” aspect, which covers ventilation and contaminant removal techniques. Dissemination control focuses on how contaminants generated in an indoor space can be transmitted, where four types of dissemination are classified. The category of information technology discusses IAQ sensors for monitoring, as well as the applications of the Internet of Things and IAQ data. Then, we further analyze the reviewed engineering controls by performing systems and functional analysis. Along with a discussion of IAQ functions, we suggest some systems design techniques, such as functional decoupling and design for flexibility/resilience, which are expected to promote more systems thinking in designing IAQ solutions.
Environmental data with a high spatio-temporal resolution is vital in informing actions toward tackling urban sustainability challenges. Yet, access to hyperlocal environmental data sources is limited due to the lack of monitoring infrastructure, consistent data quality, and data availability to the public. This paper reports environmental data (PM, NO2, temperature, and relative humidity) collected from 2020 to 2022 and calibrated in four deployments in three global cities. Each data collection campaign targeted a specific urban environmental problem related to air quality, such as tree diversity, community exposure disparities, and excess fossil fuel usage. Firstly, we introduce the mobile platform design and its deployment in Boston (US), NYC (US), and Beirut (Lebanon). Secondly, we present the data cleaning and validation process, for the air quality data. Lastly, we explain the data format and how hyperlocal environmental datasets can be used standalone and with other data to assist evidence-based decision-making. Our mobile environmental sensing datasets include cities of varying scales, aiming to address data scarcity in developing regions and support evidence-based environmental policymaking.
Mobile ambient air quality monitoring is rapidly changing the current paradigm of air quality monitoring and growing as an important tool to address air quality and climate data gaps across the globe. This review seeks to provide a systematic understanding of the current landscape of advances and applications in this field. We observe a rapidly growing number of air quality studies employing mobile monitoring, with low-cost sensor usage drastically increasing in recent years. A prominent research gap was revealed, highlighting the double burden of severe air pollution and poor air quality monitoring in low- and middle-income regions. Experiment-design-wise, the advances in low-cost monitoring technology show great potential in bridging this gap while bringing unique opportunities for real-time personal exposure, large-scale deployment, and diversified monitoring strategies. The median value of unique observations at the same location in spatial regression studies is ten, which can be used as a rule-of-thumb for future experiment design. Data-analysis-wise, even though data mining techniques have been extensively employed in air quality analysis and modeling, future research can benefit from exploring air quality information from nontabular data, such as images and natural language.
Existen muchas problemáticas nacionales concretas que, por su importancia y gravedad, requieren de una atención urgente y de una solución integral, profunda y amplia. Van del planteamiento del problema o el reto, a la articulación de capacidades científico-técnicas y colaboración con otros actores sociales, del sector público o privado, para establecer metas de corto (1 año), mediano (3 años) o largo plazo (5-6 años) que conduzcan a la solución del problema en cuestión. Por ello, el objetivo central es investigar la causas de los problemas y darles solución, para lo cual el abordaje es multidimensional y multi- o interdisciplinario, tomando en consideración los conocimientos teórico-prácticos más avanzados generados por las humanidades, ciencias y tecnologías; manteniendo un diálogo continuo con la gran diversidad de saberes y experiencias que han reunido las comunidades, los ciudadanos, los funcionarios públicos y los empresarios que desean el bien público y el cuidado de los bienes comunes con una perspectiva de cuidado ambiental.
Este libro de divulgación presenta trabajos de investigación de manera colectiva y cooperativa entre los cuerpos académicos del Centro Universitario de los Valles (Ingeniería en Control Automático, UDG-CA-1124) de la Universidad de Guadalajara, Instituto Tecnológico Superior de Irapuato (Electrónica de Potencia con clave ITESI-CA-2) del Tecnológico Nacional de México, Universidad Tecnológica Emiliano Zapata (Ingeniería y Tecnología de los Materiales, UTEZEM-CA2 y Mantenimiento y Mecatrónica, UTEZEM-CA-8) del Estado de Morelos y la Universidad de Guanajuato (Diseño e Integración de Sistemas Mecatrónicos, UGTO-CA-210).
Esta colaboración interinstitucional entre cuerpos académicos vinculados armónicamente establece una red con los objetivos principales de:
• Ampliar o complementar Líneas de Generación y Aplicación Innovadora de Conocimientos que cultivan los grupos participantes.
• Promover y demostrar la transferencia de tecnología, el uso de espacios y laboratorios para realizar proyectos y desarrollos científicos.
• Propiciar el intercambio y movilidad del personal de investigación.
• Promover colaboraciones conjuntas para el desarrollo de proyectos tecnológicos y de investigación para la generación de producción académica requerida por el Programa para el Desarrollo Profesional Docente (PRODEP).
• Potenciar y coordinar las líneas de investigación y desarrollo.
• Desarrollar soluciones a problemas de interés regional o nacional, basados en la investigación.
• Consolidar iniciativas y líneas de colaboración.
• Generar acuerdos de capacitación y cursos de actualización entre ambas instituciones.
• Formar recursos humanos.
• Impulsar otras actividades que se deriven del trabajo conjunto.
Nowadays, territorial zoning plans and city expansion are important challenges for big cities. In order to do so, many parameters and restrictions are involved in the decision-taking process, such as population density, safety, security, commuting time, etc. In addition to the available information that the city governmental agencies might have (public services coverage, transportation systems, etc.), a detailed map of air pollution is paramount.
Urban air pollution is a global concern impairing citizens' health, thus monitoring is a pressing need for city managers. City-wide networks for air pollution monitoring based on low-cost sensors are promising to provide real-time data with detail and scale never before possible. However, they still present limitations preventing their ubiquitous use. Thus, this study aimed to perform a post-deployment validation and calibration based on two step methods for ozone low-cost sensor of a city-wide network for air pollution and meteorology monitoring using low-cost sensors focusing on the main challenges. Four of the 23 data collection units (DCUs) of the UrbanSense network installed in Porto city (Portugal) with low-cost sensors for particulate matter (PM), carbon monoxide (CO), ozone (O3), and meteorological variables (temperature, relative humidity, luminosity, precipitation, and wind speed and direction) were evaluated. This study identified post-deployment challenges related to their validation and calibration. The preliminary validation showed that PM, CO and precipitation sensors recorded only unreliable data, and other sensors (wind speed and direction) very few data. A multi-step calibration strategy was implemented: inter-DCU calibration (1st step, for O3, temperature and relative humidity) and calibration with a reference-grade instrument (2nd step, for O3). In the 1st step, multivariate linear regression (MLR) resulted in models with better performance than non-linear models such as artificial neural networks (errors almost zero and R² > 0.80). In the 2nd step, the calibration models using non-linear machine learning boosting algorithms, namely Stochastic Gradient Boosting Regressor (both with the default and post-tuning hyper-parameters), performed better than artificial neural networks and linear regression approaches. The calibrated O3 data resulted in a marginal improvement from the raw data, with error values close to zero, with low predictability (R² ∼ 0.32). The lessons learned with the present study evidenced the need to redesign the calibration strategy. Thus, a novel multi-step calibration strategy is proposed, based on two steps (pre and post-deployment calibration). When performed cyclically and continuously, this strategy reduces the need for reference instruments, while probably minimising data drifts over time. More experimental campaigns are needed to collect more data and further improve calibration models.
The smart city model for operation and governance of modern cities requires huge quantities of data about people and the environment to support related applications, and crowdsourcing is effective for collecting and processing such data. Numerous reviews of the literature on crowdsourcing and smart cities as separate research fields have been published. Research on the intersection of the two is relatively new and lacks a systematic literature review. This study applies bibliometric and scientometric research methods and the research tools to study 367 related publications retrieved from the Web of Science database. Keyword co‐occurrence analysis was conducted to find the distribution of publications, research cooperation, and major research areas. Document co‐citation analysis was used to examine the domain knowledge structure, and citation burst detection was used to identify trends in research in this topic area. The analysis results clarify the research content and evolutionary context and reveal emerging research trends.
In Delhi, the capital city of India, air pollution has been a perpetual menace to urban sustainability and public health. The present study uses a mixed-method approach to enumerate to the urban authorities: (a) the state of air pollution in the city; (b) systemic flaws in the current monitoring network; (c) potential means to bolster it; and (d) need of a participatory framework for monitoring. Information about Air Quality Index (AQI), obtained from 36 monitoring stations across Delhi is compared between 2021 (20 April–25 May; 2nd year/phase of SARS-CoV-2 lockdown), and the corresponding time periods in 2020 (1st year/phase of lockdown), and 2019 (business-as-usual) using the Mann–Whitney U Test. AQI during the 2021 lockdown (a) appeared statistically more similar ( p < .01) to that of 2019 and (b) exceeded the environmental health safety benchmark for 85% days during the study period (20 April–25 May). However, this only presented a partial glimpse into the air pollution status. It owes to numerous ‘holes’ in the AQI data record (no data and/or insufficient data). Moreover, certain areas in Delhi yet have no monitoring station, or only too few, to yield a ‘representative’ estimate (inadequate spatial coverage). Such shortcomings in the existing monitoring network may deter future research and targeted/informed decision-making for pollution control. To that end, the present research offers a summary view of Low-Cost Air Quality Sensors (LCAQS), to offer the urban sustainability authorities, ‘complementary’ technique to bolster and diversify the existing network. The main advantages and disadvantages of various LCAQS sensor technologies are highlighted while emphasizing on the challenges around various calibration techniques (linear and non-linear). The final section reflects on the integration of science and technology with social dimensions of air quality monitoring and highlights key requirements for (a) community mobilization and (b) stakeholder engagement to forge a participatory systems’ design for LCAQS deployment.
This research aims to discuss the application of multi-sensor network technology for the monitoring of indoor air pollution. Indoor air pollution has become a severe problem that affects public health, especially indoor parking. The indoor air pollution monitoring system will provide information about vehicle exhaust emission levels. We have improved the system to identify six parameters of the vehicles' gas emissions within a different location at once. This research aimed to measure the parameter of Carbon Monoxide (CO), Carbon Dioxide (CO2), Hydro Carbon (HC), temperature and humidity, and levels of particulates in the air (PM10). The performance of this system shows good ability to compare the results of measurements of air quality measuring professionals. In this study, we investigated the performance of a custom-built prototype developed under the android-based application to detect air pollution levels in the parking area. Our objective was to evaluate the suitability of a low-cost multi-sensor network for monitoring air pollution in parking and the other area. The benefit of our approach is that its time and space complexity make it valuable and efficient for real-time monitoring of air pollution.
In this paper we describe our work aimed at designing a system able to measure the particulate matter (PM) concentrations via an optical particle counter (OPC) and simultaneously collect it via standard 2.5 cm filters for laboratory characterization. The Port of Civitavecchia (Italy), one of the most important maritime hubs of the Mediterranean Sea, was selected as a test site for an eight-months monitoring campaign. Comparison between the data provided by our device with those from the referenced and certified monitoring stations from the governmental Regional Agency for the Protection of the Environment (ARPA Lazio) allowed to define clear threshold values (PM10 = 25 μg/m³ and PM2.5 = 10 μg/m³). These threshold values need to be considered when correcting the OPC raw data with respect to the humidity (RH) conditions. The sample material was characterized through optical microscopy and SEM-EDS (scanning electron microscopy coupled with energy-dispersive X-ray fluorescence) and spectroscopy (FTIR, Raman), showing a variegate composition from Al-Fe-oxides to silicates, carbonates, and sulfates, to coal and amorphous carbon together with microplastics and textile fibers. As a final test, we analyzed the PM trends provided by our device during the Covid-19 lockdown, when stringent restrictions in the human activities caused well-known fluctuations in the atmospheric pollution. We again observed an evolution of the PM peaks in excellent agreement with the results yielded by the ARPA Lazio monitoring stations. This result provides a valuable confidence test for our devices highlighting the effectiveness of the presented strategy for airborne particulate-matter monitoring.
Few of the air pollution studies were applied in the State of Palestine, all showed an
increase in particulate matter concentrations above WHO guidelines. However, there is
no clear methodology for selecting monitoring locations. In this study a methodology
based on GIS and locally calibrated low-cost sensors was tested. A GIS-based weighted
overlay summation process for the potential sources of air pollution (factories, quarries,
and traffic) taking into account the influence of altitude and climate was used to obtain a
particulate matter (PM) pollution hazard map for Nablus, Palestine. To test the
methodology, eight locally calibrated PM sensors (AirUs) were deployed to measure
PM2.5 and PM10 concentrations for 55 days from 7-Jan to 2-Mar 2022. The results of the
hazard map showed that 82% of Nablus is exposed to a very high and high hazard of PM
pollution. It also shows an elevated PM2.5 concentrations above WHO guidelines in all
stations. In summary, the overall average for PM2.5 and PM10 in Nablus was 48 and 55.2
µg/m3 respectively Sensors’ readings showed a good match between the hazard index and PM concentrations. This indicate the effectiveness of mapping methodology and the use of low-cost, locally calibrated sensors in characterizing air quality status to identify the potential remediation options .
Weather in Malaysia are hot and humid throughout the year thus
having a sudden rain can disrupt the drying of laundries and make them wet. In
this study, an automated retractable roof system was developed to overcome this
problem. The development and implementation of this study enables user to
monitor the parameters at the laundry suspension area by using their smartphone
and prevent the laundries getting wet from rain. This study uses humidity
sensors, Ultraviolet (UV) sensor, rain sensor, and temperature sensor to detect
parameter such as humidity, UV intensity, presence of water and temperature
respectively. Data from the sensors were collected and analysed to determine the
values of parameters when rains occurred. These parameters were indicated as
part of weather prediction study. From experiment, the retractable roof will open
and close depended on condition met by the system. In addition, the system can
communicate with the user’s phone through using Internet connection. The
Blynk application in the smartphone allows the user to monitor and control the
system through internet connection between the application and microcontroller.
This study will be helpful for non-commercial use and can be expanded to
commercial use as with further improvement.
Aromatherapy candles with essential oils which can provides a therapeutic
treatments have been made to maintain and improve our wellbeing. In this
paper, a mini prototype of automated aromatherapy candle process plant using IoT
and WSN has been proposed and developed. The main process of producing
aromatherapy candle are heating and mixing. To produce the right quality of the
aromatherapy candle, the quantity of the raw material is important. Heating process
will be control by using ESP8266 based PID controller and monitored by
using Open Source Programmable Logic Controller called OpenPLC that run on
Raspberry Pi. The software is efficient because can support users over the entire
plant and process. Mixing process will mix the raw material evenly using agitator
motor with specific temperature. The whole process in this work can be monitored
and control through PC via this implementation of software. To obtain the best
quality of this work, the set point of temperature need to be control and the plant
able to be achieved after second test of the study. As the result, this study able to
produces aromatherapy candle with better quality in minimal time. This study also
able to control the candle from releasing too many Volatile Organic Compound
that can effect human life. Armed with the wealth of relevant information presented
in this article, it is hoped that readers will have greatly benefited and gained
a thorough understanding on how to develop an automated aroma therapy candle
process planting using IoT and WSN. With further research put forth into this
study, it is also hope it could be an advantage in innovation development and can
be implemented in real life manufacturing industry.
(A&EI) as a novel subfield became obvious. As in all areas of Biomedical Informatics, A&EI must deal with issues such as relevant data collection, the management of data extracted from accident sites, health records or sensors, wearables and apps, and appropriate data processing, with the dual purpose of preventing harm and decision support.
This book is an introduction to the research and application domain of A&EI, and is the product of three years’ work by the Working Group in A&EI of the International Medical Informatics Association (IMIA). The book presents ten chapters organized in four sections. The first section explores the framework for achieving an emergency-informatics health information infrastructure; the second focuses on the gathering of critical clinical data related to the building up of a smart environment for A&EI; the third introduces state-of-the-art technologies for integration into virtual emergency registries; and the final part considers the delicate issues of patient safety raised by the introduction of surveillance technologies into clinical care, along with other issues presenting challenges to the domain of A&EI for the future.
The book is an important contribution to the field of A&EI, and will be of interest to healthcare professionals, informaticians, and all those who want a better understanding of the domain of Accident and Emergency Informatics.
The 21st century has seen an enormous growth in emergency medical services (EMS) information technology systems, with corresponding accumulation of large volumes of data. Despite this growth, integration efforts between EMS-based systems and electronic health records, and public-sector databases have been limited due to inconsistent data structure, data missingness, and policy and regulatory obstacles. Efforts to integrate EMS systems have benefited from the evolving science of entity resolution and record linkage. In this chapter, we present the history and fundamentals of record linkage techniques, an overview of past uses of this technology in EMS, and a look into the future of record linkage techniques for integrating EMS data systems including the use of machine learning-based techniques.
Urban air quality is increasingly becoming a cause for concern for the health of the human population. The poor air quality is already wreaking havoc in major cities of the world, where serious health issues and reduction of average human life by a factor of years are reported. The air quality in developing countries can become worse as they undergo development. The urban air quality varies non-linearly depending upon the various factors such as land use, industrialization, waste disposal, traffic volume, etc. To address this problem, it is necessary to look at the plethora of available literature from multiple perspectives such as types and sources of pollutants, meteorology, urban mobility, urban planning and development, health care, economics, etc. In this paper, we provide a comprehensive survey of the state-of-the-art in urban air quality. We first review the fundamental background on air quality and present the emerging landscape of urban air quality. We then explore the available literature from multiple urban air quality measurement projects and provides the insights uncovered in them. We then take a look at the sources that are significantly contributing to polluting the air quality. Finally, we highlight open issues and research challenges in dealing with urban air pollution.
Urban air quality is increasingly becoming a cause for concern for the health of the human population. The poor air quality is already wreaking havoc in major cities of the world, where serious health issues and reduction of average human life by a factor of years are reported. The air quality in developing countries can become worse as they undergo development. The urban air quality varies non-linearly depending upon the various factors such as land use, industrialization, waste disposal, traffic volume, etc. To address this problem, it is necessary to look at the plethora of available literature from multiple perspectives such as types and sources of pollutants, meteorology, urban mobility, urban planning and development, health care, economics, etc. In this paper, we provide a comprehensive survey of the state-of-the-art in urban air quality. We first review the fundamental background on air quality and present the emerging landscape of urban air quality. We then explore the available literature from multiple urban air quality measurement projects and provides the insights uncovered in them. We then take a look at the sources that are significantly contributing to polluting the air quality. Finally, we highlight open issues and research challenges in dealing with urban air pollution.
Clinical information systems (CIS) have developed rapidly over the last 20 years and are now found in all settings that deliver and support care. From small clinics to large tertiary care settings, blood banks to pharmacies, CIS are ubiquitous. These systems may be composed of single software solutions or complex integrated modules to create a complex system. Healthcare functionality provided by software has become so broad that once simple medical devices are now minicomputers that need to be interfaced with the larger electronic health record. Telehealth allows for the provision of care outside of the physical walls of an organization, and communication between providers and patients can be accomplished today via secure messaging. Health information exchanges allow information to flow between providers and organizations. Registries take advantage of the patient data being collected to better track conditions and preventive and treatment services. As these systems have matured, the door has opened to innovations that will bring healthcare technology well beyond where it is today.KeywordsClinical information systemHospital information systemElectronic medical recordElectronic health recordTelemedicinePatient portalsHealth communicationHospital communication systemRegistriesMedical device
Air pollution is one of the biggest contributors to the global burden of disease and mortality and contributes to over a million deaths worldwide every year. Short- and long-term exposures to air pollutants, when they are present in high concentration, lead to respiratory illnesses, aggravation of cardiovascular diseases, and premature deaths. The accurate assessment of health risk and impact due to ambient and indoor air pollution is imperative for policymaking, prevention, and rectification efforts. Technological intervention and advancement in data science and modelling predictions could be of use for accurate health risk assessment and exposure to the pollution which includes exposure to small and large populations. Internet of Things includes sensors, smartphones, and air pollution models based on big data sources which are not only used to assess the exposure, but also aid in devising prevention opportunities. Key features of these tools include accessibility, spatial resolution, specific health outcomes associated with pollutants, population exposure, and application. This chapter is a state-of-the-art review that elaborates the attempts and technological interventions and advancements made to address the health risk assessment associated with air pollution and strategies adopted for personalized treatment to avert exacerbation and refractory symptoms. Technological advancement and its involvement may revolutionize the air pollution prediction, exposure, and risk assessment research in the coming time, if they meet the logistical and data science challenges along with the integration of health impact and related risks’ assessment which is linked to the exposure of air pollution.
Keywords
Exposure, Health, Internet of Things, Technology, Data science
Nitrogen species present in the atmosphere, soil, and water play a vital role in ecosystem stability. Reactive nitrogen gases are key air quality indicators and are responsible for atmospheric ozone layer depletion. Soil nitrogen species are one of the primary macronutrients for plant growth. Species of nitrogen in water are essential indicators of water quality, and they play an important role in aquatic environment monitoring. Anthropogenic activities have highly impacted the natural balance of the nitrogen species. Therefore, it is critical to monitor nitrogen concentrations in different environments continuously. Various methods have been explored to measure the concentration of nitrogen species in the air, soil, and water. Here, we review the recent advancements in optical and electrochemical sensing methods for measuring nitrogen concentration in the air, soil, and water. We have discussed the advantages and disadvantages of the existing methods and the future prospects. This will serve as a reference for researchers working with environment pollution and precision agriculture.
Low-cost sensors (LCS) are becoming popular for air quality monitoring (AQM). They promise high spatial and temporal resolutions at low-cost. In addition, citizen science applications such as personal exposure monitoring can be implemented effortlessly. However, the reliability of the data is questionable due to various error sources involved in the LCS measurement. Furthermore, sensor performance drift over time is another issue. Hence, the adoption of LCS by regulatory agencies is still evolving. Several studies have been conducted to improve the performance of low-cost sensors. This article summarizes the existing studies on the state-of-the-art of LCS for AQM. We conceptualize a step by step procedure to establish a sustainable AQM setup with LCS that can produce reliable data. The selection of sensors, calibration and evaluation, hardware setup, evaluation metrics and inferences, and end user-specific applications are various stages in the LCS-based AQM setup we propose. We present a critical analysis at every step of the AQM setup to obtain reliable data from the low-cost measurement. Finally, we conclude this study with future scope to improve the availability of air quality data.
Urban environments with a high degree of industrialization are infested with hazardous chemicals and airborne pollutants. These pollutants can have devastating effects on human health, causing both acute and chronic diseases such as respiratory infections, lung cancer, and heart disease. Air pollution monitoring is vital not only to citizens, warning them on the health risks of air pollutants, but also to policy-makers, assisting them on drafting regulations and laws that aim at minimizing those health risks. Currently, air pollution monitoring predominantly relies on expensive high-end static sensor stations. These stations produce only aggregated information about air pollutants, and are unable to capture variations in individual's air pollution exposure. As an alternative, this article develops a citizen-based air pollution monitoring system that captures individual exposure levels to air pollutants during daily indoor and outdoor activities. We present a low-cost portable sensor and carry out a measurement campaign using the sensors to demonstrate the validity and benefits of citizen-based pollution measurements. Specifically, we (i) successfully classify the data into indoor and outdoor, and (ii) validate the consistency and accuracy of our outdoor-classified data to the measurements of a high-end reference monitoring station. Our experimental results further prove the effectiveness of our campaign by (i) providing fine-grained air pollution insights over a wide geographical area, (ii) identifying probable causes of air pollution dependent on the area, and (iii) providing citizens with personalized insights about air pollutants in their daily commute.
In this work the performances of several field calibration methods for low-cost sensors, including linear/multi linear regression and supervised learning techniques, are compared. A cluster of either metal oxide or electrochemical sensors for nitrogen monoxide and carbon monoxide together with miniaturized infra-red carbon dioxide sensors was operated. Calibration was carried out during the two first weeks of evaluation against reference measurements. The accuracy of each regression method was evaluated on a five months field experiment at a semi-rural site using different indicators and techniques: orthogonal regression, target diagram, measurement uncertainty and drifts over time of sensor predictions. In addition to the analyses for ozone and nitrogen oxide already published in Part A [1], this work assessed if carbon monoxide sensors can reach the Data Quality Objective (DQOs) of 25% of uncertainty set in the European Air Quality Directive for indicative methods. As for ozone and nitrogen oxide, it was found for NO, CO and CO2 that the best agreement between sensors and reference measurements was observed for supervised learning techniques compared to linear and multilinear regression.
This study used two types of paper supported materials with a prototype, reflectance-based detector for indication of hydrogen peroxide vapor under ambient laboratory conditions. Titanyl based indicators provide detection through reaction of the indicator resulting in a dosimeter type sensor, while porphyrin based indicators provide a reversible interaction more suitable to continuous monitoring applications. These indicators provide the basis for discussion of characteristics important to design of a sensor system including the application environment and duration, desired reporting frequency, and target specificity.
The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems.
We report on an innovative use of high-temperature MEMS heater platforms as micro pellistor spectrometers. MEMS heater elements, initially designed for use as thermal infrared emitters, were fitted with thin-film noble metal layers to enable catalytic combustion processes on the hotplate surface. The modified heater platforms were operated in a range of combustible gas ambients while applying saw-tooth-like heater waveforms. Measurements of this kind revealed the heat of reaction vs. hotplate temperature profiles for each individual gas. We find that different families of gases yield distinctly different heat of reaction vs. temperature profiles and that these profiles allow the different families, and members inside some of these families, to be distinguished.
In this work the low temperature response of metal oxide semiconductor gas sensors is analyzed. Important characteristics of this low-temperature response are a pronounced selectivity to acid-and base-forming gases and a large disparity of response and recovery time constants which often leads to an integrator-type of gas response. We show that this kind of sensor performance is related to the trend of semiconductor gas sensors to adsorb water vapor in multi-layer form and that this ability is sensitively influenced by the surface morphology. In particular we show that surface roughness in the nanometer range enhances desorption of water from multi-layer adsorbates, enabling them to respond more swiftly to changes in the ambient humidity. Further experiments reveal that reactive gases, such as NO 2 and NH 3 , which are easily absorbed in the water adsorbate layers, are more easily exchanged across the liquid/air interface when the humidity in the ambient air is high.
Aerosol optical properties are simulated using the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) coupled with the Non-hydrostatic ICosahedral Atmospheric Model (NICAM). The 3-year global mean all-sky aerosol optical thickness (AOT) at 550 nm, the Ångström Exponent (AE) based on AOTs at 440 and 870 nm, and the single scattering albedo (SSA) at 550 nm are estimated at 0.123, 0.657 and 0.944, respectively. For each aerosol species, the mean AOT is within the range of the AeroCom models. Both the modeled all-sky and clear-sky results are compared with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic Network (AERONET). The simulated spatiotemporal distributions of all-sky AOTs can generally reproduce the MODIS retrievals, and the correlation and model skill can be slightly improved using the clear-sky results over most land regions. The differences between clear-sky and all-sky AOTs are larger over polluted regions. Compared with observations from AERONET, the modeled and observed all-sky AOTs and AEs are generally in reasonable agreement, whereas the SSA variation is not well captured. Although the spatiotemporal distributions of all-sky and clear-sky results are similar, the clear-sky results are generally better correlated with the observations. The clear-sky AOT and SSA are generally lower than the all-sky results, especially in those regions where the aerosol chemical composition is contributed to mostly by sulfate aerosol. The modeled clear-sky AE is larger than the all-sky AE over those regions dominated by hydrophilic aerosol, while the opposite is found over regions dominated by hydrophobic aerosol.
The performances of several field calibration methods for low-cost sensors, including linear/multi linear regression and supervised learning techniques are compared. A cluster of ozone, nitrogen dioxide, nitrogen monoxide, carbon monoxide and carbon dioxide sensors was operated. The sensors were either of metal oxide or electrochemical type or based on miniaturized infra-red cell. For each method, a two-week calibration was carried out at a semi-rural site against reference measurements. Subsequently, the accuracy of the predicted values was evaluated for about five months using a few indicators and techniques: orthogonal regression, target diagram, measurement uncertainty and drifts over time of sensor predictions. The study assessed if the sensors were could reach the Data Quality Objective (DQOs) of the European Air Quality Directive for indicative methods (between 25 and 30% of uncertainty for O3 and NO2). In this study it appears that O3 may be calibrated using simple regression techniques while for NO2 a better agreement between sensors and reference measurements was reached using supervised learning techniques. The hourly O3 DQO was met while it was unlikely that NO2 hourly one could be met. This was likely caused by the low NO2 levels correlated with high O3 levels that are typical of semi-rural site where the measurements of this study took place.
Micro-pellistors capable to detect hydrocarbons below 50 mW power consumption at 550 oC operation temperature were developed by a novel processing technique. On the top of the full membrane type micro-heaters 1.4 μm thick porous alumina was formed by laterally selective electrochemical etching of the deposited aluminum layer. The porous alumina of the active element is selectively covered by finely dispersed Pt catalyst using alternative methods; such as dropping of H2[PtCl6] and sputtering technique, all aiming at deposition of controlled volume and structure of the catalyst. Constant current method in a Wheatstone-bridge configuration was applied in functional tests.
Fine particulate matter (PM2.5) is a growing public health concern especially in industrializing countries but existing monitoring networks are unable to properly characterize human exposures due to low resolution spatiotemporal data. Low-cost portable monitors can supplement existing networks in both developed and industrializing regions to increase density of sites and data. This study tests the performance of a low-cost sensor in high concentration urban environments. Seven Portable University of Washington Particle (PUWP) monitors were calibrated with optical and gravimetric PM2.5 reference monitors in Xi'an, China in December 2013. Pairwise correlations between the raw PUWP and the reference monitors were high (R2 = 0.86–0.89). PUWP monitors were also simultaneously deployed at eight sites across Xi'an alongside gravimetric PM2.5 monitors (R2 = 0.53). The PUWP monitors were able to identify the High-technology Zone site as a potential PM2.5 hotspot with sustained high concentrations compared to the city average throughout the day.
Step aside, fitness trackers. The next wave of personal sensors is giving people the ability to monitor the air they breathe.
To assess the impact of atmospheric aerosols on health, climate, and air traffic, aerosol properties must be measured with fine spatial and temporal sampling. This can be achieved by actively involving citizens and the technology they own to form an atmospheric measurement network. We establish this new measurement strategy by developing and deploying iSPEX, a low-cost, mass-producible optical add-on for smartphones with a corresponding app. The aerosol optical thickness (AOT) maps derived from iSPEX spectropolarimetric measurements of the daytime cloud-free sky by thousands of citizen scientists throughout the Netherlands are in good agreement with the spatial AOT structure derived from satellite imagery and temporal AOT variations derived from ground-based precision photometry. These maps show structures at scales of kilometers that are typical for urban air pollution, indicating the potential of iSPEX to provide information about aerosol properties at locations and at times that are not covered by current monitoring efforts.
Health effects attributed to ambient fine particulate matter (PM2.5) now rank it among the risk factors with the highest health burdens in the world, but existing monitoring infrastructure cannot adequately characterize spatial and temporal variability in urban PM2.5 concentrations, nor in human population exposures. The development and evaluation of more portable and affordable monitoring instruments based on low-cost sensors may offer a means to supplement and extend existing infrastructure, increasing the density and coverage of empirical measurements and thereby improving exposure science and control. Here, we report on field calibrations of a custom-built, battery-operated aerosol monitoring instrument we developed using low-cost, off-the-shelf optical aerosol sensors. We calibrated our instruments using 1 h and 24 h PM2.5 data from a class III US EPA Federal Equivalent Method (FEM) PM2.5 β-attenuation monitor in continuous operation at a regulatory monitoring site in Oakland, California. We observed negligible associations with ambient humidity and temperature; linear corrections were sufficient to explain 60% of the variance in 1 h reference PM2.5 data and 72% of the variance in 24 h data. Performance at 1 h integration times was comparable to commercially available optical instruments costing considerably more. These findings warrant further exploration of the circumstances under which this class of aerosol sensors may profitably be deployed to generate improved PM2.5 datasets.
Quartz crystal microbalance (QCM) has gained exceptional importance in the fields of (bio)sensors, material science, environmental monitoring, and electrochemistry based on the phenomenal development in QCM-based sensing during the last two decades. This review provides an overview of recent advances made in QCM-based sensors, which have been widely employed in a plethora of applications for the detection of chemicals, biomolecules and microorganisms.
The detection and measurement of gas concentrations using the characteristic optical absorption of the gas species is important for both understanding and monitoring a variety of phenomena from industrial processes to environmental change. This study reviews the field, covering several individual gas detection techniques including non-dispersive infrared, spectrophotometry, tunable diode laser spectroscopy and photoacoustic spectroscopy. We present the basis for each technique, recent developments in methods and performance limitations. The technology available to support this field, in terms of key components such as light sources and gas cells, has advanced rapidly in recent years and we discuss these new developments. Finally, we present a performance comparison of different techniques, taking data reported over the preceding decade, and draw conclusions from this benchmarking.
This paper describes our experiences with building and deploying a low-cost participatory system for urban air pollution monitoring in Sydney. Though air pollution imposes significant health costs on the urban community globally, today's published data on pollution concentrations is spatially too sparse, and does not allow for sufficiently accurate estimation of exposures for (potentially mobile) individuals in order to make medical inferences. The HazeWatch project described in this paper uses several low-cost mobile sensor units attached to vehicles to measure air pollution concentrations, and users' mobile phones to tag and upload the data in real time. The greater spatial granularity of data thus collected enables creation of pollution maps of metropolitan Sydney viewable in real-time over the web, as well as personalized apps that show the individual's exposure history and allow for route planning to reduce future exposure. We share the insights we obtained from building and trialling such a system in Sydney, and highlight challenges that can be addressed collaboratively by groups developing similar systems world-wide.
Global climate, atmospheric chemistry, and air quality are affected by tropospheric particulate matter. Recent measurements suggest organic compounds present in this haze comprise roughly half of total aerosol fine mass concentration globally. Unlike the well-constrained processes which result in formation of nitrate or sulfate aerosol, the oxidation of volatile organics in the atmosphere can lead to thousands of stable compounds in the aerosol phase. Development of a tractable framework to consider the chemical and physical evolution of the organic aerosol is crucial for modeling its effect on global climate. Here we show coupling a 3-dimensional coordinate system defined by the molecular descriptors of molecular weight, heteroatom mass, and double bond equivalents (D.B.E.) with high-resolution molecular mass spectrometry is a powerful approach for describing key properties of the organic aerosol. The scheme is conceptually simple, yet maintains sufficient complexity to be compatible with quantitative structure–property relationships (QSPRs) used to predict chemical and physical properties that govern aerosol behavior. From available data, both ambient organic aerosol and laboratory generated organic aerosol frequently occupy the region characterized by <10 D.B.E. <600 M.W. and <200 heteroatom mass. A QSPR analysis conducted illustrates spatial trends within the 3D space for volatility and Henry's law constants for 31,000 organic compounds considered.
A squaraine-based system was developed and demonstrated to fluorescently and colorimetrically sense CO2 gas with high sensitivity in DMSO in the presence of fluoride ion. From results, large hypsochromic shifts were observed both in the absorption spectra (134 nm) and fluorescence spectra (126 nm), and the color change of solution could be clearly observed by the naked eye in response to carbon dioxide gas. Combining 1H NMR titration tests and theoretical calculations, a plausible sensing mechanism that the deprotonated SQ-NH2 with fluoride ion will rapidly restore on condition that acidic carbon dioxide gas bubbles in DMSO is proposed and further revealed. Moreover, theoretical studies agree with experimental data well.
We present the one month results of global aerosol optical properties for April 2006, using the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) coupled with the Non-hydrostatic ICosahedral Atmospheric Model (NICAM), by assimilating Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) with Local Ensemble Transform Kalman Filter (LETKF). The simulated AOD, Ångström Exponent (AE) and single scattering albedo (SSA) are validated by independent Aerosol Robotic Network (AERONET) observations over the global sites. The data assimilation has the strongest positive effect on the AOD simulation and slight positive influences on the AE and SSA simulations. For the time-averaged globally spatial distribution, the data assimilation increases the model skill score (S) of AOD, AE, and SSA from 0.55, 0.92, and 0.75 to 0.79, 0.94, and 0.80, respectively. Over the North Africa (NAF) and Middle East region where the aerosol composition is simple (mainly dust), the simulated AODs are best improved by the data assimilation, indicating the assimilation correctly modifies the wrong dust burdens caused by the uncertainties of the dust emission parameterization. Assimilation also improves the simulation of the temporal variations of the aerosol optical properties over the AERONET sites, with improved S at 60 (62%), 45 (55%) and 11 (50%) of 97, 82 and 22 sites for AOD, AE and SSA. By analyzing AOD and AE at five selected sites with best S improvement, this study further indicates that the assimilation can reproduce short duration events and ratios between fine and coarse aerosols more accurately.
Non-dispersive infrared (NDIR) gas sensors applied in environmental field are considered. Disadvantages of the non-dispersive infrared (NDIR) gas sensors include spectral interference and high detection limit. Efforts to improve these disadvantages are reviewed in this paper. Interference caused by water vapor and gas matrix has been partially solved using optical filters and interference correction factors. Limitations such as accuracy and sensitivity of the sensor were overcome by the improvements of inlet gas concentrations, infrared sources, optical designs (including optical filter and gas chamber) and detectors. These improvements are limited to a few gases, in particular, carbon dioxide. Drawbacks related to water vapor still remain and need to be addressed.
Over the past fifty years, considerable efforts have been devoted to measuring the concentration and chemical speciation of volatile organic compounds (VOCs) in ambient air and emissions. Recently, it has become possible to directly determine the overall effect of atmospheric trace gases on the oxidant hydroxyl radicals (OH), by measuring OH reactivity (OH loss frequency). Quantifying total OH reactivity is one way to characterize the roles of VOCs in formation of ground-level ozone and secondary organic aerosols (SOA). Approaches for measuring total OH reactivity in both emissions and ambient air have been progressing and have been applied in a wide range of studies. Here we evaluate the main techniques used to measure OH reactivity, including two methods directly measuring OH decay and one comparative reactivity method (CRM), and summarize the existing experimental and modelling studies. Total OH reactivity varies significantly on spatial, diurnal, seasonal and vertical bases. Comparison with individually detected OH sinks often reveals a significant missing reactivity, ranging from 20% to over 80% in some environments. Missing reactivity has also been determined in most source emission studies. These source measurements, as well as numerical models, have indicated that both undetected primary emissions and unmeasured secondary products could contribute to missing reactivity. A quantitative understanding of total OH reactivity of various sources and ambient environments will enhance our understanding of the suite of compounds found in emissions as well as chemical processes, and will also provide an opportunity for the improvement of atmospheric chemical mechanisms.
Over 30 years, portable systems for fast and reliable gas analysis are at the core of both academic and industrial research. Miniaturized systems can be helpful in several domains. The way to make it possible is to miniaturize the whole gas chromatograph. Micro-system conception by etching silicon channel is well-known. The main objective is to obtain similar or superior efficiencies to those obtained from laboratory chromatographs. However, stationary phase coatings on silicon surface and micro-detector conception with a low limit of detection remain a challenge. Developments are still in progress to offer a large range of stationary phases and detectors to meet the needs of analytical scientists. This review covers the recent development of micro-gas analyzers. It focuses on injectors, stationary phases, column designs and detectors reported in the literature during the last three decades. A list of commercially available micro-systems and their performances will also be presented.
A chromophore based on tricyanofuran (TCF) with a hydrazone (H) recognition moiety was developed. Its molecular-switching performance is reversible and has differential sensitivity towards aqueous ammonia at comparable concentrations. Nanofibers were fabricated from the TCF-H chromophore by electrospinning. The film fabricated from these nanofibers functions as a solid-state optical chemosensor for probing ammonia vapor. Recognition of ammonia vapor occurs by proton transfer from the hydrazone fragment of the chromophore to the ammonia nitrogen atom and is facilitated by the strongly electron withdrawing TCF fragment. The TCF-H chromophore was added to a solution of poly(acrylic acid), which was electrospun to obtain a nanofibrous sensor device. The morphology of the nanofibrous sensor was determined by SEM, which showed that nanofibers with a diameter range of 200-450 nm formed a nonwoven mat. The resultant nanofibrous sensor showed very good sensitivity in ammonia-vapor detection. Furthermore, very good reversibility and short response time were also observed.
This paper illustrates an advanced development for mobile measurement of aerosol optical thickness (AOT) in the ultraviolet-A region, with the improvements of 1) a new solar positioning bubble operating in the smartphone that assists accurate pointing of smartphone's camera to the sun and 2) a robust calibration method using Ångström exponent that is applicable to the AOTs at different wavelengths. This paper develops a new calibration method at 340-nm AOT. In addition, a very high adjusted R-square of 96.9% was observed when compared with a Microtops II sunphotometer on five different days. In addition, a mean percentage difference of 7.8% compared with Microtops II sunphotometer was achieved. This new mobile application and new sensing device work well in different atmospheric conditions, and provide effective hand-held, in-situ measurement of AOT that is comparable with a professional-grade instrument.
We report on a new low-cost non-dispersive infrared (NDIR) based sensor platform for sub-ppm gas detection. The aim of the sensor platform development was to create a cost-effective, mass-producible and highly accurate device. Due to its sensitivity, the platform is well suitable for measuring and detecting gases like carbon dioxide, methane, dinitrogen oxide, ammonia, ethanol vapour, refrigerants, etc. The sensor is based on the White-cell NDIR approach and realizes a path length of 1.28 m in a device with an external length of less than 10 cm. High mechanical accuracy of the optical system, temperature controlled optics, highly stable electronics and an optimized mirror surfaces allow a detection level as low as 0.007 ppm.
A simple monitoring system of indoor air pollution is proposed by integrating a novel colorimetric detector of formaldehyde (HCHO) and a function of a built-in camera on mobile phone. The colorimetric detector employs a solid phase colorimetric reagent made from AHMT, ZnO, KIO4 and agar, and changes color from white to purple by exposure to HCHO gas. The degree of color changes expressed in RGB model responded to the HCHO concentration levels both in air and from building materials. Limit of quantitation of the detector with 24h-exposure resulted in 0.011 mg/m(3) of air concentration which meets a requirement of methodology to detect indoor air quality guideline level of HCHO set by WHO. The detector is also applicable to classify HCHO-emitting materials at least into Type 1, whose emission flux is greater than 120 μg/m(2)/h, and others. Then, variation of the acquired photo images was investigated by using various mobile phones and changing conditions of photography. As a result, the calibration of the measured color intensity with a color standard reduced the variation of the results and gave a significant output when the auto-focused images were taken under the condition of common indoor environment.
With the help of micro-electromechanical systems (MEMS) and complementary metal-oxide-semiconductor (CMOS) technology, a portable micro gas chromatography ([Formula: see text]) system for lung cancer associated volatile organic compounds (VOCs) detection is realized for the first time. The system is composed of an MEMS preconcentrator, an MEMS separation column, and a CMOS system-on-chip (SoC). The preconcentrator provides a concentration ratio of 2170. The separation column can separate more than seven types of lung cancer associated VOCs. The SoC is fabricated by a TSMC [Formula: see text] 2P4M process including the CMOS VOCs detector, sensor calibration circuit, low-noise chopper instrumentation amplifier (IA), 10 bit analog to digital converter, and the microcontrol unit (MCU). Experimental results show that the system is able to detect seven types of lung cancer associated VOCs (acetone, 2-butanone, benzene, heptane, toluene, m-xylene, 1,3,5-trimethylbenzene). The concentration linearity is [Formula: see text] and the detection sensitivity is up to 15 ppb with 1,3,5-trimethylbenzene.
A highly sensitive on-site colorimetric forensic sensor has been developed for the quantitative detection of hydrogen sulfide and ammonia gases. The sensor consists of metal-ion-modified silica-gel powders placed in a glass tube. The powder color changes upon reaction with toxic hydrogen sulfide and ammonia gases. It is capable of easily detecting toxic gases in the concentration range between 100 ppm, which is considered as immediately dangerous to life and health, and 3000 ppm, which may cause death, by using a glass tube with an inner diameter of 3 mm. As the sensor reported here is insensitive to environmental conditions such as temperature or humidity, and is featured by simplicity, fast response, high sensitivity, and easily understandable results based on absolute affirmative/negative response, it is expected to be effectively used for on-site applications such as testing the existence of toxic gases in confined working and industrial spaces.
In 2010, the research on adsorbing diesel by biomass materials was carried out in our lab. Consistent with previous studies, both floating and adsorption performance of thermally modified biomass were improved, while the cost increased a lot. Inspired by previous studies on oil-absorbing composite materials, both the floating and sorption performance of mechanically mixed composite of cattail and reed were experimentally investigated in 2012, and the factors affecting removal rates were optimized by orthogonal experimental method. The result showed that adsorption capacity of cattail-reed composite was larger than reed, and even larger than the superposition value of cattail and reed. The buoyancy of reed sharply decreased under oscillation conditions, while cattail and the composite were lesser. The optimum conditions for removal rate of cattail were as follows: adsorbent dosage of 0.7 g, oil film thickness of 0.55 mm, oscillation frequency of 0 r/min. Under the same conditions, the particle size of reed that could remove most of the oil was 380~500 μm and the best removal rate of the composite was found when the mass ratio of cattail and reed with the same particle size was 1:4.
The detection of carbon monoxide in solution and air has been achieved using simple, inexpensive systems based on the vinyl complexes [M(CHCHR)Cl(CO)(BTD)(PPh3 )2 ] (R=aryl, BTD=2,1,3-benzothiadiazole). Depending on the nature of the vinyl group, chromogenic and fluorogenic responses signalled the presence of this odourless, tasteless, invisible, and toxic gas. Solutions of the complexes in CHCl3 underwent rapid change between easily differentiated colours when exposed to air samples containing CO. More significantly, the adsorption of the complexes on silica produced colorimetric probes for the naked-eye detection of CO in the gas phase. Structural data for key species before and after the addition of CO were obtained by means of single X-ray diffraction studies. In all cases, the ruthenium and osmium vinyl complexes studied showed a highly selective response to CO with exceptionally low detection limits. Naked-eye detection of CO at concentrations as low as 5 ppb in air was achieved with the onset of toxic levels (i.e., 100 ppm), thus resulting in a remarkably clear colour change. Moreover, complexes bearing pyrenyl, naphthyl, and phenanthrenyl moieties were fluorescent, and greater sensitivities were achieved (through turn-on emission fluorescence) in the presence of CO both in solution and air. This behaviour was explored computationally using time-dependent density functional theory (TDDFT) experiments. In addition, the systems were shown to be selective for CO over all other gases tested, including water vapour and common organic solvents. Supporting the metal complexes on cellulose strips for use in an existing optoelectronic device allows numerical readings for the CO concentration to be obtained and provision of an alarm system.
© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Recent progress in amperometric electrochemical gas sensing is reviewed. Topics covered include the use of room temperature ionic liquids (RTILs) as solvents in gas sensors, the advantageous use of micro-electrodes rather than macro-electrodes, membrane free devices and intelligent gas sensors including the simultaneous monitoring of temperature and humidity via voltammetric methods.
In this paper, we propose tapered reflectors having stair-like structures that focus scattered infrared (IR) rays to enhance the detection performance of a non-dispersive IR (NDIR) CO2 sensor. We demonstrate that the sensitivity of the output voltage is increased by 2 and 1.27 times in simulations and experiments, respectively, compared with the case when conventionally tapered reflectors are used. Through applying a stair-like structure inside the tapered optical cavity, scattered IR rays are condensed, and more accurate CO2 concentration measurements are possible. In addition, we show that the output voltage changes only slightly with temperature and humidity variations compared with the conventionally tapered optical cavity. Because the proposed structure can be applied to any type of optical cavity without major modifications, we expect that it can resolve the performance limitations of low-end NDIR gas sensors.
A sensitive Polyaniline (PANI)/ titanium dioxide (TiO2) based toxic gas sensor deposited on quartz crystal microbalance (QCM) chip was fabricated and developed through electrostatic layer-by-layer (LbL) self-assembly (SA) with polyaniline (PANI) and titanium dioxide (TiO2) sol as original materials. The synthesis process and the obtained nanocomposite were confirmed through home-made measurement set-up, field-emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), fourier transform infrared spectroscopic (FTIR) and X-ray diffraction (XRD), which demonstrates an thin PANI/TiO2 nanocomposite sensing film was successfully achieved by LbL self-assembly. The sensor response was found greatly influenced by the number of deposited layers. The resulting PANI/TiO2 based gas sensor exhibited good sensitivity and smooth shift in terms of responses based on frequency data than that based on resistance data. It exhibited high sensitivity toward 10 ppm of three different toxic gases (ammonia, hydrogen sulfide and trimethylamine) with evident frequency shift, fast response and recovery time. The sensor was further demonstrated possessing excellent reversibility, long-term stability, as well as accepted selectivity with significant selectivity toward NH3, and trimethylamine (TMA), and H2S followed by. In real-time application, the designed corresponding examination set-up based on the obtained PANI/TiO2 based sensor exhibited excellent performance and accurate evaluation for three typical foodstuffs. The PANI/TiO2 nanocomposite based gas sensor coated on QCM substrate via LbL self-assembly provides a promising efficient sensor to detect toxic gases in relative low concentrations.
A new type of chemical sensor for gaseous nitrogen oxides (NOx, the sum of NO and NO2) has been fabricated by combining a porous glass-based NO2 sensing chip with an oxidizing agent. In this device, NO is first oxidized to NO2 over the oxidizer on a porous glass sheet (8 mm square, 1 mm thick) prepared by soaking in a sulfuric acid/potassium permanganate solution, after which the NO2 is detected by a second chip, the same size as the oxidizing chip, impregnated with Saltzman's reagent. A sensor of this type placed in a miniature aluminum holder (3 × 5 × 1.5 cm) was passively exposed to air containing ppm levels of NO or NO2. As a result, the chip changed from colorless to dark red and a plot of absorbance at 525 nm against the total exposure (defined as the sum of the product of the instantaneous gas concentration by the exposure interval) was linear. Based on the slope of the plot obtained from the NO2 exposure trials, the detection limit of the sensor was approximately 0.2 ppm NO2 assuming a 1 h exposure. It was also found that these devices exhibited equivalent sensitivity to both NO and NO2, indicating that these sensors are capable of measuring the combined NO and NO2 concentration.
In recent years, the need of measurement and detection of samples in situ or with very small volume and low concentration (low sub parts per billion) is a cause for going to miniaturize systems via micro electromechanical system (MEMS) technology. Gas chromatography (GC) is a common technique that is widely used for separating and measuring the semi volatile and volatile compounds. Conventional GCs are bulky and cannot be used for in situ analysis, hence in the last decades many studies have been reported with the aim of designing and developing chip-based GC. The focus of this review is to follow and investigate the development and the achievements in the field of chip-based GC and its components from beginning up to now.
