An Interoperable Architecture for Air Pollution Early Warning System Based on Sensor Web
NASA Astrophysics Data System (ADS)
Samadzadegan, F.; Zahmatkesh, H.; Saber, M.; Ghazi khanlou, H. J.
2013-09-01
Environmental monitoring systems deal with time-sensitive issues which require quick responses in emergency situations. Handling the sensor observations in near real-time and obtaining valuable information is challenging issues in these systems from a technical and scientific point of view. The ever-increasing population growth in urban areas has caused certain problems in developing countries, which has direct or indirect impact on human life. One of applicable solution for controlling and managing air quality by considering real time and update air quality information gathered by spatially distributed sensors in mega cities, using sensor web technology for developing monitoring and early warning systems. Urban air quality monitoring systems using functionalities of geospatial information system as a platform for analysing, processing, and visualization of data in combination with Sensor Web for supporting decision support systems in disaster management and emergency situations. This system uses Sensor Web Enablement (SWE) framework of the Open Geospatial Consortium (OGC), which offers a standard framework that allows the integration of sensors and sensor data into spatial data infrastructures. SWE framework introduces standards for services to access sensor data and discover events from sensor data streams as well as definition set of standards for the description of sensors and the encoding of measurements. The presented system provides capabilities to collect, transfer, share, process air quality sensor data and disseminate air quality status in real-time. It is possible to overcome interoperability challenges by using standard framework. In a routine scenario, air quality data measured by in-situ sensors are communicated to central station where data is analysed and processed. The extracted air quality status is processed for discovering emergency situations, and if necessary air quality reports are sent to the authorities. This research proposed an architecture to represent how integrate air quality sensor data stream into geospatial data infrastructure to present an interoperable air quality monitoring system for supporting disaster management systems by real time information. Developed system tested on Tehran air pollution sensors for calculating Air Quality Index (AQI) for CO pollutant and subsequently notifying registered users in emergency cases by sending warning E-mails. Air quality monitoring portal used to retrieving and visualize sensor observation through interoperable framework. This system provides capabilities to retrieve SOS observation using WPS in a cascaded service chaining pattern for monitoring trend of timely sensor observation.
Understanding social and behavioral drivers and impacts of air quality sensor use.
Hubbell, Bryan J; Kaufman, Amanda; Rivers, Louie; Schulte, Kayla; Hagler, Gayle; Clougherty, Jane; Cascio, Wayne; Costa, Dan
2018-04-15
Lower-cost air quality sensors (hundreds to thousands of dollars) are now available to individuals and communities. This technology is undergoing a rapid and fragmented evolution, resulting in sensors that have uncertain data quality, measure different air pollutants and possess a variety of design attributes. Why and how individuals and communities choose to use sensors is arguably influenced by social context. For example, community experiences with environmental exposures and health effects and related interactions with industry and government can affect trust in traditional air quality monitoring. To date, little social science research has been conducted to evaluate why or how sensors, and sensor data, are used by individuals and communities, or how the introduction of sensors changes the relationship between communities and air quality managers. This commentary uses a risk governance/responsible innovation framework to identify opportunities for interdisciplinary research that brings together social scientists with air quality researchers involved in developing, testing, and deploying sensors in communities. Potential areas for social science research include communities of sensor users; drivers for use of sensors and sensor data; behavioral, socio-political, and ethical implications of introducing sensors into communities; assessing methods for communicating sensor data; and harnessing crowdsourcing capabilities to analyze sensor data. Social sciences can enhance understanding of perceptions, attitudes, behaviors, and other human factors that drive levels of engagement with and trust in different types of air quality data. New transdisciplinary research bridging social sciences, natural sciences, engineering, and design fields of study, and involving citizen scientists working with professionals from a variety of backgrounds, can increase our understanding of air sensor technology use and its impacts on air quality and public health. Published by Elsevier B.V.
Baron, Ronan; Saffell, John
2017-11-22
This review examines the use of amperometric electrochemical gas sensors for monitoring inorganic gases that affect urban air quality. First, we consider amperometric gas sensor technology including its development toward specifically designed air quality sensors. We then review recent academic and research organizations' studies where this technology has been trialed for air quality monitoring applications: early studies showed the potential of electrochemical gas sensors when colocated with reference Air Quality Monitoring (AQM) stations. Spatially dense networks with fast temporal resolution provide information not available from sparse AQMs with longer recording intervals. We review how this technology is being offered as commercial urban air quality networks and consider the remaining challenges. Sensors must be sensitive, selective, and stable; air quality monitors/nodes must be electronically and mechanically well designed. Data correction is required and models with differing levels of sophistication are being designed. Data analysis and validation is possibly the biggest remaining hurdle needed to deliver reliable concentration readings. Finally, this review also considers the roles of companies, urban infrastructure requirements, and public research in the development of this technology.
This Air Sensor Guidebook has been developed by the U.S. EPA to assist those interested in potentially using lower cost air quality sensor technologies for air quality measurements. Its development was in direct response to a request for such a document following a recent scienti...
Development of indoor environmental index: Air quality index and thermal comfort index
NASA Astrophysics Data System (ADS)
Saad, S. M.; Shakaff, A. Y. M.; Saad, A. R. M.; Yusof, A. M.; Andrew, A. M.; Zakaria, A.; Adom, A. H.
2017-03-01
In this paper, index for indoor air quality (also known as IAQI) and thermal comfort index (TCI) have been developed. The IAQI was actually modified from previous outdoor air quality index (AQI) designed by the United States Environmental Protection Agency (US EPA). In order to measure the index, a real-time monitoring system to monitor indoor air quality level was developed. The proposed system consists of three parts: sensor module cloud, base station and service-oriented client. The sensor module cloud (SMC) contains collections of sensor modules that measures the air quality data and transmit the captured data to base station through wireless. Each sensor modules includes an integrated sensor array that can measure indoor air parameters like Carbon Dioxide, Carbon Monoxide, Ozone, Nitrogen Dioxide, Oxygen, Volatile Organic Compound and Particulate Matter. Temperature and humidity were also being measured in order to determine comfort condition in indoor environment. The result from several experiments show that the system is able to measure the air quality presented in IAQI and TCI in many indoor environment settings like air-conditioner, chemical present and cigarette smoke that may impact the air quality. It also shows that the air quality are changing dramatically, thus real-time monitoring system is essential.
Spatial and Temporal Trends of Air Pollutants in the South Coast Basin Using Low Cost Sensors
The emergence of small, portable, low-cost air sensors has encouraged a shift from traditional monitoring approaches for air quality. The U.S. Environmental Protection Agency (U.S. EPA), in collaboration with the South Coast Air Quality Management District’s (SCAQMD) Air Quality ...
End-user perspective of low-cost sensors for outdoor air pollution monitoring.
Rai, Aakash C; Kumar, Prashant; Pilla, Francesco; Skouloudis, Andreas N; Di Sabatino, Silvana; Ratti, Carlo; Yasar, Ansar; Rickerby, David
2017-12-31
Low-cost sensor technology can potentially revolutionise the area of air pollution monitoring by providing high-density spatiotemporal pollution data. Such data can be utilised for supplementing traditional pollution monitoring, improving exposure estimates, and raising community awareness about air pollution. However, data quality remains a major concern that hinders the widespread adoption of low-cost sensor technology. Unreliable data may mislead unsuspecting users and potentially lead to alarming consequences such as reporting acceptable air pollutant levels when they are above the limits deemed safe for human health. This article provides scientific guidance to the end-users for effectively deploying low-cost sensors for monitoring air pollution and people's exposure, while ensuring reasonable data quality. We review the performance characteristics of several low-cost particle and gas monitoring sensors and provide recommendations to end-users for making proper sensor selection by summarizing the capabilities and limitations of such sensors. The challenges, best practices, and future outlook for effectively deploying low-cost sensors, and maintaining data quality are also discussed. For data quality assurance, a two-stage sensor calibration process is recommended, which includes laboratory calibration under controlled conditions by the manufacturer supplemented with routine calibration checks performed by the end-user under final deployment conditions. For large sensor networks where routine calibration checks are impractical, statistical techniques for data quality assurance should be utilised. Further advancements and adoption of sophisticated mathematical and statistical techniques for sensor calibration, fault detection, and data quality assurance can indeed help to realise the promised benefits of a low-cost air pollution sensor network. Copyright © 2017 Elsevier B.V. All rights reserved.
Air Sensor Toolbox provides information to citizen scientists, researchers and developers interested in learning more about new lower-cost compact air sensor technologies and tools for measuring air quality.
Air Sensor Toolbox for Citizen Scientists
EPA’s Air Sensor Toolbox provides information and guidance on new low-cost compact technologies for measuring air quality. It provides information to help citizens more effectively and accurately collect air quality data in their community.
Air Sensor Toolbox: Resources and Funding
EPA’s Air Sensor Toolbox provides information and guidance on new low-cost compact technologies for measuring air quality. It provides information to help citizens more effectively and accurately collect air quality data in their community.
Temperature and Humidity Calibration of a Low-Cost Wireless Dust Sensor for Real-Time Monitoring.
Hojaiji, Hannaneh; Kalantarian, Haik; Bui, Alex A T; King, Christine E; Sarrafzadeh, Majid
2017-03-01
This paper introduces the design, calibration, and validation of a low-cost portable sensor for the real-time measurement of dust particles within the environment. The proposed design consists of low hardware cost and calibration based on temperature and humidity sensing to achieve accurate processing of airborne dust density. Using commercial particulate matter sensors, a highly accurate air quality monitoring sensor was designed and calibrated using real world variations in humidity and temperature for indoor and outdoor applications. Furthermore, to provide a low-cost secure solution for real-time data transfer and monitoring, an onboard Bluetooth module with AES data encryption protocol was implemented. The wireless sensor was tested against a Dylos DC1100 Pro Air Quality Monitor, as well as an Alphasense OPC-N2 optical air quality monitoring sensor for accuracy. The sensor was also tested for reliability by comparing the sensor to an exact copy of itself under indoor and outdoor conditions. It was found that accurate measurements under real-world humid and temperature varying and dynamically changing conditions were achievable using the proposed sensor when compared to the commercially available sensors. In addition to accurate and reliable sensing, this sensor was designed to be wearable and perform real-time data collection and transmission, making it easy to collect and analyze data for air quality monitoring and real-time feedback in remote health monitoring applications. Thus, the proposed device achieves high quality measurements at lower-cost solutions than commercially available wireless sensors for air quality.
Communicating Instantaneous Air Quality Data: Pilot Project
Communicating Instantaneous Air Quality Data: Pilot ProjectEPA is launching a pilot project to test a new tool for making instantaneous outdoor air quality data useful for the public. The new “sensor scale” is designed to be used with sensors
Air-Microfluidics: Creating Small, Low-cost, Portable Air Quality Sensors
Air-microfluidics shows great promise in dramatically reducing the size, cost, and power requirements of future air quality sensors without compromising their accuracy. Microfabrication provides a suite of relatively new tools for the development of micro electro mechanical syste...
#2) Sensor Technology-State of the Science
Establish market surveys of commercially-available air quality sensorsConduct an extensive literature survey describing the state of sensor technologiesInvestigate emerging technologies and their potential to meet future air quality monitoring needs for the Agency as well as othe...
Communicating Instantaneous Air Quality Data: Pilot Project Feed Back
EPA is launching a pilot project to test a new tool for making instantaneous outdoor air quality data useful for the public. The new “sensor scale” is designed to be used with air quality sensors that provide data in short time increments – often as little
NASA Astrophysics Data System (ADS)
Feenstra, B. J.; Polidori, A.; Tisopulos, L.; Papapostolou, V.; Zhang, H.; Pathmanabhan, J.
2016-12-01
In recent years great progress has been made in development of low-cost miniature air quality sensing technologies. Such low-cost sensors offer a prospect of providing a real-time spatially dense information on pollutants, however, the quality of the data produced by these sensors is so far untested. In an effort to inform the general public about the actual performance of commercially available low-cost air quality sensors, in June 2014 the South Coast Air Quality Management District (SCAQMD) has established the Air Quality Sensor Performance Evaluation Center (AQ-SPEC). This program performs a thorough characterization of low-cost sensors under ambient (in the field) and controlled (in the laboratory) conditions. During the field testing, air quality sensors are operated side-by-side with Federal Reference Methods and Federal Equivalent Methods (FRM and FEM, respectively), which are routinely used to measure the ambient concentration of gaseous or particle pollutants for regulatory purposes. Field testing is conducted at two of SCAQMD's existing air monitoring stations, one in Rubidoux and one near the I-710 freeway. Sensors that demonstrate an acceptable performance in the field are brought back to the lab where a "characterization chamber" is used to challenge these devices with known concentrations of different particle and gaseous pollutants under different temperature and relative humidity levels. Testing results for each sensor are then summarized in a technical report and, along with other relevant information, posted online on a dedicated website (www.aqmd.gov/aq-spec) to educate the public about the capabilities of commercially available sensors and their potential applications. During this presentation, the results from two years of field and laboratory testing will be presented. The major strengths and weaknesses of some of the most commonly available particle and gaseous sensors will be discussed.
Development and evaluation of optical fiber NH3 sensors for application in air quality monitoring
NASA Astrophysics Data System (ADS)
Huang, Yu; Wieck, Lucas; Tao, Shiquan
2013-02-01
Ammonia is a major air pollutant emitted from agricultural practices. Sources of ammonia include manure from animal feeding operations and fertilizer from cropping systems. Sensor technologies with capability of continuous real time monitoring of ammonia concentration in air are needed to qualify ammonia emissions from agricultural activities and further evaluate human and animal health effects, study ammonia environmental chemistry, and provide baseline data for air quality standard. We have developed fiber optic ammonia sensors using different sensing reagents and different polymers for immobilizing sensing reagents. The reversible fiber optic sensors have detection limits down to low ppbv levels. The response time of these sensors ranges from seconds to tens minutes depending on transducer design. In this paper, we report our results in the development and evaluation of fiber optic sensor technologies for air quality monitoring. The effect of change of temperature, humidity and carbon dioxide concentration on fiber optic ammonia sensors has been investigated. Carbon dioxide in air was found not interfere the fiber optic sensors for monitoring NH3. However, the change of humidity can cause interferences to some fiber optic NH3 sensors depending on the sensor's transducer design. The sensitivity of fiber optic NH3 sensors was found depends on temperature. Methods and techniques for eliminating these interferences have been proposed.
NASA Astrophysics Data System (ADS)
Demuth, Dustin; Nuest, Daniel; Bröring, Arne; Pebesma, Edzer
2013-04-01
In the past year, a group of open hardware enthusiasts and citizen scientists had large success in the crowd-funding of an open hardware-based sensor platform for air quality monitoring, called the Air Quality Egg. Via the kickstarter platform, the group was able to collect triple the amount of money than needed to fulfill their goals. Data generated by the Air Quality Egg is pushed to the data logging platform cosm.com, which makes the devices a part of the Internet of Things. The project aims at increasing the participation of citizens in the collection of data, the development of sensors, the operation of sensor stations, and, as data on cosm is publicly available, the sharing, visualization and analysis of data. Air Quality Eggs can measure NO2 and CO concentrations, as well as relative humidity and temperature. The chosen sensors are low-cost and have limited precision and accurracy. The Air Quality Egg consists of a stationary outdoor and a stationary indoor unit. Each outdoor unit will wirelessly transmit air quality measurements to the indoor unit, which forwards the data to cosm. Most recent versions of the Air Quality Egg allow a rough calibration of the gas sensors and on-the-fly conversion from raw sensor readings (impedance) to meaningful air quality data expressed in units of parts per billion. Data generated by these low-cost platforms are not intended to replace well-calibrated official monitoring stations, but rather augment the density of the total monitoring network with citizen sensors. To improve the usability of the Air Quality Egg, we present a new and more advanced concept, called the AirQuality SenseBox. We made the outdoor platform more autonomous and location-aware by adding solarpanels and rechargeable batteries as a power source. The AirQuality SenseBox knows its own position from a GPS device attached to the platform. As a mobile sensor platform, it can for instance be attached to vehicles. A low-cost and low-power wireless chipset reads the sensors and broadcasts the data. The data is received by gateways that convert the data and forward it to services. Although cosm is still supported, we also use services that are more common in the scientific domain, in particular the OGC Sensor Observation Service. In contrast to the ``One Sender - One Receiver'' (pair) setup proposed by the platform developers, we follow a ``Many Senders - Many Receivers'' (mesh) solution. As data is broadcasted by the platforms, it can be received and processed by any gateway, and, as the sender is not bound to the receiver, applications different from the gateways can receive and evaluate the data measured by the platform. Advantages of our solution are: (i) prepared gateways, which have more precise data at hand, can send calibration instructions to the mobile sensor platforms when those are in proximity; (ii) redundancy is obtained by adding additional gateways, to avoid the loss of data if a gateway fails; (iii) autonomous stations can be ubiquitous, are robust, do not require frequent maintenance, and can be placed at arbitrary locations; (iv) the standardized interface is vendor-independent and allows direct integration into existing analysis software.
#2) Sensor Technology-State of the Science | Science ...
Establish market surveys of commercially-available air quality sensorsConduct an extensive literature survey describing the state of sensor technologiesInvestigate emerging technologies and their potential to meet future air quality monitoring needs for the Agency as well as other partners/stakeholders Develop sensor user guidesEducate sensor developers/sensors users on the state of low cost censorsFacilitate knowledge transfer to Federal/Regional/State air quality associatesWork directly with sensor developers to dramatically speed up the development of next generation air monitoring Support ORD’s Sensor Roadmap by focusing on areas of highest priority (NAAQS, Air Toxics, Citizen Science)Establish highly integrated research efforts across ORD and its partners (internal/external) to ensure consistent The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose.
Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary)
Griswold, William G.; RS, Abhijit; Johnston, Jill E.; Herting, Megan M.; Thorson, Jacob; Collier-Oxandale, Ashley; Hannigan, Michael
2017-01-01
In May 2017, a two-day workshop was held in Los Angeles (California, U.S.A.) to gather practitioners who work with low-cost sensors used to make air quality measurements. The community of practice included individuals from academia, industry, non-profit groups, community-based organizations, and regulatory agencies. The group gathered to share knowledge developed from a variety of pilot projects in hopes of advancing the collective knowledge about how best to use low-cost air quality sensors. Panel discussion topics included: (1) best practices for deployment and calibration of low-cost sensor systems, (2) data standardization efforts and database design, (3) advances in sensor calibration, data management, and data analysis and visualization, and (4) lessons learned from research/community partnerships to encourage purposeful use of sensors and create change/action. Panel discussions summarized knowledge advances and project successes while also highlighting the questions, unresolved issues, and technological limitations that still remain within the low-cost air quality sensor arena. PMID:29143775
Sun, Li; Wong, Ka Chun; Wei, Peng; Ye, Sheng; Huang, Hao; Yang, Fenhuan; Westerdahl, Dane; Louie, Peter K K; Luk, Connie W Y; Ning, Zhi
2016-02-05
This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO2) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring.
Sun, Li; Wong, Ka Chun; Wei, Peng; Ye, Sheng; Huang, Hao; Yang, Fenhuan; Westerdahl, Dane; Louie, Peter K.K.; Luk, Connie W.Y.; Ning, Zhi
2016-01-01
This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO2) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring. PMID:26861336
NASA Astrophysics Data System (ADS)
Mukherjee, A. D.; Brown, S. G.; McCarthy, M. C.
2017-12-01
A new generation of low cost air quality sensors have the potential to provide valuable information on the spatial-temporal variability of air pollution - if the measurements have sufficient quality. This study examined the performance of a particulate matter sensor model, the AirBeam (HabitatMap Inc., Brooklyn, NY), over a three month period in the urban environment of Sacramento, California. Nineteen AirBeam sensors were deployed at a regulatory air monitoring site collocated with meteorology measurements and as a local network over an 80 km2 domain in Sacramento, CA. This study presents the methodology to evaluate the precision, accuracy, and reliability of the sensors over a range of meteorological and aerosol conditions. The sensors demonstrated a robust degree of precision during collocated measurement periods (R2 = 0.98 - 0.99) and a moderate degree of correlation against a Beta Attenuation Monitor PM2.5 monitor (R2 0.6). A normalization correction is applied during the study period so that each AirBeam sensor in the network reports a comparable value. The role of the meteorological environment on the accuracy of the sensor measurements is investigated, along with the possibility of improving the measurements through a meteorology weighted correction. The data quality of the network of sensors is examined, and the spatial variability of particulate matter through the study domain derived from the sensor network is presented.
Monitoring urban air quality using a high-density network of low-cost sensor nodes in Oslo, Norway.
NASA Astrophysics Data System (ADS)
Castell, Nuria; Schneider, Philipp; Vogt, Matthias; Dauge, Franck R.; Lahoz, William; Bartonova, Alena
2017-04-01
Urban air quality represents a major public health burden and is a long-standing concern to citizens. Air pollution is associated with a range of diseases, symptoms and conditions that impair health and quality of life. In Oslo, traffic, especially exhaust from heavy-duty and private diesel vehicles and dust resuspension from studded tyres, together with wood burning in winter, are the main sources of pollution. Norway, as part of the European Economic Area, is obliged to comply with the European air quality regulations and ensure clean air. Despite this, Oslo has exceeded both the NO2 and PM10 thresholds for health protection defined in the Directive 2008/50/EC. The air quality in the Oslo area is continuously monitored in 12 compliance monitoring stations. These stations provide reliable and accurate data but their density is too low to provide a detailed spatial distribution of air quality. The emergence of low-cost nodes enables observations at high spatial resolution, providing the opportunity to enhance existing monitoring systems. However, the data generated by these nodes is significantly less accurate and precise than the data provided by reference equipment. We have conducted an evaluation of low-cost nodes to monitor NO2 and PM10, comparing the data collected with low-cost nodes against CEN (European Standardization Organization) reference analysers. During January and March 2016, a network of 24 nodes was deployed in Oslo. During January, high NO2 levels were observed for several days in a row coinciding with the formation of a thermal inversion. During March, we observed an episode with high PM10 levels due to road dust resuspension. Our results show that there is a major technical challenge associated with current commercial low-cost sensors, regarding the sensor robustness and measurement repeatability. Despite this, low-cost sensor nodes are able to reproduce the NO2 and PM10 variability. The data from the sensors was employed to generate detailed NO2 and PM10 air quality maps using a data fusion technique. This way we were able to offer localized air quality information for the city of Oslo. The outlook for commercial low-cost sensors is promising, and our results show that currently some sensors are already capable of providing coarse information about air quality, indicating if the air quality is good, moderate or if the air is heavily polluted. This type of information could be suitable for applications that aim to raise awareness, or engage the community by monitoring local air quality, as such applications do not require the same accuracy as scientific or regulatory monitoring.
WSN based indoor air quality monitoring in classrooms
NASA Astrophysics Data System (ADS)
Wang, S. K.; Chew, S. P.; Jusoh, M. T.; Khairunissa, A.; Leong, K. Y.; Azid, A. A.
2017-03-01
Indoor air quality monitoring is essential as the human health is directly affected by indoor air quality. This paper presents the investigations of the impact of undergraduate students' concentration during lecture due to the indoor air quality in classroom. Three environmental parameters such as temperature, relative humidity and concentration of carbon dioxide are measured using wireless sensor network based air quality monitoring system. This simple yet reliable system is incorporated with DHT-11 and MG-811 sensors. Two classrooms were selected to install the monitoring system. The level of indoor air quality were measured and students' concentration was assessed using intelligent test during normal lecturing section. The test showed significant correlation between the collected environmental parameters and the students' level of performances in their study.
Monitoring Indoor Air Quality for Enhanced Occupational Health.
Pitarma, Rui; Marques, Gonçalo; Ferreira, Bárbara Roque
2017-02-01
Indoor environments are characterized by several pollutant sources. Because people spend more than 90% of their time in indoor environments, several studies have pointed out the impact of indoor air quality on the etiopathogenesis of a wide number of non-specific symptoms which characterizes the "Sick Building Syndrome", involving the skin, the upper and lower respiratory tract, the eyes and the nervous system, as well as many building related diseases. Thus, indoor air quality (IAQ) is recognized as an important factor to be controlled for the occupants' health and comfort. The majority of the monitoring systems presently available is very expensive and only allow to collect random samples. This work describes the system (iAQ), a low-cost indoor air quality monitoring wireless sensor network system, developed using Arduino, XBee modules and micro sensors, for storage and availability of monitoring data on a web portal in real time. Five micro sensors of environmental parameters (air temperature, humidity, carbon monoxide, carbon dioxide and luminosity) were used. Other sensors can be added for monitoring specific pollutants. The results reveal that the system can provide an effective indoor air quality assessment to prevent exposure risk. In fact, the indoor air quality may be extremely different compared to what is expected for a quality living environment. Systems like this would have benefit as public health interventions to reduce the burden of symptoms and diseases related to "sick buildings".
Dias, M Beatrice; Taylor, Michael
2018-01-01
Background Air quality affects us all and is a rapidly growing concern in the 21st century. We spend the majority of our lives indoors and can be exposed to a number of pollutants smaller than 2.5 microns (particulate matter, PM2.5) resulting in detrimental health effects. Indoor air quality sensors have the potential to provide people with the information they need to understand their risk and take steps to reduce their exposure. One such sensor is the Speck sensor developed at the Community Robotics, Education and Technology Empowerment Lab at Carnegie Mellon University. This sensor provides users with continuous real-time and historical PM2.5 information, a Web-based platform where people can track their PM2.5 levels over time and learn about ways to reduce their exposure, and a venue (blog post) for the user community to exchange information. Little is known about how the use of such monitors affects people’s knowledge, attitudes, and behaviors with respect to indoor air pollution. Objective The aim of this study was to assess whether using the sensor changes what people know and do about indoor air pollution. Methods We conducted 2 studies. In the first study, we recruited 276 Pittsburgh residents online and through local branches of the Carnegie Library of Pittsburgh, where the Speck sensor was made available by the researchers in the library catalog. Participants completed a 10- to 15-min survey on air pollution knowledge (its health impact, sources, and mitigation options), perceptions of indoor air quality, confidence in mitigation, current behaviors toward air quality, and personal empowerment and creativity in the spring and summer of 2016. In our second study, we surveyed 26 Pittsburgh residents in summer 2016 who checked out the Speck sensor for 3 weeks on the same measures assessed in the first study, with additional questions about the perception and use of the sensor. Follow-up interviews were conducted with a subset of those who used the Speck sensor. Results A series of paired t tests found participants were significantly more knowledgeable (t25=−2.61, P=.02), reported having significantly better indoor air quality (t25=−5.20, P<.001), and felt more confident about knowing how to mitigate their risk (t25=−1.87, P=.07) after using the Speck sensor than before. McNemar test showed participants tended to take more action to reduce indoor air pollution after using the sensor (χ225=2.7, P=.10). Qualitative analysis suggested possible ripple effects of use, including encouraging family and friends to learn about indoor air pollution. Conclusions Providing people with low- or no-cost portable indoor air quality monitors, with a supporting Web-based platform that offers information about how to reduce risk, can help people better express perceptions and adopt behaviors commensurate with the risks they face. Thus, thoughtfully designed and deployed personal sensing devices can help empower people to take steps to reduce their risk. PMID:29519779
Wong-Parodi, Gabrielle; Dias, M Beatrice; Taylor, Michael
2018-03-08
Air quality affects us all and is a rapidly growing concern in the 21st century. We spend the majority of our lives indoors and can be exposed to a number of pollutants smaller than 2.5 microns (particulate matter, PM 2.5 ) resulting in detrimental health effects. Indoor air quality sensors have the potential to provide people with the information they need to understand their risk and take steps to reduce their exposure. One such sensor is the Speck sensor developed at the Community Robotics, Education and Technology Empowerment Lab at Carnegie Mellon University. This sensor provides users with continuous real-time and historical PM 2.5 information, a Web-based platform where people can track their PM 2.5 levels over time and learn about ways to reduce their exposure, and a venue (blog post) for the user community to exchange information. Little is known about how the use of such monitors affects people's knowledge, attitudes, and behaviors with respect to indoor air pollution. The aim of this study was to assess whether using the sensor changes what people know and do about indoor air pollution. We conducted 2 studies. In the first study, we recruited 276 Pittsburgh residents online and through local branches of the Carnegie Library of Pittsburgh, where the Speck sensor was made available by the researchers in the library catalog. Participants completed a 10- to 15-min survey on air pollution knowledge (its health impact, sources, and mitigation options), perceptions of indoor air quality, confidence in mitigation, current behaviors toward air quality, and personal empowerment and creativity in the spring and summer of 2016. In our second study, we surveyed 26 Pittsburgh residents in summer 2016 who checked out the Speck sensor for 3 weeks on the same measures assessed in the first study, with additional questions about the perception and use of the sensor. Follow-up interviews were conducted with a subset of those who used the Speck sensor. A series of paired t tests found participants were significantly more knowledgeable (t 25 =-2.61, P=.02), reported having significantly better indoor air quality (t 25 =-5.20, P<.001), and felt more confident about knowing how to mitigate their risk (t 25 =-1.87, P=.07) after using the Speck sensor than before. McNemar test showed participants tended to take more action to reduce indoor air pollution after using the sensor (χ 2 25 =2.7, P=.10). Qualitative analysis suggested possible ripple effects of use, including encouraging family and friends to learn about indoor air pollution. Providing people with low- or no-cost portable indoor air quality monitors, with a supporting Web-based platform that offers information about how to reduce risk, can help people better express perceptions and adopt behaviors commensurate with the risks they face. Thus, thoughtfully designed and deployed personal sensing devices can help empower people to take steps to reduce their risk. ©Gabrielle Wong-Parodi, M Beatrice Dias, Michael Taylor. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 08.03.2018.
NASA Astrophysics Data System (ADS)
French, R. A.; Preuss, P.
2013-12-01
Recent advances in the development of small-scale and inexpensive air pollutant sensors, coupled with the ubiquitous use of wireless and mobile technology, will transform the field of air quality monitoring. For the first time, the general public may purchase air monitors, which can measure their personal exposure to NOx, Ozone, black carbon, and VOCs for a few hundred dollars. Concerned citizens may now gather the data for themselves to answer questions such as, ';what am I breathing?' and ';is my air clean?' The research and policy community will have access to real-time air quality data collected at the local and regional scale, making targeted protection of environmental health possible. With these benefits come many questions from citizen scientists, policymakers, and researchers. These include, what is the quality of the data? How will the public interpret data from the air sensors and are there guidelines to interpret that data? How do you know if the air sensor is trustworthy? Recognizing that this revolution in air quality monitoring will proceed regardless of the involvement of the government, the Innovation Team at the EPA Office of Research and Development, in partnership with the Office of Enforcement and Compliance Assistance and the Office of Air and Radiation, seized the opportunity to ensure that users of next generation air sensors can realize the full potential benefits of these innovative technologies. These efforts include releasing an EPA Draft Roadmap for Next Generation Air Monitoring, testing air sensors under laboratory and field conditions, field demonstrations of new air sensor technology for the public, and building a community of air sensor developers, researchers, local, state and federal officials, and community members through workshops and a website. This presentation will review the status of those programs, highlighting the particular programs of interest to citizen scientists. The Next Generation Air Monitoring program may serve as a model for similar efforts in the EPA and at other Federal Agencies, who would like to take an active role in facilitating the future of citizen science and environmental monitoring.
CityAir app: Mapping air-quality perception using people as sensors
NASA Astrophysics Data System (ADS)
Castell, Nuria; Fredriksen, Mirjam; Cole-Hunter, Thomas; Robinson, Johanna; Keune, Hans; Nieuwenhuijsen, Mark; Bartonova, Alena
2016-04-01
Outdoor air pollution is a major environmental health problem affecting all people in developed and developing countries alike. Ambient (outdoor) air pollution in both cities and rural areas was estimated to cause 3.7 million premature deaths worldwide in 2012. In modern society, people are expending an increasing amount of time in polluted urban environments, thus increasing their exposure and associated health responses. Some cities provide information about air pollution levels to their citizens using air quality monitoring networks. However, due to their high cost and maintenance, the density of the monitoring networks is very low and not capable to capture the high temporal and spatial variability of air pollution. Thus, the citizen lacks a specific answer to the question of "how the air quality is in our surroundings". In the framework of the EU-funded CITI-SENSE project the innovative concept of People as Sensors is being applied to the field of outdoor air pollution. This is being done in eight European cities, including Barcelona, Belgrade, Edinburgh, Haifa, Ljubljana, Oslo, Ostrava and Vienna. People as Sensors defines a measurement model, in which measurements are not only taken by hardware sensors, but in which also humans can contribute with their individual "measurements" such as their subjective perception of air quality and other personal observations. In order to collect the personal observations a mobile app, CityAir, has been developed. CityAir allows citizens to rate the air quality in their surroundings with colour at their current location: green if air quality is very good, yellow if air quality is good, orange if air quality is poor and red if air quality is very poor. The users have also the possibility of indicating the source of pollution (i.e. traffic, industry, wood burning) and writing a comment. The information is on-line and accessible for other app users, thus contributing to create an air-quality map based on citizens' perception. Currently, 400 + Android OS and 180+ iOS smartphone users in 12+ countries have downloaded, installed and used CityAir. The central advantage of the People as Sensors approach is that it can complement costly physical sensor networks. The observations made in smartphones are shared and other persons can consult those to take decisions as for instance choosing a cleaner route to bicycle to work or avoid exercising in certain areas that day. The drawbacks are limited comparability and interpretability, and the inherent uncertainty. CityAir can be seen as a democratic platform for empowering citizens to contribute to environmental governance, facilitating the communication between the citizen and the decision makers. Citizens are encouraged to participate in sharing their perception on the air quality in their city. Citizens become agents of change by uncovering and sharing their perception of air quality in a place that matters to them. We discuss the current challenges: how to involve citizens in the use of the app and how to communicate and visualize the information in a way that is useful for the citizens; point out possible solutions, and pin-point directions for future research.
NASA Astrophysics Data System (ADS)
Jenerette, D.; Wang, J.; Chandler, M.; Ripplinger, J.; Koutzoukis, S.; Ge, C.; Castro Garcia, L.; Kucera, D.; Liu, X.
2017-12-01
Large uncertainties remain in identifying the distribution of urban air quality and temperature risks across neighborhood to regional scales. Nevertheless, many cities are actively expanding vegetation with an expectation to moderate both climate and air quality risks. We address these uncertainties through an integrated analysis of satellite data, atmospheric modeling, and in-situ environmental sensor networks maintained by citizen scientists. During the summer of 2017 we deployed neighborhood-scale networks of air temperature and ozone sensors through three campaigns across urbanized southern California. During each five-week campaign we deployed six sensor nodes that included an EPA federal equivalent method ozone sensor and a suite of meteorological sensors. Each node was further embedded in a network of 100 air temperature sensors that combined a randomized design developed by the research team and a design co-created by citizen scientists. Between 20 and 60 citizen scientists were recruited for each campaign, with local partners supporting outreach and training to ensure consistent deployment and data gathering. We observed substantial variation in both temperature and ozone concentrations at scales less than 4km, whole city, and the broader southern California region. At the whole city scale the average spatial variation with our ozone sensor network just for city of Long Beach was 26% of the mean, while corresponding variation in air temperature was only 7% of the mean. These findings contrast with atmospheric model estimates of variation at the regional scale of 11% and 1%. Our results show the magnitude of fine-scale variation underestimated by current models and may also suggest scaling functions that can connect neighborhood and regional variation in both ozone and temperature risks in southern California. By engaging citizen science with high quality sensors, satellite data, and real-time forecasting, our results help identify magnitudes of climate and air quality risk variation across scales and can guide individual decisions and urban policies surrounding vegetation to moderate these risks.
Bringing hands-on exploration of air quality technology to the ...
This is an educational presentation to the OAQPS Teachers Workshop on the PM sensor kit and other related air technology educational activities. This workshop for teachers and other educators includes topics, such as: how EPA manages air quality, the environmental health effects and risks of air pollution, climate change, and sustainability solutions and more. Attendees will also build a DYI Sensor kit and explore energy choices and the environment when they play the interactive board game developed by EPA scientists called Generate! This workshop for teachers and other educators includes topics, such as: how EPA manages air quality, the environmental health effects and risks of air pollution, climate change and sustainability and more. Attendees will also build a DYI Sensor kit and explore energy choices and the environment when they play the interactive board game developed by EPA scientists called Generate!
Low-Cost Sensor Units for Measuring Urban Air Quality
NASA Astrophysics Data System (ADS)
Popoola, O. A.; Mead, M.; Stewart, G.; Hodgson, T.; McLoed, M.; Baldovi, J.; Landshoff, P.; Hayes, M.; Calleja, M.; Jones, R.
2010-12-01
Measurements of selected key air quality gases (CO, NO & NO2) have been made with a range of miniature low-cost sensors based on electrochemical gas sensing technology incorporating GPS and GPRS for position and communication respectively. Two types of simple to operate sensors units have been designed to be deployed in relatively large numbers. Mobile handheld sensor units designed for operation by members of the public have been deployed on numerous occasions including in Cambridge, London and Valencia. Static sensor units have also been designed for long-term autonomous deployment on existing street furniture. A study was recently completed in which 45 sensor units were deployed in the Cambridge area for a period of 3 months. Results from these studies indicate that air quality varies widely both spatially and temporally. The widely varying concentrations found suggest that the urban environment cannot be fully understood using limited static site (AURN) networks and that a higher resolution, more dispersed network is required to better define air quality in the urban environment. The results also suggest that higher spatial and temporal resolution measurements could improve knowledge of the levels of individual exposure in the urban environment.
Measuring PM and related air pollutants using low-cost sensors
Emerging air quality sensors may play a key role in better characterizing levels of air pollution in a variety of settings There are a wide range of low-cost (< $500 US) sensors on the market, but few have been characterized. If accurate, this new generation of inexpensive sens...
Building and evaluating sensor-based Citizens' Observatories for improving quality of life in cities
NASA Astrophysics Data System (ADS)
Castell, Nuria; Lahoz, William; Schneider, Philipp; Høiskar, Britt Ann; Grossberndt, Sonja; Naderer, Clemens; Robinson, Johanna; Kocman, David; Horvat, Milena; Bartonova, Alena
2014-05-01
Urban air quality, the environmental quality of public spaces and indoor areas such as schools, are areas of great concern to citizens and policymakers. However, access to information addressing these areas is not always available in a user-friendly manner. In particular, the quality and quantity of this information is not consistent across these areas, and does not reflect differences in needs among users. The EU-funded CITI-SENSE project will build on the concept of the Citizens' Observatories to empower citizens to contribute to and participate in environmental governance, and enable them to support and influence decision making by policymakers. To achieve this goal, CITI-SENSE will develop, test, demonstrate and validate a community-based environmental monitoring and information system using low-cost sensors and Earth Observation applications. Key to achieving this goal is the chain "sensors-platforms-products-users" linking providers of technology to users: (i) technologies for distributed monitoring (sensors); (ii) information and communication technologies (platform); (iii) information products and services (products); (iv) and citizen involvement in both monitoring and societal decisions (users). The CITI-SENSE observatories cover three empowerment initiatives: urban air quality; public spaces; and school indoor quality. The empowerment initiatives are being performed at nine locations across Europe. Each location has adapted the generic case study to their local circumstances and has contacted the urban stakeholders needed to run the study. The empowerment initiatives are divided into two phases: a first phase (Pilot Study), and a second phase (Full Implementation). The main goal of the Pilot Study is to test and evaluate the chain "sensors-platform-products-users". To assess the results of the empowerment initiatives, key performance indicators (KPIs) are being developed; these include questionnaires for users. The KPIs will be used to design the full implementation phase of the project. First results from the Pilot Study will be presented for three participating cities: Ljubljana (Slovenia), Vienna (Austria) and Oslo (Norway), which differ in size, environmental conditions and social perception on local air quality. Ljubljana and Oslo empowerment initiatives include urban air quality, and school indoor air quality, while Vienna only includes urban air quality. For the area of urban air quality, the three cities will deploy a wireless network of five static sensor nodes and distribute five personal sensors among people to be carried while performing daily activities in the pilot study. The data will be accessible to users through mobile phones, web services and other devices. For the full implementation phase the sensor network will comprise a total of 20 to 40 static nodes, depending on the size of the city, and 20 personal nodes. For the school indoor air quality three sensors will be allocated inside the school and one outside. The data will be visible provided in school classrooms giving the students a unique and innovative approach to learn about air quality by being involved. Acknowledgements: CITI-SENSE is a Collaborative Project partly funded by the EU FP7-ENV-2012 under grant agreement no 308524. www.citi-sense.eu.
Empowering smartphone users with sensor node for air quality measurement
NASA Astrophysics Data System (ADS)
Oletic, Dinko; Bilas, Vedran
2013-06-01
We present an architecture of a sensor node developed for use with smartphones for participatory sensing of air quality in urban environments. Our solution features inexpensive metal-oxide semiconductor gas sensors (MOX) for measurement of CO, O3, NO2 and VOC, along with sensors for ambient temperature and humidity. We focus on our design of sensor interface consisting of power-regulated heater temperature control, and the design of resistance sensing circuit. Accuracy of the sensor interface is characterized. Power consumption of the sensor node is analysed. Preliminary data obtained from the CO gas sensors in laboratory conditions and during the outdoor field-test is shown.
NASA Astrophysics Data System (ADS)
Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.
2018-01-01
Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that it accounts for pollutant cross-sensitivities. This highlights the importance of developing multipollutant sensor packages (as opposed to single-pollutant monitors); we determined this is especially critical for NO2 and CO2. The evaluation reveals that only the RF-calibrated sensors meet the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. We also demonstrate that the RF-model-calibrated sensors could detect differences in NO2 concentrations between a near-road site and a suburban site less than 1.5 km away. From this study, we conclude that combining RF models with carefully controlled state-of-the-art multipollutant sensor packages as in the RAMP monitors appears to be a very promising approach to address the poor performance that has plagued low-cost air quality sensors.
AIRQino, a low-cost air quality mobile platform
NASA Astrophysics Data System (ADS)
Zaldei, Alessandro; Vagnoli, Carolina; Di Lonardo, Sara; Gioli, Beniamino; Gualtieri, Giovanni; Toscano, Piero; Martelli, Francesca; Matese, Alessandro
2015-04-01
Recent air quality regulations (Directive 2008/50/EC) enforce the transition from point-based monitoring networks to new tools that must be capable of mapping and forecasting air quality on the totality of land area, and therefore the totality of citizens. This implies new technologies such as models and additional indicative measurements, are needed in addition to accurate fixed air quality monitoring stations, that until now have been taken as reference by local administrators for the enforcement of various mitigation strategies. However, due to their sporadic spatial distribution, they cannot describe the highly resolved spatial pollutant variations within cities. Integrating additional indicative measurements may provide adequate information on the spatial distribution of the ambient air quality, also allowing for a reduction of the required minimum number of fixed sampling points, whose high cost and complex maintenance still remain a crucial concern for local administrators. New low-cost and small size sensors are becoming available, that could be employed in air quality monitoring including mobile applications. However, accurate assessment of their accuracy and performance both in controlled and real monitoring conditions is crucially needed. Quantifying sensor response is a significant challenge due to the sensitivity to ambient temperature and humidity and the cross-sensitivity to others pollutant species. This study reports the development of an Arduino compatible electronic board (AIRQino) which integrates a series of low-cost metal oxide and NDIR sensors for air quality monitoring, with sensors to measure air temperature, relative humidity, noise, solar radiation and vertical acceleration. A comparative assessment was made for CO2, CO, NO2, CH4, O3, VOCs concentrations, temperature and relative humidity. A controlled climatic chamber study (-80°C / +80°C) was performed to verify temperature and humidity interference using reference gas cylinders and high quality reference sensors. The AIRQino was installed on mobile vectors such as bikes, buses and trams in the cities of Firenze and Siracusa (Italy), that send data real-time to a Web portal. By integrating a microprocessor unit it is capable of directly updating calibration coefficients to provide corrected sensor output as digital string through RS232 serial port. Results from the lab tests and the 'real world' mobile applications are presented and discussed, to assess to what extent this sensor technology might be useful for the development of portable, compact, wireless and cost-effective system for air quality monitoring in urban areas at high spatio-temporal resolution.
NASA Technical Reports Server (NTRS)
Ross, A.; Richards, A.; Keith, K.; Frew, C.; Boseck, J.; Sutton, S.; Watts, C.; Rickman, D.
2007-01-01
This project focused on a comprehensive utilization of air quality model products as decision support tools (DST) needed for public health applications. A review of past and future air quality measurement methods and their uncertainty, along with the relationship of air quality to national and global public health, is vital. This project described current and future NASA satellite remote sensing and ground sensing capabilities and the potential for using these sensors to enhance the prediction, prevention, and control of public health effects that result from poor air quality. The qualitative uncertainty of current satellite remotely sensed air quality, the ground-based remotely sensed air quality, the air quality/public health model, and the decision making process is evaluated in this study. Current peer-reviewed literature suggests that remotely sensed air quality parameters correlate well with ground-based sensor data. A satellite remote-sensed and ground-sensed data complement is needed to enhance the models/tools used by policy makers for the protection of national and global public health communities
NASA Astrophysics Data System (ADS)
Cross, Eben S.; Williams, Leah R.; Lewis, David K.; Magoon, Gregory R.; Onasch, Timothy B.; Kaminsky, Michael L.; Worsnop, Douglas R.; Jayne, John T.
2017-09-01
The environments in which we live, work, and play are subject to enormous variability in air pollutant concentrations. To adequately characterize air quality (AQ), measurements must be fast (real time), scalable, and reliable (with known accuracy, precision, and stability over time). Lower-cost air-quality-sensor technologies offer new opportunities for fast and distributed measurements, but a persistent characterization gap remains when it comes to evaluating sensor performance under realistic environmental sampling conditions. This limits our ability to inform the public about pollution sources and inspire policy makers to address environmental justice issues related to air quality. In this paper, initial results obtained with a recently developed lower-cost air-quality-sensor system are reported. In this project, data were acquired with the ARISense integrated sensor package over a 4.5-month time interval during which the sensor system was co-located with a state-operated (Massachusetts, USA) air quality monitoring station equipped with reference instrumentation measuring the same pollutant species. This paper focuses on validating electrochemical (EC) sensor measurements of CO, NO, NO2, and O3 at an urban neighborhood site with pollutant concentration ranges (parts per billion by volume, ppb; 5 min averages, ±1σ): [CO] = 231 ± 116 ppb (spanning 84-1706 ppb), [NO] = 6.1 ± 11.5 ppb (spanning 0-209 ppb), [NO2] = 11.7 ± 8.3 ppb (spanning 0-71 ppb), and [O3] = 23.2 ± 12.5 ppb (spanning 0-99 ppb). Through the use of high-dimensional model representation (HDMR), we show that interference effects derived from the variable ambient gas concentration mix and changing environmental conditions over three seasons (sensor flow-cell temperature = 23.4 ± 8.5 °C, spanning 4.1 to 45.2 °C; and relative humidity = 50.1 ± 15.3 %, spanning 9.8-79.9 %) can be effectively modeled for the Alphasense CO-B4, NO-B4, NO2-B43F, and Ox-B421 sensors, yielding (5 min average) root mean square errors (RMSE) of 39.2, 4.52, 4.56, and 9.71 ppb, respectively. Our results substantiate the potential for distributed air pollution measurements that could be enabled with these sensors.
Air Sensor Guidebook | Science Inventory | US EPA
This Air Sensor Guidebook has been developed by the U.S. EPA to assist those interested in potentially using lower cost air quality sensor technologies for air quality measurements. Its development was in direct response to a request for such a document following a recent scientific conference (Apps and Sensors for Air Pollution-2012). Low cost air quality sensors ($100-$2500) are now commercially available in a wide variety of designs and capabilities. This is an emerging technology area and one that is quickly evolving. Even so, their availability has resulted in questions from many as to how they might be used appropriately. This document attempts to provide useful information concerning some of those questions. The National Exposure Research Laboratory’s (NERL’s) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA’s mission to protect human health and the environment. HEASD’s research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA’s strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and pol
Schneider, Philipp; Castell, Nuria; Vogt, Matthias; Dauge, Franck R; Lahoz, William A; Bartonova, Alena
2017-09-01
The recent emergence of low-cost microsensors measuring various air pollutants has significant potential for carrying out high-resolution mapping of air quality in the urban environment. However, the data obtained by such sensors are generally less reliable than that from standard equipment and they are subject to significant data gaps in both space and time. In order to overcome this issue, we present here a data fusion method based on geostatistics that allows for merging observations of air quality from a network of low-cost sensors with spatial information from an urban-scale air quality model. The performance of the methodology is evaluated for nitrogen dioxide in Oslo, Norway, using both simulated datasets and real-world measurements from a low-cost sensor network for January 2016. The results indicate that the method is capable of producing realistic hourly concentration fields of urban nitrogen dioxide that inherit the spatial patterns from the model and adjust the prior values using the information from the sensor network. The accuracy of the data fusion method is dependent on various factors including the total number of observations, their spatial distribution, their uncertainty (both in terms of systematic biases and random errors), as well as the ability of the model to provide realistic spatial patterns of urban air pollution. A validation against official data from air quality monitoring stations equipped with reference instrumentation indicates that the data fusion method is capable of reproducing city-wide averaged official values with an R 2 of 0.89 and a root mean squared error of 14.3 μg m -3 . It is further capable of reproducing the typical daily cycles of nitrogen dioxide. Overall, the results indicate that the method provides a robust way of extracting useful information from uncertain sensor data using only a time-invariant model dataset and the knowledge contained within an entire sensor network. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Broday, David M
2017-10-02
The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented.
2017-01-01
The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented. PMID:28974042
Development of a wireless air pollution sensor package for aerial-sampling of emissions
A new sensor system for mobile and aerial emission sampling was developed for open area pollutant sources, such as prescribed forest burns. The sensor system, termed “Kolibri”, consists of multiple low-cost air quality sensors measuring CO2, CO, samplers for particulate matter wi...
Low cost sensors: Field evaluations and multi-sensor approaches for emissions factors
The development, and application of low cost sensors to measure both particulate and gas-phase air pollutants is poised to explode over the next several years. The need for the sensors is driven by poor air quality experienced in inhabited regions throughout the world, in both de...
NASA Astrophysics Data System (ADS)
Collier, A. M.; Hannigan, M.; Piedrahita, R.; Casey, J. G.; Johnston, J.; Chiang, S.
2016-12-01
The growing accessibility of low-cost air quality monitoring technologies has led to their increased usage among community-based organizations, particularly for the monitoring of pollutants dangerous to human health (e.g., hazardous air pollutants or HAPS). However, often these low-cost sensors are `off-the-shelf' and are being utilized in a manner that differs from their intended purpose - necessitating high quality calibrations. For example, VOC sensors intended for the detection of high levels of a particular compound in an industrial setting may instead be used for ambient monitoring of a group of VOCs. Academic/community partnerships can be an ideal way to improve this type of sensor quantification while providing a community with not only the opportunity to use these technologies with additional support around data quality, but also the opportunity for education around the abilities and applications of low-cost sensors. In the spring of 2016, our lab at the University of Colorado, Boulder partnered with communities in Los Angeles and Kern County to deploy low-cost air quality monitors for the purpose of quantifying methane and non-methane hydrocarbon signals in an effort to learn more about potential impacts from local sources (e.g., nearby highways and oil & gas development). The monitoring platform was developed in our lab and is capable of logging multiple gas phase species as well as some environmental parameters. The monitors include two different metal oxide VOC sensors - each with slightly different sensing capabilities. Calibration was achieved using a pre- and post-deployment field normalization to reference monitoring equipment maintained by the South Coast Air Quality Management District. Monitors were then deployed at locations throughout the community. We will present results on our efforts to quantify a total non-methane hydrocarbon signal, observations from the field data, and recommendations for academic/community partnerships formed around air quality monitoring.
High-Density, High-Resolution, Low-Cost Air Quality Sensor Networks for Urban Air Monitoring
NASA Astrophysics Data System (ADS)
Mead, M. I.; Popoola, O. A.; Stewart, G.; Bright, V.; Kaye, P.; Saffell, J.
2012-12-01
Monitoring air quality in highly granular environments such as urban areas which are spatially heterogeneous with variable emission sources, measurements need to be made at appropriate spatial and temporal scales. Current routine air quality monitoring networks generally are either composed of sparse expensive installations (incorporating e.g. chemiluminescence instruments) or higher density low time resolution systems (e.g. NO2 diffusion tubes). Either approach may not accurately capture important effects such as pollutant "hot spots" or adequately capture spatial (or temporal) variability. As a result, analysis based on data from traditional low spatial resolution networks, such as personal exposure, may be inaccurate. In this paper we present details of a sophisticated, low-cost, multi species (gas phase, speciated PM, meteorology) air quality measurement network methodology incorporating GPS and GPRS which has been developed for high resolution air quality measurements in urban areas. Sensor networks developed in the Centre for Atmospheric Science (University of Cambridge) incorporated electrochemical gas sensors configured for use in urban air quality studies operating at parts-per-billion (ppb) levels. It has been demonstrated that these sensors can be used to measure key air quality gases such as CO, NO and NO2 at the low ppb mixing ratios present in the urban environment (estimated detection limits <4ppb for CO and NO and <1ppb for NO2. Mead et al (submitted Aug., 2012)). Based on this work, a state of the art multi species instrument package for deployment in scalable sensor networks has been developed which has general applicability. This is currently being employed as part of a major 3 year UK program at London Heathrow airport (the Sensor Networks for Air Quality (SNAQ) Heathrow project). The main project outcome is the creation of a calibrated, high spatial and temporal resolution data set for O3, NO, NO2, SO2, CO, CO2, VOCstotal, size-speciated PM, temperature, relative humidity, wind speed and direction. The network incorporates existing GPRS infrastructures for real time sending of data with low overheads in terms of cost, effort and installation. In this paper we present data from the SNAQ Heathrow project as well as previous deployments showing measurement capability at the ppb level for NO, NO2 and CO. We show that variability can be observed and measured quantitatively using these sensor networks over widely differing time scales from individual emission events, diurnal variability associated with traffic and meteorological conditions, through to longer term synoptic weather conditions and seasonal behaviour. This work demonstrates a widely applicable generic capability to urban areas, airports as well as other complex emissions environments making this sensor system methodology valuable for scientific, policy and regulatory issues. We conclude that the low-cost high-density network philosophy has the potential to provide a more complete assessment of the high-granularity air quality structure generally observed in the environment. Further, when appropriately deployed, has the potential to offer a new paradigm in air quality quantification and monitoring.
Castell, Nuria; Schneider, Philipp; Grossberndt, Sonja; Fredriksen, Mirjam F; Sousa-Santos, Gabriela; Vogt, Mathias; Bartonova, Alena
2018-08-01
In Norway, children in kindergartens spend significant time outdoors under all weather conditions, and there is thus a natural concern about the quality of outdoor air. It is well known that air pollution is associated with a wide variety of adverse health impacts for children, with greater impact on children with asthma. Especially during winter and spring, kindergartens in Oslo that are situated close to streets with busy traffic, or in areas where wood burning is used for house heating, can experience many days with bad air quality. During these periods, updated information on air quality levels can help the kindergarten teachers to plan appropriate outdoor activities and thus protect children's health. We have installed 17 low-cost air quality nodes in kindergartens in Oslo. These nodes are smaller, cheaper and less complex to use than traditional equipment. Performance evaluation shows that while they are less accurate and suffer from higher uncertainty than reference equipment, they still can provide reliable coarse information about local pollution. The main challenge when using this technology is that calibration parameters might change with time depending on the atmospheric conditions. Thus, even if the sensors are calibrated a priori, once deployed, and especially if they are deployed for a long time, it is not possible to determine if a node is over- or under-estimating the concentration levels. To enhance the data from the sensors, we employed a data fusion technique that allows generating a detailed air quality map merging the data from the sensors and the data from an urban model, thus being able to offer air quality information to any location within Oslo. We arranged a focus group with the participation of local administration, kindergarten staff and parents to understand their opinion and needs related to the air quality information that was provided to the participant kindergartens. They expressed concern about the data quality but agree that having updated information on the air quality in the surroundings of kindergartens can help them to reduce children's exposure to air pollution. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Community Air Monitoring Where You Live in EPA Region 5
Community air monitoring projects that are using air sensor technology to monitor air quality in states in EPA’s Region 5 are providing the public with more information on the quality of the air they breathe.
Community Air Monitoring Where You Live in EPA Region 8
Community air monitoring projects that are using air sensor technology to monitor air quality in states in EPA’s Region 8 are providing the public with more information on the quality of the air they breathe.
Regulatory Considerations of Lower Cost Air Pollution Sensor Data Performance
Low-cost, portable air quality sensors could be the next generation of air monitoring, however, this nascent technology is not without risk. This article looks at how the U.S. Environmental Protection Agency (EPA) uses air monitoring data, the procedures followed to ensure and a...
Micro sensor node for air pollutant monitoring: hardware and software issues.
Choi, Sukwon; Kim, Nakyoung; Cha, Hojung; Ha, Rhan
2009-01-01
Wireless sensor networks equipped with various gas sensors have been actively used for air quality monitoring. Previous studies have typically explored system issues that include middleware or networking performance, but most research has barely considered the details of the hardware and software of the sensor node itself. In this paper, we focus on the design and implementation of a sensor board for air pollutant monitoring applications. Several hardware and software issues are discussed to explore the possibilities of a practical WSN-based air pollution monitoring system. Through extensive experiments and evaluation, we have determined the various characteristics of the gas sensors and their practical implications for air pollutant monitoring systems.
Citizen science and air quality research at the U.S. EPA
This presentation summarizes some of the broad areas of effort at EPA related to citizen science and then focuses in specifically on recent developments in air quality. The air quality focus includes briefly summarizing emerging air sensor technology and a variety of projects th...
Urban air quality measurements using a sensor-based system
NASA Astrophysics Data System (ADS)
Ródenas, Mila; Hernández, Daniel; Gómez, Tatiana; López, Ramón; Muñoz, Amalia
2017-04-01
Air pollution levels in urban areas have increased the interest, not only of the scientific community but also of the general public, and both at the regional and at the European level. This interest has run in parallel to the development of miniaturized sensors, which only since very recently are suitable for air quality measurements. Certainly, their small size and price allows them to be used as a network of sensors capable of providing high temporal and spatial frequency measurements to characterize an area or city and with increasing potential, under certain considerations, as a complement of conventional methods. Within the frame of the LIFE PHOTOCITYTEX project (use of photocatalytic textiles to help reducing air pollution), CEAM has developed a system to measure gaseous compounds of importance for urban air quality characterization. This system, which allows an autonomous power supply, uses commercial NO, NO2, O3 and CO2 small sensors and incorporates measurements of temperature and humidity. A first version, using XBee boards (Radiofrequency) for communications has been installed in the urban locations defined by the project (tunnel and school), permitting the long-term air quality characterization of sites in the presence of the textiles. An improved second version of the system which also comprises a sensor for measuring particles and which uses GPRS for communications, has been developed and successfully installed in the city center of Valencia. Data are sent to a central server where they can be accessed by citizens in nearly real time and online and, in general, they can be utilized in the air quality characterization, for decision-making related to decontamination (traffic regulation, photocatalytic materials, etc.), in air quality models or in mobile applications of interest for the citizens. Within this work, temporal trends obtained with this system in different urban locations will be shown, discussing the impact of the characteristics of the selected sites and the seasonal variability on the air quality levels observed. Acknowledgements EUPHORE staff is acknowledged. PHOTOCITYTEX project (LIFE13 ENV/ES/000603) is acknowledged for supporting this work. Fundación CEAM is partly supported by Generalitat Valenciana - Spain.
Calibration of low-cost gas sensors for an urban air quality monitoring network
NASA Astrophysics Data System (ADS)
Scott, A.; Kelley, C.; He, C.; Ghugare, P.; Lehman, A.; Benish, S.; Stratton, P.; Dickerson, R. R.; Zuidema, C.; Azdoud, Y.; Ren, X.
2017-12-01
In a warming world, environmental pollution may be exacerbated by anthropogenic activities, such as climate change and the urban heat island effect, as well as natural phenomena such as heat waves. However, monitoring air pollution at federal reference standards (approximately 1 part per billion or ppb for ambient ozone) is cost-prohibitive in heterogeneous urban areas as many expensive devices are required to fully capture a region's geo-spatial variability. Innovation in low-cost sensors provide a potential solution, yet technical challenges remain to overcome possible imprecision in the data. We present the calibrations of ozone and nitrous dioxide from a low-cost air quality monitoring device designed for the Baltimore Open Air Project. The sensors used in this study are commercially available thin film electrochemical sensors from SPEC Sensor, which are amperometric, meaning they generate current proportional to volumetric fraction of gas. The results of sensor calibrations in the laboratory and field are presented.
Field calibration of electrochemical NO2 sensors in a citizen science context
NASA Astrophysics Data System (ADS)
Mijling, Bas; Jiang, Qijun; de Jonge, Dave; Bocconi, Stefano
2018-03-01
In many urban areas the population is exposed to elevated levels of air pollution. However, real-time air quality is usually only measured at few locations. These measurements provide a general picture of the state of the air, but they are unable to monitor local differences. New low-cost sensor technology is available for several years now, and has the potential to extend official monitoring networks significantly even though the current generation of sensors suffer from various technical issues.Citizen science experiments based on these sensors must be designed carefully to avoid generation of data which is of poor or even useless quality. This study explores the added value of the 2016 Urban AirQ campaign, which focused on measuring nitrogen dioxide (NO2) in Amsterdam, the Netherlands. Sixteen low-cost air quality sensor devices were built and distributed among volunteers living close to roads with high traffic volume for a 2-month measurement period. Each electrochemical sensor was calibrated in-field next to an air monitoring station during an 8-day period, resulting in R2 ranging from 0.3 to 0.7. When temperature and relative humidity are included in a multilinear regression approach, the NO2 accuracy is improved significantly, with R2 ranging from 0.6 to 0.9. Recalibration after the campaign is crucial, as all sensors show a significant signal drift in the 2-month measurement period. The measurement series between the calibration periods can be corrected for after the measurement period by taking a weighted average of the calibration coefficients.Validation against an independent air monitoring station shows good agreement. Using our approach, the standard deviation of a typical sensor device for NO2 measurements was found to be 7 µg m-3, provided that temperatures are below 30 °C. Stronger ozone titration on street sides causes an underestimation of NO2 concentrations, which 75 % of the time is less than 2.3 µg m-3.Our findings show that citizen science campaigns using low-cost sensors based on the current generations of electrochemical NO2 sensors may provide useful complementary data on local air quality in an urban setting, provided that experiments are properly set up and the data are carefully analysed.
Kim, MinJeong; Liu, Hongbin; Kim, Jeong Tai; Yoo, ChangKyoo
2014-08-15
Sensor faults in metro systems provide incorrect information to indoor air quality (IAQ) ventilation systems, resulting in the miss-operation of ventilation systems and adverse effects on passenger health. In this study, a new sensor validation method is proposed to (1) detect, identify and repair sensor faults and (2) evaluate the influence of sensor reliability on passenger health risk. To address the dynamic non-Gaussianity problem of IAQ data, dynamic independent component analysis (DICA) is used. To detect and identify sensor faults, the DICA-based squared prediction error and sensor validity index are used, respectively. To restore the faults to normal measurements, a DICA-based iterative reconstruction algorithm is proposed. The comprehensive indoor air-quality index (CIAI) that evaluates the influence of the current IAQ on passenger health is then compared using the faulty and reconstructed IAQ data sets. Experimental results from a metro station showed that the DICA-based method can produce an improved IAQ level in the metro station and reduce passenger health risk since it more accurately validates sensor faults than do conventional methods. Copyright © 2014 Elsevier B.V. All rights reserved.
Findings from the 2013 EPA Air Sensors Workshop
This article, first published in the January 2014 issue of EM Magazine, provides findings from the Air Sensors 2013: Data Quality & Applications workshop held in Research Triangle Park, N.C., in March 2013.
Public engagement on urban air pollution: an exploratory study of two interventions.
Oltra, Christian; Sala, Roser; Boso, Àlex; Asensio, Sergi López
2017-06-01
The use of portable sensors to measure air quality is a promising approach for the management of urban air quality given its potential to improve public participation in environmental issues and to promote healthy behaviors. However, not all the projects that use air quality mobile sensors consider the potential effects of their use on the attitudes and behaviors of non-expert individuals. This study explores the experiences, perceptions, attitudes, and behavioral intentions of 12 participants who used a real-time NO 2 sensor over a period of 7 days in the metropolitan area of Barcelona and compares them with 16 participants who did not have access to the device but rather to documentary information. The study design is based on recombined focus groups who met at the beginning and end of a 7-day activity. The results suggest that the experience with the sensors, in comparison with the traditional information, generates greater motivation among participants. Also, that the use of the sensor seems to support a more specific awareness of the problem of air pollution. In relation to risk perception, the textual and visual information seems to generate stronger beliefs of severity among participants. In both groups, beliefs of low controllability and self-efficacy are observed. Neither using the sensor nor reading the documentary information seems to contribute positively in this sense. The results of the study aim to contribute to the design of public involvement strategies in urban air pollution.
Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang
2013-01-01
Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859
Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang
2013-11-27
Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.
NASA Technical Reports Server (NTRS)
Alvarado, U. R.; Bortner, M. H.; Grenda, R. N.; Brehm, W. F.; Frippel, G. G.; Alyea, F.; Kraiman, H.; Folder, P.; Krowitz, L.
1982-01-01
The technology advancements that will be necessary to implement the atmospheric observation systems are considered. Upper and lower atmospheric air quality and meteorological parameters necessary to support the air quality investigations were included. The technology needs were found predominantly in areas related to sensors and measurements of air quality and meteorological measurements.
Outlier Detection in Urban Air Quality Sensor Networks.
van Zoest, V M; Stein, A; Hoek, G
2018-01-01
Low-cost urban air quality sensor networks are increasingly used to study the spatio-temporal variability in air pollutant concentrations. Recently installed low-cost urban sensors, however, are more prone to result in erroneous data than conventional monitors, e.g., leading to outliers. Commonly applied outlier detection methods are unsuitable for air pollutant measurements that have large spatial and temporal variations as occur in urban areas. We present a novel outlier detection method based upon a spatio-temporal classification, focusing on hourly NO 2 concentrations. We divide a full year's observations into 16 spatio-temporal classes, reflecting urban background vs. urban traffic stations, weekdays vs. weekends, and four periods per day. For each spatio-temporal class, we detect outliers using the mean and standard deviation of the normal distribution underlying the truncated normal distribution of the NO 2 observations. Applying this method to a low-cost air quality sensor network in the city of Eindhoven, the Netherlands, we found 0.1-0.5% of outliers. Outliers could reflect measurement errors or unusual high air pollution events. Additional evaluation using expert knowledge is needed to decide on treatment of the identified outliers. We conclude that our method is able to detect outliers while maintaining the spatio-temporal variability of air pollutant concentrations in urban areas.
Low cost sensors for PM and related air pollutants in the US and India
Emerging air quality sensors have a variety of possible applications. If accurate and reliable, they have a number of benefits over conventional monitors. They are low-cost, lightweight, and have low power consumption. Because of their low cost, a dense array of sensors instal...
An airborne remote sensing system for urban air quality
NASA Technical Reports Server (NTRS)
Duncan, L. J.; Friedman, E. J.; Keitz, E. L.; Ward, E. A.
1974-01-01
Several NASA sponsored remote sensors and possible airborne platforms were evaluated. Outputs of dispersion models for SO2 and CO pollution in the Washington, D.C. area were used with ground station data to establish the expected performance and limitations of the remote sensors. Aircraft/sensor support requirements are discussed. A method of optimum flight plan determination was made. Cost trade offs were performed. Conclusions about the implementation of various instrument packages as parts of a comprehensive air quality monitoring system in Washington are presented.
Indoor air quality inspection and analysis system based on gas sensor array
NASA Astrophysics Data System (ADS)
Gao, Xiang; Wang, Mingjiang; Fan, Binwen
2017-08-01
A detection and analysis system capable of measuring the concentration of four major gases in indoor air is designed. It uses four gas sensors constitute a gas sensor array, to achieve four indoor gas concentration detection, while the detection of data for further processing to reduce the cross-sensitivity between the gas sensor to improve the accuracy of detection.
MEMS device for mass market gas and chemical sensors
NASA Astrophysics Data System (ADS)
Kinkade, Brian R.; Daly, James T.; Johnson, Edward A.
2000-08-01
Gas and chemical sensors are used in many applications. Industrial health and safety monitors allow companies to meet OSHA requirements by detecting harmful levels of toxic or combustible gases. Vehicle emissions are tested during annual inspections. Blood alcohol breathalizers are used by law enforcement. Refrigerant leak detection ensures that the Earth's ozone layer is not being compromised. Industrial combustion emissions are also monitored to minimize pollution. Heating and ventilation systems watch for high levels of carbon dioxide (CO2) to trigger an increase in fresh air exchange. Carbon monoxide detectors are used in homes to prevent poisoning from poor combustion ventilation. Anesthesia gases are monitored during a patients operation. The current economic reality is that two groups of gas sensor technologies are competing in two distinct existing market segments - affordable (less reliable) chemical reaction sensors for consumer markets and reliable (expensive) infrared (IR) spectroscopic sensors for industrial, laboratory, and medical instrumentation markets. Presently high volume mass-market applications are limited to CO detectros and on-board automotive emissions sensors. Due to reliability problems with electrochemical sensor-based CO detectors there is a hesitancy to apply these sensors in other high volume applications. Applications such as: natural gas leak detection, non-invasive blood glucose monitoring, home indoor air quality, personal/portable air quality monitors, home fire/burnt cooking detector, and home food spoilage detectors need a sensor that is a small, efficient, accurate, sensitive, reliable, and inexpensive. Connecting an array of these next generation gas sensors to wireless networks that are starting to proliferate today creates many other applications. Asthmatics could preview the air quality of their destinations as they venture out into the day. HVAC systems could determine if fresh air intake was actually better than the air in the house. Internet grocery delivery services could check for spoiled foods in their clients' refrigerators. City emissions regulators could monitor the various emissions sources throughout the area from their desk to predict how many pollution vouchers they will need to trade in the next week. We describe a new component architecture for mass-market sensors based on silicon microelectromechanical systems (MEMS) technology. MEMS are micrometer-scale devices that can be fabricated as discrete devices or large arrays, using the technology of integrated circuit manufacturing. These new photonic bandgap and MEMS fabricataion technologies will simplify the component technology to provide high-quality gas and chemical sensors at consumer prices.
Next Generation Air Quality Platform: Openness and Interoperability for the Internet of Things.
Kotsev, Alexander; Schade, Sven; Craglia, Massimo; Gerboles, Michel; Spinelle, Laurent; Signorini, Marco
2016-03-18
The widespread diffusion of sensors, mobile devices, social media and open data are reconfiguring the way data underpinning policy and science are being produced and consumed. This in turn is creating both opportunities and challenges for policy-making and science. There can be major benefits from the deployment of the IoT in smart cities and environmental monitoring, but to realize such benefits, and reduce potential risks, there is an urgent need to address current limitations, including the interoperability of sensors, data quality, security of access and new methods for spatio-temporal analysis. Within this context, the manuscript provides an overview of the AirSensEUR project, which establishes an affordable open software/hardware multi-sensor platform, which is nonetheless able to monitor air pollution at low concentration levels. AirSensEUR is described from the perspective of interoperable data management with emphasis on possible use case scenarios, where reliable and timely air quality data would be essential.
Next Generation Air Quality Platform: Openness and Interoperability for the Internet of Things
Kotsev, Alexander; Schade, Sven; Craglia, Massimo; Gerboles, Michel; Spinelle, Laurent; Signorini, Marco
2016-01-01
The widespread diffusion of sensors, mobile devices, social media and open data are reconfiguring the way data underpinning policy and science are being produced and consumed. This in turn is creating both opportunities and challenges for policy-making and science. There can be major benefits from the deployment of the IoT in smart cities and environmental monitoring, but to realize such benefits, and reduce potential risks, there is an urgent need to address current limitations, including the interoperability of sensors, data quality, security of access and new methods for spatio-temporal analysis. Within this context, the manuscript provides an overview of the AirSensEUR project, which establishes an affordable open software/hardware multi-sensor platform, which is nonetheless able to monitor air pollution at low concentration levels. AirSensEUR is described from the perspective of interoperable data management with emphasis on possible use case scenarios, where reliable and timely air quality data would be essential. PMID:26999160
Air Quality Monitoring and Sensor Technologies
EPA scientist Ron Williams presented on the features, examination, application, examples, and data quality of continuous monitoring study designs at EPA's Community Air Monitoring Training in July 2015.
NASA Astrophysics Data System (ADS)
Papapostolou, Vasileios; Zhang, Hang; Feenstra, Brandon J.; Polidori, Andrea
2017-12-01
A state-of-the-art integrated chamber system has been developed for evaluating the performance of low-cost air quality sensors. The system contains two professional grade chamber enclosures. A 1.3 m3 stainless-steel outer chamber and a 0.11 m3 Teflon-coated stainless-steel inner chamber are used to create controlled aerosol and gaseous atmospheres, respectively. Both chambers are temperature and relative humidity controlled with capability to generate a wide range of environmental conditions. The system is equipped with an integrated zero-air system, an ozone and two aerosol generation systems, a dynamic dilution calibrator, certified gas cylinders, an array of Federal Reference Method (FRM), Federal Equivalent Method (FEM), and Best Available Technology (BAT) reference instruments and an automated control and sequencing software. Our experiments have demonstrated that the chamber system is capable of generating stable and reproducible aerosol and gas concentrations at low, medium, and high levels. This paper discusses the development of the chamber system along with the methods used to quantitatively evaluate sensor performance. Considering that a significant number of academic and research institutions, government agencies, public and private institutions, and individuals are becoming interested in developing and using low-cost air quality sensors, it is important to standardize the procedures used to evaluate their performance. The information discussed herein provides a roadmap for entities who are interested in characterizing air quality sensors in a rigorous, systematic and reproducible manner.
Matrix Factorisation-based Calibration For Air Quality Crowd-sensing
NASA Astrophysics Data System (ADS)
Dorffer, Clement; Puigt, Matthieu; Delmaire, Gilles; Roussel, Gilles; Rouvoy, Romain; Sagnier, Isabelle
2017-04-01
Internet of Things (IoT) is extending internet to physical objects and places. The internet-enabled objects are thus able to communicate with each other and with their users. One main interest of IoT is the ease of production of huge masses of data (Big Data) using distributed networks of connected objects, thus making possible a fine-grained yet accurate analysis of physical phenomena. Mobile crowdsensing is a way to collect data using IoT. It basically consists of acquiring geolocalized data from the sensors (from or connected to the mobile devices, e.g., smartphones) of a crowd of volunteers. The sensed data are then collectively shared using wireless connection—such as GSM or WiFi—and stored on a dedicated server to be processed. One major application of mobile crowdsensing is environment monitoring. Indeed, with the proliferation of miniaturized yet sensitive sensors on one hand and, on the other hand, of low-cost microcontrollers/single-card PCs, it is easy to extend the sensing abilities of smartphones. Alongside the conventional, regulated, bulky and expensive instruments used in authoritative air quality stations, it is then possible to create a large-scale mobile sensor network providing insightful information about air quality. In particular, the finer spatial sampling rate due to such a dense network should allow air quality models to take into account local effects such as street canyons. However, one key issue with low-cost air quality sensors is the lack of trust in the sensed data. In most crowdsensing scenarios, the sensors (i) cannot be calibrated in a laboratory before or during their deployment and (ii) might be sparsely or continuously faulty (thus providing outliers in the data). Such issues should be automatically handled from the sensor readings. Indeed, due to the masses of generated data, solving the above issues cannot be performed by experts but requires specific data processing techniques. In this work, we assume that some mobile sensors share some information using the APISENSE® crowdsensing platform and we aim to calibrate the sensor responses from the data directly. For that purpose, we express the sensor readings as a low-rank matrix with missing entries and we revisit self-calibration as a Matrix Factorization (MF) problem. In our proposed framework, one factor matrix contains the calibration parameters while the other is structured by the calibration model and contains some values of the sensed phenomenon. The MF calibration approach also uses the precise measurements from ATMO—the French public institution—to drive the calibration of the mobile sensors. MF calibration can be improved using, e.g., the mean calibration parameters provided by the sensor manufacturers, or using sparse priors or a model of the physical phenomenon. All our approaches are shown to provide a better calibration accuracy than matrix-completion-based and robust-regression-based methods, even in difficult scenarios involving a lot of missing data and/or very few accurate references. When combined with a dictionary of air quality patterns, our experiments suggest that MF is not only able to perform sensor network calibration but also to provide detailed maps of air quality.
A black carbon air quality network
NASA Astrophysics Data System (ADS)
Kirchstetter, T.; Caubel, J.; Cados, T.; Preble, C.; Rosen, A.
2016-12-01
We developed a portable, power efficient black carbon sensor for deployment in an air quality network in West Oakland, California. West Oakland is a San Francisco Bay Area residential/industrial community adjacent to regional port and rail yard facilities, and is surrounded by major freeways. As such, the community is affected by diesel particulate matter emissions from heavy-duty diesel trucks, locomotives, and ships associated with freight movement. In partnership with Environmental Defense Fund, the Bay Area Air Quality Management District, and the West Oakland Environmental Indicators Project, we are collaborating with community members to build and operate a 100-sensor black carbon measurement network for a period of several months. The sensor employs the filter-based light transmission method to measure black carbon. Each sensor node in the network transmits data hourly via SMS text messages. Cost, power consumption, and performance are considered in choosing components (e.g., pump) and operating conditions (e.g., sample flow rate). In field evaluation trials over several weeks at three monitoring locations, the sensor nodes provided black carbon concentrations comparable to commercial instruments and ran autonomously for a week before sample filters and rechargeable batteries needed to be replaced. Buildup to the 100-sensor network is taking place during Fall 2016 and will overlap with other ongoing air monitoring projects and monitoring platforms in West Oakland. Sensors will be placed along commercial corridors, adjacent to freeways, upwind of and within the Port, and throughout the residential community. Spatial and temporal black carbon concentration patterns will help characterize pollution sources and demonstrate the value of sensing networks for characterizing intra-urban air pollution concentrations and exposure to air pollution.
A smart indoor air quality sensor network
NASA Astrophysics Data System (ADS)
Wen, Jin
2006-03-01
The indoor air quality (IAQ) has an important impact on public health. Currently, the indoor air pollution, caused by gas, particle, and bio-aerosol pollutants, is considered as the top five environmental risks to public health and has an estimated cost of $2 billion/year due to medical cost and lost productivity. Furthermore, current buildings are especially vulnerable for chemical and biological warfare (CBW) agent contamination because the central air conditioning and ventilation system serve as a nature carrier to spread the released agent from one location to the whole indoor environment within a short time period. To assure the IAQ and safety for either new or existing buildings, real time comprehensive IAQ and CBW measurements are needed. With the development of new sensing technologies, economic and reliable comprehensive IAQ and CBW sensors become promising. However, few studies exist that examine the design and evaluation issues related to IAQ and CBW sensor network. In this paper, relevant research areas including IAQ and CBW sensor development, demand control ventilation, indoor CBW sensor system design, and sensor system design for other areas such as water system protection, fault detection and diagnosis, are reviewed and summarized. Potential research opportunities for IAQ and CBW sensor system design and evaluation are discussed.
Technology review: prototyping platforms for monitoring ambient conditions.
Afolaranmi, Samuel Olaiya; Ramis Ferrer, Borja; Martinez Lastra, Jose Luis
2018-05-08
The monitoring of ambient conditions in indoor spaces is very essential owing to the amount of time spent indoors. Specifically, the monitoring of air quality is significant because contaminated air affects the health, comfort and productivity of occupants. This research work presents a technology review of prototyping platforms for monitoring ambient conditions in indoor spaces. It involves the research on sensors (for CO 2 , air quality and ambient conditions), IoT platforms, and novel and commercial prototyping platforms. The ultimate objective of this review is to enable the easy identification, selection and utilisation of the technologies best suited for monitoring ambient conditions in indoor spaces. Following the review, it is recommended to use metal oxide sensors, optical sensors and electrochemical sensors for IAQ monitoring (including NDIR sensors for CO 2 monitoring), Raspberry Pi for data processing, ZigBee and Wi-Fi for data communication, and ThingSpeak IoT platform for data storage, analysis and visualisation.
An Indoor Monitoring System for Ambient Assisted Living Based on Internet of Things Architecture
Marques, Gonçalo; Pitarma, Rui
2016-01-01
The study of systems and architectures for ambient assisted living (AAL) is undoubtedly a topic of great relevance given the aging of the world population. The AAL technologies are designed to meet the needs of the aging population in order to maintain their independence as long as possible. As people typically spend more than 90% of their time in indoor environments, indoor air quality (iAQ) is perceived as an imperative variable to be controlled for the inhabitants’ wellbeing and comfort. Advances in networking, sensors, and embedded devices have made it possible to monitor and provide assistance to people in their homes. The continuous technological advancements make it possible to build smart objects with great capabilities for sensing and connecting several possible advancements in ambient assisted living systems architectures. Indoor environments are characterized by several pollutant sources. Most of the monitoring frameworks instantly accessible are exceptionally costly and only permit the gathering of arbitrary examples. iAQ is an indoor air quality system based on an Internet of Things paradigm that incorporates in its construction Arduino, ESP8266, and XBee technologies for processing and data transmission and micro sensors for data acquisition. It also allows access to data collected through web access and through a mobile application in real time, and this data can be accessed by doctors in order to support medical diagnostics. Five smaller scale sensors of natural parameters (air temperature, moistness, carbon monoxide, carbon dioxide, and glow) were utilized. Different sensors can be included to check for particular contamination. The results reveal that the system can give a viable indoor air quality appraisal in order to anticipate technical interventions for improving indoor air quality. Indeed indoor air quality might be distinctively contrasted with what is normal for a quality living environment. PMID:27869682
An Indoor Monitoring System for Ambient Assisted Living Based on Internet of Things Architecture.
Marques, Gonçalo; Pitarma, Rui
2016-11-17
The study of systems and architectures for ambient assisted living (AAL) is undoubtedly a topic of great relevance given the aging of the world population. The AAL technologies are designed to meet the needs of the aging population in order to maintain their independence as long as possible. As people typically spend more than 90% of their time in indoor environments, indoor air quality (iAQ) is perceived as an imperative variable to be controlled for the inhabitants' wellbeing and comfort. Advances in networking, sensors, and embedded devices have made it possible to monitor and provide assistance to people in their homes. The continuous technological advancements make it possible to build smart objects with great capabilities for sensing and connecting several possible advancements in ambient assisted living systems architectures. Indoor environments are characterized by several pollutant sources. Most of the monitoring frameworks instantly accessible are exceptionally costly and only permit the gathering of arbitrary examples. iAQ is an indoor air quality system based on an Internet of Things paradigm that incorporates in its construction Arduino, ESP8266, and XBee technologies for processing and data transmission and micro sensors for data acquisition. It also allows access to data collected through web access and through a mobile application in real time, and this data can be accessed by doctors in order to support medical diagnostics. Five smaller scale sensors of natural parameters (air temperature, moistness, carbon monoxide, carbon dioxide, and glow) were utilized. Different sensors can be included to check for particular contamination. The results reveal that the system can give a viable indoor air quality appraisal in order to anticipate technical interventions for improving indoor air quality. Indeed indoor air quality might be distinctively contrasted with what is normal for a quality living environment.
Low-Cost Sensor POD Design Considerations
Public concern about air quality is growing in communities around the globe as citizens learn more about the potential health effects of the air they breathe. Air quality monitoring has often been restricted to organizations administering Federal Reference Method (FRM) or Federal...
Low-Cost Sensor POD Design Considerations
Public concern about air quality is growing in communities around the globe as citizens learn more about the potential health effects of the air they breathe.1 Air quality monitoring has often been restricted to organizations administering Federal Reference Method (FRM) or Federa...
Air-microfluidics is a field that has the potential to dramatically reduce the size, cost, and power requirements of future air quality sensors. Microfabrication provides a suite of relatively new tools for the development of micro electro mechanical systems (MEMS) that can be ap...
Community-led Air Sensor Evaluation: New Tools for Citizen Scientists Fact Sheet
EPA has developed a guide and analysis tool for citizen scientists to evaluate the performance of low-cost sensors and interpret the data they collect to help citizen scientists interested in learning about local air quality.
Uncertainty in air quality observations using low-cost sensors
NASA Astrophysics Data System (ADS)
Castell, Nuria; Dauge, Franck R.; Dongol, Rozina; Vogt, Matthias; Schneider, Philipp
2016-04-01
Air pollution poses a threat to human health, and the WHO has classified air pollution as the world's largest single environmental health risk. In Europe, the majority of the population lives in areas where air quality levels frequently exceed WHO's ambient air quality guidelines. The emergence of low-cost, user-friendly and very compact air pollution platforms allowing observations at high spatial resolution in near real-time, provides us with new opportunities to simultaneously enhance existing monitoring systems as well as enable citizens to engage in more active environmental monitoring (citizen science). However the data sets generated by low-cost sensors show often questionable data quality. For many sensors, neither their error characteristics nor how their measurement capability holds up over time or through a range of environmental conditions, have been evaluated. We have conducted an exhaustive evaluation of the commercial low-cost platform AQMesh (measuring NO, NO2, CO, O3, PM10 and PM2.5) in laboratory and in real-world conditions in the city of Oslo (Norway). Co-locations in field of 24 platforms were conducted over a 6 month period (April to September 2015) allowing to characterize the temporal variability in the performance. Additionally, the field performance included the characterization on different monitoring urban monitoring sites characteristic of both traffic and background conditions. All the evaluations have been conducted against CEN reference method analyzers maintained according to the Norwegian National Reference Laboratory quality system. The results show clearly that a good performance in laboratory does not imply similar performance in real-world outdoor conditions. Moreover, laboratory calibration is not suitable for subsequent measurements in urban environments. In order to reduce the errors, sensors require on-site field calibration. Even after such field calibration, the platforms show a significant variability in the performance due to changes in the environmental conditions. Currently there is a lack of testing to ensure adequate sensor performance prior to marketing such instruments. Even when manufacturers provide detailed specification sheets, there is little guarantee that the specifications can actually be met in real-world conditions. Data quality is a pertinent concern, especially when citizens are collecting and interpreting the data by themselves. Poor or unknown data quality can lead to incorrect or inappropriate decisions. We present the experiences gained within the EU project CITI-SENSE, where low-cost sensors are one of the tools employed to empower citizens in air quality issues.
Castell, Nuria; Dauge, Franck R; Schneider, Philipp; Vogt, Matthias; Lerner, Uri; Fishbain, Barak; Broday, David; Bartonova, Alena
2017-02-01
The emergence of low-cost, user-friendly and very compact air pollution platforms enable observations at high spatial resolution in near-real-time and provide new opportunities to simultaneously enhance existing monitoring systems, as well as engage citizens in active environmental monitoring. This provides a whole new set of capabilities in the assessment of human exposure to air pollution. However, the data generated by these platforms are often of questionable quality. We have conducted an exhaustive evaluation of 24 identical units of a commercial low-cost sensor platform against CEN (European Standardization Organization) reference analyzers, evaluating their measurement capability over time and a range of environmental conditions. Our results show that their performance varies spatially and temporally, as it depends on the atmospheric composition and the meteorological conditions. Our results show that the performance varies from unit to unit, which makes it necessary to examine the data quality of each node before its use. In general, guidance is lacking on how to test such sensor nodes and ensure adequate performance prior to marketing these platforms. We have implemented and tested diverse metrics in order to assess if the sensor can be employed for applications that require high accuracy (i.e., to meet the Data Quality Objectives defined in air quality legislation, epidemiological studies) or lower accuracy (i.e., to represent the pollution level on a coarse scale, for purposes such as awareness raising). Data quality is a pertinent concern, especially in citizen science applications, where citizens are collecting and interpreting the data. In general, while low-cost platforms present low accuracy for regulatory or health purposes they can provide relative and aggregated information about the observed air quality. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Do-It-Yourself Air Sensors – Exploring the Atmosphere and Turning on Light Bulbs!?
These are educational slides that will be presented in a webinar to the National Science Teachers Association. Topics covered include general air quality, current EPA research, and EPA's particle sensor kit that is a classroom activity.
The Role of Unmanned Aerial Systems-Sensors in Air Quality Research
The use of unmanned aerial systems (UASs) and miniaturized sensors for a variety of scientific and security purposes has rapidly increased. UASs include aerostats (tethered balloons) and remotely controlled, unmanned aerial vehicles (UAVs) including lighter-than-air vessels, fix...
Personal Air Pollution Exposure Monitoring using Low Cost Sensors in Chennai City
NASA Astrophysics Data System (ADS)
Reddy Yasa, Pavan; Shiva, Nagendra S. N.
2016-04-01
Air quality in many cities is deteriorating due to rapid urbanization and motorization. In the past, most of the health impacts studies in the urban areas have considered stationary air quality monitoring station data for health impact assessment. Since, there exist a spatial and temporal variation of air quality because of rapid change in land use pattern and complex interaction between emission sources and meteorological conditions, the human exposure assessment using stationary data may not provide realistic information. In such cases low cost sensors monitoring is viable in providing both spatial and temporal variations of air pollutant concentrations. In the present study an attempt has been made to use low cost sensor for monitoring the personal exposure to the two criteria pollutants CO and PM2.5 at 3 different locations of Chennai city. Maximum and minimum concentrations of CO and PM2.5 were found to be 5.4ppm, 0.8ppm and 534.8μg/m3, 1.9μg/m3 respectively. Results showed high concentrations near the intersection and low concentrations in the straight road.
Woodall, George M; Hoover, Mark D; Williams, Ronald; Benedict, Kristen; Harper, Martin; Soo, Jhy-Charm; Jarabek, Annie M; Stewart, Michael J; Brown, James S; Hulla, Janis E; Caudill, Motria; Clements, Andrea L; Kaufman, Amanda; Parker, Alison J; Keating, Martha; Balshaw, David; Garrahan, Kevin; Burton, Laureen; Batka, Sheila; Limaye, Vijay S; Hakkinen, Pertti J; Thompson, Bob
2017-01-01
The US Environmental Protection Agency (EPA) and other federal agencies face a number of challenges in interpreting and reconciling short-duration (seconds to minutes) readings from mobile and handheld air sensors with the longer duration averages (hours to days) associated with the National Ambient Air Quality Standards (NAAQS) for the criteria pollutants-particulate matter (PM), ozone, carbon monoxide, lead, nitrogen oxides, and sulfur oxides. Similar issues are equally relevant to the hazardous air pollutants (HAPs) where chemical-specific health effect reference values are the best indicators of exposure limits; values which are often based on a lifetime of continuous exposure. A multi-agency, staff-level Air Sensors Health Group (ASHG) was convened in 2013. ASHG represents a multi-institutional collaboration of Federal agencies devoted to discovery and discussion of sensor technologies, interpretation of sensor data, defining the state of sensor-related science across each institution, and provides consultation on how sensors might effectively be used to meet a wide range of research and decision support needs. ASHG focuses on several fronts: improving the understanding of what hand-held sensor technologies may be able to deliver; communicating what hand-held sensor readings can provide to a number of audiences; the challenges of how to integrate data generated by multiple entities using new and unproven technologies; and defining best practices in communicating health-related messages to various audiences. This review summarizes the challenges, successes, and promising tools of those initial ASHG efforts and Federal agency progress on crafting similar products for use with other NAAQS pollutants and the HAPs. NOTE: The opinions expressed are those of the authors and do not necessary represent the opinions of their Federal Agencies or the US Government. Mention of product names does not constitute endorsement.
Research in Action: Collect air quality data to characterize near-road/near-source hotspots; Determine potential impact on nearby residences & roadways; Case study of successful use of such data; Relationship between distance to roadways and industrial sources, exposure to...
Assessment of air quality microsensors versus reference methods: The EuNetAir joint exercise
NASA Astrophysics Data System (ADS)
Borrego, C.; Costa, A. M.; Ginja, J.; Amorim, M.; Coutinho, M.; Karatzas, K.; Sioumis, Th.; Katsifarakis, N.; Konstantinidis, K.; De Vito, S.; Esposito, E.; Smith, P.; André, N.; Gérard, P.; Francis, L. A.; Castell, N.; Schneider, P.; Viana, M.; Minguillón, M. C.; Reimringer, W.; Otjes, R. P.; von Sicard, O.; Pohle, R.; Elen, B.; Suriano, D.; Pfister, V.; Prato, M.; Dipinto, S.; Penza, M.
2016-12-01
The 1st EuNetAir Air Quality Joint Intercomparison Exercise organized in Aveiro (Portugal) from 13th-27th October 2014, focused on the evaluation and assessment of environmental gas, particulate matter (PM) and meteorological microsensors, versus standard air quality reference methods through an experimental urban air quality monitoring campaign. The IDAD-Institute of Environment and Development Air Quality Mobile Laboratory was placed at an urban traffic location in the city centre of Aveiro to conduct continuous measurements with standard equipment and reference analysers for CO, NOx, O3, SO2, PM10, PM2.5, temperature, humidity, wind speed and direction, solar radiation and precipitation. The comparison of the sensor data generated by different microsensor-systems installed side-by-side with reference analysers, contributes to the assessment of the performance and the accuracy of microsensor-systems in a real-world context, and supports their calibration and further development. The overall performance of the sensors in terms of their statistical metrics and measurement profile indicates significant differences in the results depending on the platform and on the sensors considered. In terms of pollutants, some promising results were observed for O3 (r2: 0.12-0.77), CO (r2: 0.53-0.87), and NO2 (r2: 0.02-0.89). For PM (r2: 0.07-0.36) and SO2 (r2: 0.09-0.20) the results show a poor performance with low correlation coefficients between the reference and microsensor measurements. These field observations under specific environmental conditions suggest that the relevant microsensor platforms, if supported by the proper post processing and data modelling tools, have enormous potential for new strategies in air quality control.
Community Air Sensor Network (CAIRSENSE) project ...
Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low cost, continuous and commercially-available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ~2 km area in Southeastern U.S. Co-location of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as whether multiple identical sensors reproduced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in sampling days could be used in a correction algorihm to im
Advancing Sensor Technology to Monitor Wildfires
EPA and partners are looking at ways to use miniature sensors to monitor air quality near wildfires. Data from these small sensors can complement measurements obtained from more complex regulatory-grade monitors that are stationary.
Citizen Science Air Monitoring in the Ironbound Community ...
The Environmental Protection Agency’s (EPA) mission is to protect human health and the environment. To move toward achieving this goal, EPA is facilitating identification of potential environmental concerns, particularly in vulnerable communities. This includes actively supporting citizen science projects and providing communities with the information and assistance they need to conduct their own air pollution monitoring efforts. The Air Sensor Toolbox for Citizen Scientists1 was developed as a resource to meet stakeholder needs. Examples of materials developed for the Toolbox and ultimately pilot tested in the Ironbound Community in Newark, New Jersey are reported here. The Air Sensor Toolbox for Citizen Scientists is designed as an online resource that provides information and guidance on new, low-cost compact technologies used for measuring air quality. The Toolbox features resources developed by EPA researchers that can be used by citizens to effectively collect, analyze, interpret, and communicate air quality data. The resources include information about sampling methods, how to calibrate and validate monitors, options for measuring air quality, data interpretation guidelines, and low-cost sensor performance information. This Regional Applied Research Effort (RARE) project provided an opportunity for the Office of Research and Development (ORD) to work collaboratively with EPA Region 2 to provide the Ironbound Community with a “Toolbox” specific for c
Project GoalDevelop tools Citizen Scientists can use to assist them in conducting environmental monitoringResearch PlanIdentify a citizen science project as a potential pilot study locationEstablish their pollutant monitoring interestsDevelop a sensor package to meet their needs ...
NASA Astrophysics Data System (ADS)
Jiao, Wan; Hagler, Gayle; Williams, Ronald; Sharpe, Robert; Brown, Ryan; Garver, Daniel; Judge, Robert; Caudill, Motria; Rickard, Joshua; Davis, Michael; Weinstock, Lewis; Zimmer-Dauphinee, Susan; Buckley, Ken
2016-11-01
Advances in air pollution sensor technology have enabled the development of small and low-cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low-cost, continuous, and commercially available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ˜ 2 km area in the southeastern United States. Collocation of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as the degree to which multiple identical sensors produced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, and -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r < 0.5) with a reference monitor and erroneously high concentration values. A wide variety of particulate matter (PM) sensors were tested with variable results - some sensors had very high agreement (e.g., r = 0.99) between identical sensors but moderate agreement with a reference PM2.5 monitor (e.g., r = 0.65). For select sensors that had moderate to strong correlation with reference monitors (r > 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in number of sampling days could be used in a correction algorithm to improve the agreement. Maximum improvement in agreement with a reference, incorporating all factors, was observed for an NO2 sensor (multiple correlation coefficient R2adj-orig = 0.57, R2adj-final = 0.81); however, other sensors showed no apparent improvement in agreement. A four-node sensor network was successfully able to capture ozone (two nodes) and PM (four nodes) data for an 8-month period of time and show expected diurnal concentration patterns, as well as potential ozone titration due to nearby traffic emissions. Overall, this study demonstrates the performance of emerging air quality sensor technologies in a real-world setting; the variable agreement between sensors and reference monitors indicates that in situ testing of sensors against benchmark monitors should be a critical aspect of all field studies.
NASA Astrophysics Data System (ADS)
Johnson, Nicholas E.; Bonczak, Bartosz; Kontokosta, Constantine E.
2018-07-01
The increased availability and improved quality of new sensing technologies have catalyzed a growing body of research to evaluate and leverage these tools in order to quantify and describe urban environments. Air quality, in particular, has received greater attention because of the well-established links to serious respiratory illnesses and the unprecedented levels of air pollution in developed and developing countries and cities around the world. Though numerous laboratory and field evaluation studies have begun to explore the use and potential of low-cost air quality monitoring devices, the performance and stability of these tools has not been adequately evaluated in complex urban environments, and further research is needed. In this study, we present the design of a low-cost air quality monitoring platform based on the Shinyei PPD42 aerosol monitor and examine the suitability of the sensor for deployment in a dense heterogeneous urban environment. We assess the sensor's performance during a field calibration campaign from February 7th to March 25th 2017 with a reference instrument in New York City, and present a novel calibration approach using a machine learning method that incorporates publicly available meteorological data in order to improve overall sensor performance. We find that while the PPD42 performs well in relation to the reference instrument using linear regression (R2 = 0.36-0.51), a gradient boosting regression tree model can significantly improve device calibration (R2 = 0.68-0.76). We discuss the sensor's performance and reliability when deployed in a dense, heterogeneous urban environment during a period of significant variation in weather conditions, and important considerations when using machine learning techniques to improve the performance of low-cost air quality monitors.
NASA Astrophysics Data System (ADS)
Hagan, David H.; Isaacman-VanWertz, Gabriel; Franklin, Jonathan P.; Wallace, Lisa M. M.; Kocar, Benjamin D.; Heald, Colette L.; Kroll, Jesse H.
2018-01-01
The use of low-cost air quality sensors for air pollution research has outpaced our understanding of their capabilities and limitations under real-world conditions, and there is thus a critical need for understanding and optimizing the performance of such sensors in the field. Here we describe the deployment, calibration, and evaluation of electrochemical sensors on the island of Hawai`i, which is an ideal test bed for characterizing such sensors due to its large and variable sulfur dioxide (SO2) levels and lack of other co-pollutants. Nine custom-built SO2 sensors were co-located with two Hawaii Department of Health Air Quality stations over the course of 5 months, enabling comparison of sensor output with regulatory-grade instruments under a range of realistic environmental conditions. Calibration using a nonparametric algorithm (k nearest neighbors) was found to have excellent performance (RMSE < 7 ppb, MAE < 4 ppb, r2 > 0.997) across a wide dynamic range in SO2 (< 1 ppb, > 2 ppm). However, since nonparametric algorithms generally cannot extrapolate to conditions beyond those outside the training set, we introduce a new hybrid linear-nonparametric algorithm, enabling accurate measurements even when pollutant levels are higher than encountered during calibration. We find no significant change in instrument sensitivity toward SO2 after 18 weeks and demonstrate that calibration accuracy remains high when a sensor is calibrated at one location and then moved to another. The performance of electrochemical SO2 sensors is also strong at lower SO2 mixing ratios (< 25 ppb), for which they exhibit an error of less than 2.5 ppb. While some specific results of this study (calibration accuracy, performance of the various algorithms, etc.) may differ for measurements of other pollutant species in other areas (e.g., polluted urban regions), the calibration and validation approaches described here should be widely applicable to a range of pollutants, sensors, and environments.
Isopropyl Alcohol Volatile Sensor Development for In-Flight Air Quality
Breathing air quality within commercial airline cabins has come under increased scrutiny due to the identification of volatile organic compounds from...cleaning solvents for breathing lines and life support gear used in the aerospace community , as a target analyte.
NASA Astrophysics Data System (ADS)
Hromadka, J.; Korposh, S.; Partridge, M. C.; James, S.; Davis, F.; Crump, D.; Lee, S.-W.; Tatam, R. P.
2017-04-01
An array of three long period gratings (LPGs) fabricated in a single optical fibre and multiplexed in the wavelength domain was used to measure simultaneously temperature, relative humidity (RH) and volatile organic compounds (VOCs). Each LPG sensor was designed to optimize its response to a desired measurand. The LPGs were fabricated with periods such that they operated at or near the phase matching turning point. The sensors were calibrated in the laboratory and the simultaneous measurement of the key indoor air quality parameters was undertaken in laboratory and office environments. It was demonstrated successfully that the data produced by the LPG sensor array under real conditions was in a good agreement with that produced by commercially available sensors. Further, the potential application of fibre optic sensors for VOCs detection at high levels has been demonstrated.
Test Structures for Rapid Prototyping of Gas and Pressure Sensors
NASA Technical Reports Server (NTRS)
Buehler, M.; Cheng, L. J.; Martin, D.
1996-01-01
A multi-project ceramic substrate was used in developing a gas sensor and pressure sensor. The ceramic substrate cantained 36 chips with six variants including sensors, process control monitors, and an interconnect ship. Tha gas sensor is being developed as an air quality monitor and the pressure gauge as a barometer.
Sensor Technology and Performance Characteristics
The US EPA is currently involved in detailed laboratory and/or field studies involving a wide variety of low cost air quality sensors currently being made available to potential citizen scientists. These devices include sensors associated with the monitoring of nitrogen dioxide (...
Mobile Sensors Environmental Assessment
2005-09-26
4-1 4.1 Impacts of Land-Based Sensors.........................................................................4-1 4.1.1 Air Quality...4-27 4.3 Impacts of the Proposed Action...4-38 4.6 Cumulative Impacts
Jo, ByungWan
2018-01-01
The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH4, CO, SO2, and H2S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R2 and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality. PMID:29561777
Jo, ByungWan; Khan, Rana Muhammad Asad
2018-03-21
The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH₄, CO, SO₂, and H₂S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R ² and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality.
Method, system and apparatus for monitoring and adjusting the quality of indoor air
Hartenstein, Steven D.; Tremblay, Paul L.; Fryer, Michael O.; Hohorst, Frederick A.
2004-03-23
A system, method and apparatus is provided for monitoring and adjusting the quality of indoor air. A sensor array senses an air sample from the indoor air and analyzes the air sample to obtain signatures representative of contaminants in the air sample. When the level or type of contaminant poses a threat or hazard to the occupants, the present invention takes corrective actions which may include introducing additional fresh air. The corrective actions taken are intended to promote overall health of personnel, prevent personnel from being overexposed to hazardous contaminants and minimize the cost of operating the HVAC system. The identification of the contaminants is performed by comparing the signatures provided by the sensor array with a database of known signatures. Upon identification, the system takes corrective actions based on the level of contaminant present. The present invention is capable of learning the identity of previously unknown contaminants, which increases its ability to identify contaminants in the future. Indoor air quality is assured by monitoring the contaminants not only in the indoor air, but also in the outdoor air and the air which is to be recirculated. The present invention is easily adaptable to new and existing HVAC systems. In sum, the present invention is able to monitor and adjust the quality of indoor air in real time by sensing the level and type of contaminants present in indoor air, outdoor and recirculated air, providing an intelligent decision about the quality of the air, and minimizing the cost of operating an HVAC system.
Woodall, George M.; Hoover, Mark D.; Williams, Ronald; Benedict, Kristen; Harper, Martin; Soo, Jhy-Charm; Jarabek, Annie M.; Stewart, Michael J.; Brown, James S.; Hulla, Janis E.; Caudill, Motria; Clements, Andrea L.; Kaufman, Amanda; Parker, Alison J.; Keating, Martha; Balshaw, David; Garrahan, Kevin; Burton, Laureen; Batka, Sheila; Limaye, Vijay S.; Hakkinen, Pertti J.; Thompson, Bob
2017-01-01
The US Environmental Protection Agency (EPA) and other federal agencies face a number of challenges in interpreting and reconciling short-duration (seconds to minutes) readings from mobile and handheld air sensors with the longer duration averages (hours to days) associated with the National Ambient Air Quality Standards (NAAQS) for the criteria pollutants-particulate matter (PM), ozone, carbon monoxide, lead, nitrogen oxides, and sulfur oxides. Similar issues are equally relevant to the hazardous air pollutants (HAPs) where chemical-specific health effect reference values are the best indicators of exposure limits; values which are often based on a lifetime of continuous exposure. A multi-agency, staff-level Air Sensors Health Group (ASHG) was convened in 2013. ASHG represents a multi-institutional collaboration of Federal agencies devoted to discovery and discussion of sensor technologies, interpretation of sensor data, defining the state of sensor-related science across each institution, and provides consultation on how sensors might effectively be used to meet a wide range of research and decision support needs. ASHG focuses on several fronts: improving the understanding of what hand-held sensor technologies may be able to deliver; communicating what hand-held sensor readings can provide to a number of audiences; the challenges of how to integrate data generated by multiple entities using new and unproven technologies; and defining best practices in communicating health-related messages to various audiences. This review summarizes the challenges, successes, and promising tools of those initial ASHG efforts and Federal agency progress on crafting similar products for use with other NAAQS pollutants and the HAPs. NOTE: The opinions expressed are those of the authors and do not necessary represent the opinions of their Federal Agencies or the US Government. Mention of product names does not constitute endorsement. PMID:29093969
Plug-and-play web-based visualization of mobile air monitoring data
The collection of air measurements in real-time on moving platforms, such as wearable, bicycle-mounted, or vehicle-mounted air sensors, is becoming an increasingly common method to investigate local air quality. However, visualizing and analyzing geospatial air monitoring data r...
NASA Astrophysics Data System (ADS)
Casey, J. G.; Hannigan, M.; Collier, A. M.; Coffey, E.; Piedrahita, R.
2016-12-01
Affordable, small, portable, quiet tools to measure atmospheric trace gases and air quality enable novel experimental design and new findings. Members of the Hannigan Lab at the University of Colorado in Boulder have been working over the last few years to integrate emerging affordable gas sensors into such an air quality monitor. Presented here are carbon monoxide (CO) and carbon dioxide (CO2) measurements from two field experiments that utilized these tools. In the first experiment, ten air quality monitors were located northeast of Boulder throughout the Denver Julesburg oil and gas basin. The Colorado Department of Health and Environment has several air quality monitoring sites in this broader region, each in an Urban center. One goal of the experiment was to determine whether or not significant spatial variability of EPA criteria pollutants like CO, exists on a sub-regulatory monitoring grid scale. Another goal of the experiment was to compare rural sampling locations with urban sites. The monitors collected continuous data (sampling every 15 seconds) at each location over the course of several months. Our sensor calibration procedures are presented along with our observations and an analysis of the spatial and temporal variability in CO and CO2. In the second experiment, we used eight of our air quality monitors to better understand how home heating fuel type can impact indoor air quality in two communities on the Navajo Nation. We sought to compare air quality in homes using one of four different fuels for heat (wood, wood plus coal, pellet, and gas). There are many factors that contribute to indoor air quality and the impact of an emission source, like a woodstove, within a home. Having multiple, easily deployable, air quality monitors allowed us to account for many of these factors. We sampled four homes at a time, aiming for one home from each of our fuel groups in each sampling period. We sampled inside and outside of each home for a period of 3-4 days. In this way, we hoped to account for possible weather and outdoor air quality biases. CO and CO2 were measured and are put into context with acceptable levels. During periods when there were no emissions of CO and CO2, we used their rates of decay to calculate the home's air exchange rate via the tracer gas technique. The air exchange rate was then used to calculate emission rates for CO.
A state of the art regarding urban air quality prediction models
NASA Astrophysics Data System (ADS)
Croitoru, Cristiana; Nastase, Ilinca
2018-02-01
Urban pollution represents an increasing risk to residents of urban regions, particularly in large, over-industrialized cities knowing that the traffic is responsible for more than 25% of air gaseous pollutants and dust particles. Air quality modelling plays an important role in addressing air pollution control and management approaches by providing guidelines for better and more efficient air quality forecasting, along with smart monitoring sensor networks. The advances in technology regarding simulations, forecasting and monitoring are part of the new smart cities which offers a healthy environment for their occupants.
NASA Astrophysics Data System (ADS)
Vucnik, Matevz; Robinson, Johanna; Smolnikar, Miha; Kocman, David; Horvat, Milena; Mohorcic, Mihael
2015-04-01
Key words: portable air quality sensor, CITI-SENSE, participatory monitoring, VESNA-AQ The emergence of low-cost easy to use portable air quality sensors units is opening new possibilities for individuals to assess their exposure to air pollutants at specific place and time, and share this information through the Internet connection. Such portable sensors units are being used in an ongoing citizen science project called CITI-SENSE, which enables citizens to measure and share the data. The project aims through creating citizens observatories' to empower citizens to contribute to and participate in environmental governance, enabling them to support and influence community and societal priorities as well as associated decision making. An air quality measurement system based on VESNA sensor platform was primarily designed within the project for the use as portable sensor unit in selected pilot cities (Belgrade, Ljubljana and Vienna) for monitoring outdoor exposure to pollutants. However, functionally the same unit with different set of sensors could be used for example as an indoor platform. The version designed for the pilot studies was equipped with the following sensors: NO2, O3, CO, temperature, relative humidity, pressure and accelerometer. The personal sensor unit is battery powered and housed in a plastic box. The VESNA-based air quality (AQ) monitoring system comprises the VESNA-AQ portable sensor unit, a smartphone app and the remote server. Personal sensor unit supports wireless connection to an Android smartphone via built-in Wi-Fi. The smartphone in turn serves also as the communication gateway towards the remote server using any of available data connections. Besides the gateway functionality the role of smartphone is to enrich data coming from the personal sensor unit with the GPS location, timestamps and user defined context. This, together with an accelerometer, enables the user to better estimate ones exposure in relation to physical activities, time and location. The end user can monitor the measured parameters through a smartphone application. The smartphone app implements a custom developed LCSP (Lightweight Client Server Protocol) protocol which is used to send requests to the VESNA-AQ unit and to exchange information. When the data is obtained from the VESNA-AQ unit, the mobile application visualizes the data. It also has an option to forward the data to the remote server in a custom JSON structure over a HTTP POST request. The server stores the data in the database and in parallel translates the data to WFS and forwards it to the main CITI-SENSE platform over WFS-T in a common XML format over HTTP POST request. From there data can be accessed through the Internet and visualised in different forms and web applications developed by the CITI-SENSE project. In the course of the project, the collected data will be made publicly available enabling the citizens to participate in environmental governance. Acknowledgements: CITI-SENSE is a Collaborative Project partly funded by the EU FP7-ENV-2012 under grant agreement no 308524 (www.citi-sense.eu).
A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems
Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling
2015-01-01
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. PMID:26703598
A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems.
Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling
2015-12-12
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.
Sensor-Based Optimization Model for Air Quality Improvement in Home IoT
Kim, Jonghyuk
2018-01-01
We introduce current home Internet of Things (IoT) technology and present research on its various forms and applications in real life. In addition, we describe IoT marketing strategies as well as specific modeling techniques for improving air quality, a key home IoT service. To this end, we summarize the latest research on sensor-based home IoT, studies on indoor air quality, and technical studies on random data generation. In addition, we develop an air quality improvement model that can be readily applied to the market by acquiring initial analytical data and building infrastructures using spectrum/density analysis and the natural cubic spline method. Accordingly, we generate related data based on user behavioral values. We integrate the logic into the existing home IoT system to enable users to easily access the system through the Web or mobile applications. We expect that the present introduction of a practical marketing application method will contribute to enhancing the expansion of the home IoT market. PMID:29570684
Sensor-Based Optimization Model for Air Quality Improvement in Home IoT.
Kim, Jonghyuk; Hwangbo, Hyunwoo
2018-03-23
We introduce current home Internet of Things (IoT) technology and present research on its various forms and applications in real life. In addition, we describe IoT marketing strategies as well as specific modeling techniques for improving air quality, a key home IoT service. To this end, we summarize the latest research on sensor-based home IoT, studies on indoor air quality, and technical studies on random data generation. In addition, we develop an air quality improvement model that can be readily applied to the market by acquiring initial analytical data and building infrastructures using spectrum/density analysis and the natural cubic spline method. Accordingly, we generate related data based on user behavioral values. We integrate the logic into the existing home IoT system to enable users to easily access the system through the Web or mobile applications. We expect that the present introduction of a practical marketing application method will contribute to enhancing the expansion of the home IoT market.
NASA Astrophysics Data System (ADS)
Castell, Nuria; Liu, Hai-Ying; Schneider, Philipp; Cole-Hunter, Tom; Lahoz, William; Bartonova, Alena
2015-04-01
Most European cities exceed the air quality guidelines established by the WHO to protect human health. As such, citizens are exposed to potentially harmful pollutant levels. Some cities have services (e.g., web pages, mobile apps, etc.) which provide timely air quality information to the public. However, air quality data at individual level is currently scarce or non-existent. Making this information directly useful to individuals poses a challenge. For instance, if a user is informed that the air quality is "poor", what does that mean for him/her, and how can this information be acted upon? Despite individuals having a unique relationship with their environment, the information on the state of atmospheric components and related hazards is currently mostly generic, and seldom personally relevant. This undermines citizens' interest in their environment, and consequently limits their ability to recognize and change both their contribution and their exposure to air pollution. In Oslo, two EU founded projects, CITI-SENSE (Engelken-Jorge et al., 2014) and Citi-Sense-MOB (Castell et al., 2014), are trying to establish a dialogue with citizens by providing them with the possibility of getting personalized air quality information on their smartphones. The users are able to check the air quality in their immediate surroundings and track their individual exposure while moving through the urban environment (Castell et al., 2014). In this way, they may be able to reduce their exposure such as by changing transport modes or routes, for example by selecting less polluted streets to walk or cycle through. Using a smartphone application, citizens are engaged in collecting and sharing environmental data generated by low-cost air quality sensors, and in reporting their individual perception (turning citizens into sensors themselves). The highly spatially resolved data on air quality and perception is geo-located. This allows for simultaneous visualization of both kinds of the sensor information on a map. These field experiences will allow us to evaluate the ability of crowdsourcing and low-cost sensor technologies to enhance existing air quality monitoring systems. They will also test to what extent this approach enables citizens to engage in more active environmental monitoring. Challenges include precision and accuracy of the measurements, scientific understanding of these novel data and provision of added value for the participants (Liu et al., 2014). References: Castell et al. 2014. Mobile technologies and services for environmental monitoring: The Citi-Sense-MOB approach. Urban Climate. http://dx.doi.org/10.1016/j.uclim.2014.08.002 Engelken-Jorge M, Moreno J, Keune H, Verheyden W, Bartonova A, CITI-SENSE Consortium. 2014. Developing citizens' observatories for environmental monitoring and citizen empowerment: challenges and future scenarios. In Proceedings of the Conference for EDemocracy and Open Governement (CeDEM14): 21-23 May 2014; Danube University Krems, Austria. Edited by Parycek P, Edelmann N. 2014:49-60. Liu H.-Y., Kobernus M., Broday D., Bartonova A. 2014. A conceptual approach to a citizens' observatory - supporting community-based environmental governance. Environmental Health. 13:107. doi:10.1186/1476-069X-13-107.
A new sensor system for mobile and aerial emission sampling was developed for open area pollutant sources, such as prescribed forest burns. The sensor system, termed “Kolibri”, consists of multiple low-cost air quality sensors measuring CO2, CO, samplers for particulate matter wi...
A new sensor system for mobile and aerial emission sampling was developed for open area pollutant sources, such as prescribed forest burns. The sensor system, termed “Kolibri”, consists of multiple low-cost air quality sensors measuring CO2, CO, samplers for particulate matter wi...
A new sensor system for mobile and aerial emission sampling was developed for open area sources, such as open burning. The sensor system, termed “Kolibri”, consists of multiple low-cost air quality sensors measuring CO2, CO, and black carbon, samplers for particulate matter with ...
A Prototype Sensor for In Situ Sensing of Fine Particulate Matter and Volatile Organic Compounds
Ng, Chee-Loon; Kai, Fuu-Ming; Tee, Ming-Hui; Tan, Nicholas; Hemond, Harold F.
2018-01-01
Air pollution exposure causes seven million deaths per year, according to the World Health Organization. Possessing knowledge of air quality and sources of air pollution is crucial for managing air pollution and providing early warning so that a swift counteractive response can be carried out. An optical prototype sensor (AtmOptic) capable of scattering and absorbance measurements has been developed to target in situ sensing of fine particulate matter (PM2.5) and volatile organic compounds (VOCs). For particulate matter testing, a test chamber was constructed and the emission of PM2.5 from incense burning inside the chamber was measured using the AtmOptic. The weight of PM2.5 particles was collected and measured with a filter to determine their concentration and the sensor signal-to-concentration correlation. The results of the AtmOptic were also compared and found to trend well with the Dylos DC 1100 Pro air quality monitor. The absorbance spectrum of VOCs emitted from various laboratory chemicals and household products as well as a two chemical mixtures were recorded. The quantification was demonstrated, using toluene as an example, by calibrating the AtmOptic with compressed gas standards containing VOCs at different concentrations. The results demonstrated the sensor capabilities in measuring PM2.5 and volatile organic compounds. PMID:29346281
A Prototype Sensor for In Situ Sensing of Fine Particulate Matter and Volatile Organic Compounds.
Ng, Chee-Loon; Kai, Fuu-Ming; Tee, Ming-Hui; Tan, Nicholas; Hemond, Harold F
2018-01-18
Air pollution exposure causes seven million deaths per year, according to the World Health Organization. Possessing knowledge of air quality and sources of air pollution is crucial for managing air pollution and providing early warning so that a swift counteractive response can be carried out. An optical prototype sensor (AtmOptic) capable of scattering and absorbance measurements has been developed to target in situ sensing of fine particulate matter (PM2.5) and volatile organic compounds (VOCs). For particulate matter testing, a test chamber was constructed and the emission of PM2.5 from incense burning inside the chamber was measured using the AtmOptic. The weight of PM2.5 particles was collected and measured with a filter to determine their concentration and the sensor signal-to-concentration correlation. The results of the AtmOptic were also compared and found to trend well with the Dylos DC 1100 Pro air quality monitor. The absorbance spectrum of VOCs emitted from various laboratory chemicals and household products as well as a two chemical mixtures were recorded. The quantification was demonstrated, using toluene as an example, by calibrating the AtmOptic with compressed gas standards containing VOCs at different concentrations. The results demonstrated the sensor capabilities in measuring PM2.5 and volatile organic compounds.
Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary)
In May 2017, a two-day workshop was held in Los Angeles (California, U.S.A.) to gather practitioners who work with low-cost sensors used to make air quality measurements. The community of practice included individuals from academia, industry, non-profit groups, community-based or...
Villa, Tommaso Francesco; Gonzalez, Felipe; Miljievic, Branka; Ristovski, Zoran D.; Morawska, Lidia
2016-01-01
Assessment of air quality has been traditionally conducted by ground based monitoring, and more recently by manned aircrafts and satellites. However, performing fast, comprehensive data collection near pollution sources is not always feasible due to the complexity of sites, moving sources or physical barriers. Small Unmanned Aerial Vehicles (UAVs) equipped with different sensors have been introduced for in-situ air quality monitoring, as they can offer new approaches and research opportunities in air pollution and emission monitoring, as well as for studying atmospheric trends, such as climate change, while ensuring urban and industrial air safety. The aims of this review were to: (1) compile information on the use of UAVs for air quality studies; and (2) assess their benefits and range of applications. An extensive literature review was conducted using three bibliographic databases (Scopus, Web of Knowledge, Google Scholar) and a total of 60 papers was found. This relatively small number of papers implies that the field is still in its early stages of development. We concluded that, while the potential of UAVs for air quality research has been established, several challenges still need to be addressed, including: the flight endurance, payload capacity, sensor dimensions/accuracy, and sensitivity. However, the challenges are not simply technological, in fact, policy and regulations, which differ between countries, represent the greatest challenge to facilitating the wider use of UAVs in atmospheric research. PMID:27420065
Casey, Joanna Gordon; Ortega, John; Coffey, Evan; Hannigan, Michael
2018-06-01
A large fraction of the global population relies on the inefficient combustion of solid fuels for cooking and home heating, resulting in household exposure to combustion byproducts. In the southwestern United States, unhealthy air quality has been observed in some homes that use solid fuels as a primary source of heat on the Navajo Nation. In order to better understand how home heating fuel choice can influence indoor air quality in this region, we used recently developed low-cost electrochemical sensors to measure carbon monoxide (CO) air mole fractions continuously inside and outside 41 homes in two communities on the Navajo Nation. Using low-cost sensors in this study, which don't require extensive training to operate, enabled collaboration with local Diné College students and faculty in the planning and implementation of home deployments. Households used natural gas, propane, pellets, wood, and/or coal for heating. We developed quantification methods that included uncertainty estimation for Alphasense CO-B4 sensors, for measurements both inside and outside homes. CO concentrations elevated above background were observed in homes in each heating fuel group, but the highest hourly concentrations were observed in wood and coal burning homes, some of which exceeded World Health Organization Guidelines on both an hourly and eight-hourly basis. In order to probe the many factors that can influence indoor pollutant concentrations, we developed and implemented methods that employ CO emission and decay time periods observed in homes during everyday activities to estimate air exchange rates as well as CO emission rates on the basis of a given well-mixed volume of air. The air quality measurement tools and methods demonstrated in this study can be readily extended to indoor air quality studies in other communities around the world to inform how home heating and cooking practices are influencing indoor air quality during normal daily activities. Copyright © 2018 Elsevier B.V. All rights reserved.
EPA scientists are partnering with Clean Air Carolina (CAC) in Charlotte, N.C., and the Eastern Band of Cherokee Indians (EBCI) in Cherokee, N.C., to conduct a citizen science air quality project in these regions.
Evaluating the performance of low cost chemical sensors for air pollution research.
Lewis, Alastair C; Lee, James D; Edwards, Peter M; Shaw, Marvin D; Evans, Mat J; Moller, Sarah J; Smith, Katie R; Buckley, Jack W; Ellis, Matthew; Gillot, Stefan R; White, Andrew
2016-07-18
Low cost pollution sensors have been widely publicized, in principle offering increased information on the distribution of air pollution and a democratization of air quality measurements to amateur users. We report a laboratory study of commonly-used electrochemical sensors and quantify a number of cross-interferences with other atmospheric chemicals, some of which become significant at typical suburban air pollution concentrations. We highlight that artefact signals from co-sampled pollutants such as CO2 can be greater than the electrochemical sensor signal generated by the measurand. We subsequently tested in ambient air, over a period of three weeks, twenty identical commercial sensor packages alongside standard measurements and report on the degree of agreement between references and sensors. We then explore potential experimental approaches to improve sensor performance, enhancing outputs from qualitative to quantitative, focusing on low cost VOC photoionization sensors. Careful signal handling, for example, was seen to improve limits of detection by one order of magnitude. The quantity, magnitude and complexity of analytical interferences that must be characterised to convert a signal into a quantitative observation, with known uncertainties, make standard individual parameter regression inappropriate. We show that one potential solution to this problem is the application of supervised machine learning approaches such as boosted regression trees and Gaussian processes emulation.
CAIRSENSE Study: Real-world evaluation of low cost sensors ...
Low-cost air pollution sensors are a rapidly developing field in air monitoring. In recent years, numerous sensors have been developed that can provide real-time concentration data for different air pollutants at costs accessible to individuals and non-regulatory groups. Additionally, these sensors have the potential to improve the spatial resolution of monitoring networks and provide a better understanding of neighborhood- and local-scale air quality and sources. However, many new sensors have not been evaluated to determine their long-term performance and capabilities. In this study, nine different low-cost sensor models, including O3, NO2 and particle sensors, were deployed in Denver, CO from September 2015 to February 2016. Three sensors of each type were deployed to evaluate instrument precision and consistency over the time period. Sensors were co-located with reference monitors at the Denver NCore site in order to evaluate sensor accuracy and precision. Denver was chosen as the location for this study to evaluate sensor performance in dry, high altitude, and low winter temperatures. Sensors were evaluated for data completeness, performance over time, and comparison with regulatory monitors. This presentation will also address challenges and approaches to data logging and processing. Preliminary analysis revealed that most sensors had high data completeness when data loggers were operational (e.g., the Aeroqual O3 sensor ranged from 94-100%), and exhibited
Mobile Sensors and Applications for Air Pollutants
Executive Summary The public has long been interested in understanding what pollutants are in the air they breathe so they can best protect their environmental health and welfare. The current air quality monitoring network consists of discrete stations with expensive equipment ...
Node-to-node field calibration of wireless distributed air pollution sensor network.
Kizel, Fadi; Etzion, Yael; Shafran-Nathan, Rakefet; Levy, Ilan; Fishbain, Barak; Bartonova, Alena; Broday, David M
2018-02-01
Low-cost air quality sensors offer high-resolution spatiotemporal measurements that can be used for air resources management and exposure estimation. Yet, such sensors require frequent calibration to provide reliable data, since even after a laboratory calibration they might not report correct values when they are deployed in the field, due to interference with other pollutants, as a result of sensitivity to environmental conditions and due to sensor aging and drift. Field calibration has been suggested as a means for overcoming these limitations, with the common strategy involving periodical collocations of the sensors at an air quality monitoring station. However, the cost and complexity involved in relocating numerous sensor nodes back and forth, and the loss of data during the repeated calibration periods make this strategy inefficient. This work examines an alternative approach, a node-to-node (N2N) calibration, where only one sensor in each chain is directly calibrated against the reference measurements and the rest of the sensors are calibrated sequentially one against the other while they are deployed and collocated in pairs. The calibration can be performed multiple times as a routine procedure. This procedure minimizes the total number of sensor relocations, and enables calibration while simultaneously collecting data at the deployment sites. We studied N2N chain calibration and the propagation of the calibration error analytically, computationally and experimentally. The in-situ N2N calibration is shown to be generic and applicable for different pollutants, sensing technologies, sensor platforms, chain lengths, and sensor order within the chain. In particular, we show that chain calibration of three nodes, each calibrated for a week, propagate calibration errors that are similar to those found in direct field calibration. Hence, N2N calibration is shown to be suitable for calibration of distributed sensor networks. Copyright © 2017 Elsevier Ltd. All rights reserved.
Final report on the portable weather station.
DOT National Transportation Integrated Search
2010-03-01
This station was required to have air temperature, relative humidity, wind speed and direction, and : pavement temperature sensors of similar quality to the traditional RWIS sensors, have an integrated solar : powered battery system, and be trailer...
Leccardi, Matteo; Decarli, Massimiliano; Lorenzelli, Leandro; Milani, Paolo; Mettala, Petteri; Orava, Risto; Barborini, Emanuele
2012-01-01
We have fabricated and tested in long-term field operating conditions a wireless unit for outdoor air quality monitoring. The unit is equipped with two multiparametric sensors, one miniaturized thermo-hygrometer, front-end analogical and digital electronics, and an IEEE 802.15.4 based module for wireless data transmission. Micromachined platforms were functionalized with nanoporous metal-oxides to obtain multiparametric sensors, hosting gas-sensitive, anemometric and temperature transducers. Nanoporous metal-oxide layer was directly deposited on gas sensing regions of micromachined platform batches by hard-mask patterned supersonic cluster beam deposition. An outdoor, roadside experiment was arranged in downtown Milan (Italy), where one wireless sensing unit was continuously operated side by side with standard gas chromatographic instrumentation for air quality measurements. By means of a router PC, data from sensing unit and other instrumentation were collected, merged, and sent to a remote data storage server, through an UMTS device. The whole-system robustness as well as sensor dataset characteristics were continuously characterized over a run-time period of 18 months. PMID:22969394
The collection of air measurements in real-time on moving platforms, such as wearable, bicycle-mounted, or vehicle-mounted air sensors, is becoming an increasingly common method to investigate local air quality. However, visualizing and analyzing geospatial air monitoring data re...
NASA Astrophysics Data System (ADS)
Collier-Oxandale, A. M.; Hannigan, M.; Casey, J. G.; Johnston, J.; Coffey, E.; Thorson, J.
2017-12-01
The field of low-cost air quality sensing technologies is growing rapidly through the continual development of new sensors, increased research into sensor performance, and more and more community groups utilizing sensors to investigate local issues. However, as this technology is still in an exploratory phase, there are few `best-practices' available to serve as guidelines for these projects and the standardization of some procedures could benefit the research community as a whole. For example, deployment considerations such as where and how to place a monitor at a given location are often determined by accessibility and safety, power-requirements, and what is an ideal for sampling the target pollutant. Using data from multiple gas-phase sensors, we will examine the importance of siting considerations for low-cost monitoring systems. During a sampling campaign in Los Angeles, a subset of monitors was deployed at one field site to explore the variability in air quality sensor data around a single building. The site is a three story, multi-family housing unit in a primarily residential neighborhood that is near two major roadways and other potential sources of pollution. Five low-cost monitors were co-located prior to and following the field deployment. During the approximately 2.5-month deployment, these monitors were placed at various heights above street level, on different sides of the building, and on the roof. In our analysis, we will examine how monitor placement affects a sensor's ability to detect local verses more regional trends and how this building-scale spatial variability changes over time. Additionally, examining data from VOC sensors (quantified for methane and total non-methane hydrocarbon signals) and O3 sensors will allow us to compare the variability of primary and secondary pollutants. An outcome of this analysis may include guidelines or `best practices' for siting sensors that could aid in ensuring the collection of high quality field data. These may be particularly useful in community-based projects where monitor siting is typically a collaborative process.
Classifying Sources Influencing Indoor Air Quality (IAQ) Using Artificial Neural Network (ANN)
Mad Saad, Shaharil; Melvin Andrew, Allan; Md Shakaff, Ali Yeon; Mohd Saad, Abdul Rahman; Muhamad Yusof @ Kamarudin, Azman; Zakaria, Ammar
2015-01-01
Monitoring indoor air quality (IAQ) is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN—a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC), base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room’s conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity. PMID:26007724
Low-cost, high-density sensor network for urban emission monitoring: BEACO2N
NASA Astrophysics Data System (ADS)
Kim, J.; Shusterman, A.; Lieschke, K.; Newman, C.; Cohen, R. C.
2017-12-01
In urban environments, air quality is spatially and temporally heterogeneous as diverse emission sources create a high degree of variability even at the neighborhood scale. Conventional air quality monitoring relies on continuous measurements with limited spatial resolution or passive sampling with high-density and low temporal resolution. Either approach averages the air quality information over space or time and hinders our attempts to understand emissions, chemistry, and human exposure in the near-field of emission sources. To better capture the true spatio-temporal heterogeneity of urban conditions, we have deployed a low-cost, high-density air quality monitoring network in San Francisco Bay Area distributed at 2km horizontal spacing. The BErkeley Atmospheric CO2 Observation Network (BEACO2N) consists of approximately 50 sensor nodes, measuring CO2, CO, NO, NO2, O3, and aerosol. Here we describe field-based calibration approaches that are consistent with the low-cost strategy of the monitoring network. Observations that allow inference of emission factors and identification of specific local emission sources will also be presented.
Air Sensor Kit Performance Testing and Pollutant Mapping Supports Community Air Monitoring Project
EPA is collaborating on a research project with the South Coast Air Quality Management District in Diamond Bar, Calif. to gain an enhanced understanding of fine particulate matter (PM2.5) and ozone concentrations across the study area.
Predicting Air Quality in Smart Environments
Deleawe, Seun; Kusznir, Jim; Lamb, Brian; Cook, Diane J.
2011-01-01
The pervasive sensing technologies found in smart environments offer unprecedented opportunities for monitoring and assisting the individuals who live and work in these spaces. As aspect of daily life that is often overlooked in maintaining a healthy lifestyle is the air quality of the environment. In this paper we investigate the use of machine learning technologies to predict CO2 levels as an indicator of air quality in smart environments. We introduce techniques for collecting and analyzing sensor information in smart environments and analyze the correlation between resident activities and air quality levels. The effectiveness of our techniques is evaluated using three physical smart environment testbeds. PMID:21617739
NASA Technical Reports Server (NTRS)
Gregory, G. L.; Lee, R. B., III; Mathis, J. J., Jr.
1981-01-01
The Southeastern Virginia Urban Plume Study (SEV-UPS) utilizes remote sensors and satellite platforms to monitor the Earth's environment and resources. SEV-UPS focuses on the application of specific remote sensors to the monitoring and study of specific air quality problems. The 1979 SEV-UPS field program was conducted with specific objectives: (1) to provide correlative data to evaluate the Laser Absorption spectrometer ozone remote sensors; (2) to demonstrate the utility of the sensor for the study of urban ozone problems; (3) to provide additional insights into air quality phenomena occuring in Southeastern Virginia; and (4) to compare measurement results of various in situ measurement platforms. The field program included monitoring from 12 surface stations, 4 aircraft, 2 tethered balloons, 2 radiosonde release sites, and numerous surface meteorological observation sites. The aircraft monitored 03, NO, NOX, Bscat, temperature, and dewpoint temperature.
Sun, Li; Westerdahl, Dane; Ning, Zhi
2017-08-19
Emerging low-cost gas sensor technologies have received increasing attention in recent years for air quality measurements due to their small size and convenient deployment. However, in the diverse applications these sensors face many technological challenges, including sensor drift over long-term deployment that cannot be easily addressed using mathematical correction algorithms or machine learning methods. This study aims to develop a novel approach to auto-correct the drift of commonly used electrochemical nitrogen dioxide (NO₂) sensor with comprehensive evaluation of its application. The impact of environmental factors on the NO₂ electrochemical sensor in low-ppb concentration level measurement was evaluated in laboratory and the temperature and relative humidity correction algorithm was evaluated. An automated zeroing protocol was developed and assessed using a chemical absorbent to remove NO₂ as a means to perform zero correction in varying ambient conditions. The sensor system was operated in three different environments in which data were compared to a reference NO₂ analyzer. The results showed that the zero-calibration protocol effectively corrected the observed drift of the sensor output. This technique offers the ability to enhance the performance of low-cost sensor based systems and these findings suggest extension of the approach to improve data quality from sensors measuring other gaseous pollutants in urban air.
A New Black Carbon Sensor for Dense Air Quality Monitoring Networks
Caubel, Julien J.; Cados, Troy E.; Kirchstetter, Thomas W.
2018-01-01
Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)—a major component of particulate matter pollution associated with adverse human health risks—is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD’s sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval). PMID:29494528
A New Black Carbon Sensor for Dense Air Quality Monitoring Networks.
Caubel, Julien J; Cados, Troy E; Kirchstetter, Thomas W
2018-03-01
Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)-a major component of particulate matter pollution associated with adverse human health risks-is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD's sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval).
Development of wireless sensor network for monitoring indoor air pollutant
NASA Astrophysics Data System (ADS)
Saad, Shaharil Mad; Shakaff, Ali Yeon Md; Saad, Abdul Rahman Mohd; Yusof @ Kamarudin, Azman Muhamad
2015-05-01
The air that we breathe with everyday contains variety of contaminants and particles. Some of these contaminants and particles are hazardous to human health. Most of the people don't realize that the content of air they being exposed to whether it was a good or bad air quality. The air quality whether in indoor or outdoor environment can be influenced by physical factors like dust particles, gaseous pollutants (including carbon dioxide, carbon monoxide and volatile organic compounds) and biological like molds and bacteria growth which largely depend on temperature and humidity condition of a room. These kinds of pollutants can affect human health, physical reaction, comfort or work performance. In this study, a wireless sensor network (WSN) monitoring system for monitor air pollutant in indoor environment was developed. The system was divided into three parts: web-based interface program, sensing module and a base station. The measured data was displayed on the web which is can be accessed by the user. The result shows that the overall measured parameters were meet the acceptable limit, requirement and criteria of indoor air pollution inside the building. The research can be used to improve the indoor air quality level in order to create a comfortable working and healthy environment for the occupants inside the building.
Evaluation of NASA Data Products for RPO Applications
NASA Technical Reports Server (NTRS)
Frisbie, Troy; Knowlton, Kelly; Andrews, Jane
2005-01-01
This presentation summarizes preliminary investigations at SSC by NASA's ASD in Air Quality including decision support tools, partner plans, working groups, and committees. An overview of follow-on short-term and long-term objectives is also provided. A table of potential NASA sensors for use with air quality applications is included, along with specifications for MODIS 04 and 06 products. This presentation was originally given by Rich Piorot of the Vermont Department of Environmental Conservation - Air Quality as part of a round-table discussion during "Exploring Collaborative Opportunities in Air Quality Monitoring, Modelling and Communication Workshop" in Boulder, CO, on March 21-22, 2005; verbal consent for this presentation to be provided to Mr. Piorot was given by the NASA SSC ASD Air Quality Program Manager on March 14, 2005.
WebDMS: A Web-Based Data Management System for Environmental Data
NASA Astrophysics Data System (ADS)
Ekstrand, A. L.; Haderman, M.; Chan, A.; Dye, T.; White, J. E.; Parajon, G.
2015-12-01
DMS is an environmental Data Management System to manage, quality-control (QC), summarize, document chain-of-custody, and disseminate data from networks ranging in size from a few sites to thousands of sites, instruments, and sensors. The server-client desktop version of DMS is used by local and regional air quality agencies (including the Bay Area Air Quality Management District, the South Coast Air Quality Management District, and the California Air Resources Board), the EPA's AirNow Program, and the EPA's AirNow-International (AirNow-I) program, which offers countries the ability to run an AirNow-like system. As AirNow's core data processing engine, DMS ingests, QCs, and stores real-time data from over 30,000 active sensors at over 5,280 air quality and meteorological sites from over 130 air quality agencies across the United States. As part of the AirNow-I program, several instances of DMS are deployed in China, Mexico, and Taiwan. The U.S. Department of State's StateAir Program also uses DMS for five regions in China and plans to expand to other countries in the future. Recent development has begun to migrate DMS from an onsite desktop application to WebDMS, a web-based application designed to take advantage of cloud hosting and computing services to increase scalability and lower costs. WebDMS will continue to provide easy-to-use data analysis tools, such as time-series graphs, scatterplots, and wind- or pollution-rose diagrams, as well as allowing data to be exported to external systems such as the EPA's Air Quality System (AQS). WebDMS will also provide new GIS analysis features and a suite of web services through a RESTful web API. These changes will better meet air agency needs and allow for broader national and international use (for example, by the AirNow-I partners). We will talk about the challenges and advantages of migrating DMS to the web, modernizing the DMS user interface, and making it more cost-effective to enhance and maintain over time.
Measuring NO, NO2, CO2 and O3 with low-cost sensors
NASA Astrophysics Data System (ADS)
Müller, Michael; Graf, Peter; Hüglin, Christoph
2017-04-01
Inexpensive sensors measuring ambient gas concentrations can be integrated in sensor units forming dense sensor networks. The utilized sensors have to be sufficiently accurate as the value of such networks directly depends on the information they provide. Thus, thorough testing of sensors before bringing them into service and the application of effective strategies for performance monitoring and adjustments during service are key elements for operating the low-cost sensors that are currently available on the market. We integrated several types of low-cost sensors into sensor units (Alphasense NO2 B4/B42F/B43F, Alphasense NO B4, SensAir CO2 LP8, Aeroqual O3 SM50), run them in the field next to instruments of air quality monitoring stations and performed tests in the laboratory. The poster summarizes our findings regarding the achieved sensor accuracy, methods to improve sensor performance as well as strategies to monitor the current state of the sensor (drifts, sensitivity) within a sensor network.
Instruction Guide and Macro Analysis Tool for Community-led Air Monitoring
EPA has developed two tools for evaluating the performance of low-cost sensors and interpreting the data they collect to help citizen scientists, communities, and professionals interested in learning about local air quality.
A Modular IoT Platform for Real-Time Indoor Air Quality Monitoring.
Benammar, Mohieddine; Abdaoui, Abderrazak; Ahmad, Sabbir H M; Touati, Farid; Kadri, Abdullah
2018-02-14
The impact of air quality on health and on life comfort is well established. In many societies, vulnerable elderly and young populations spend most of their time indoors. Therefore, indoor air quality monitoring (IAQM) is of great importance to human health. Engineers and researchers are increasingly focusing their efforts on the design of real-time IAQM systems using wireless sensor networks. This paper presents an end-to-end IAQM system enabling measurement of CO₂, CO, SO₂, NO₂, O₃, Cl₂, ambient temperature, and relative humidity. In IAQM systems, remote users usually use a local gateway to connect wireless sensor nodes in a given monitoring site to the external world for ubiquitous access of data. In this work, the role of the gateway in processing collected air quality data and its reliable dissemination to end-users through a web-server is emphasized. A mechanism for the backup and the restoration of the collected data in the case of Internet outage is presented. The system is adapted to an open-source Internet-of-Things (IoT) web-server platform, called Emoncms, for live monitoring and long-term storage of the collected IAQM data. A modular IAQM architecture is adopted, which results in a smart scalable system that allows seamless integration of various sensing technologies, wireless sensor networks (WSNs) and smart mobile standards. The paper gives full hardware and software details of the proposed solution. Sample IAQM results collected in various locations are also presented to demonstrate the abilities of the system.
A Low Cost High Density Sensor Network for Air Quality at London Heathrow Airport
NASA Astrophysics Data System (ADS)
Bright, V.; Mead, M. I.; Popoola, O. A.; Baron, R. P.; Saffell, J.; Stewart, G.; Kaye, P.; Jones, R.
2012-12-01
Atmospheric composition within urban areas has a direct effect on the air quality of an environment in which a large majority of people live and work. Atmospheric pollutants including ozone (O3), nitrogen dioxide (NO2), volatile organic compounds (VOCs) and particulate matter (PM) can have a significant effect on human health. As such it is important to determine the potential exposure of individuals to these atmospheric constituents and investigate the processes that lead to the degradation of air quality within the urban environment. Whilst modelled pollutant levels on the local scale often suggest high degrees of spatial and temporal variability, the relatively sparse fixed site automated urban networks only provide low spatial resolution data that do not appear adequate in detecting such small scale variability. In this paper we demonstrate that measurements can now be made using networks of low-cost sensors that utilise a variety of techniques, including electrochemical and optical, to measure concentrations of atmospheric species. Once equipped with GPS and GPRS to determine position and transmit data respectively, these networks have the potential to provide valuable insights into pollutant variability inherent on the local or micro-scale. The methodology has been demonstrated successfully in field campaigns carried out in cities including London and Valencia, and is now being deployed as part of the Sensor Networks for Air Quality currently deployed at London Heathrow airport (SNAQ-Heathrow) which is outlined in the partner paper presented by Mead et al. (this conference). The SNAQ-Heathrow network of 50 sensor nodes will provide an unprecedented data set that includes measurements of O3, NO, NO2, CO, CO2, SO2, total VOCs, size-speciated PM as well as meteorological variables that include temperature, relative humidity, wind speed and direction. This network will provide high temporal (20 second intervals) and spatial (50 sites within the airport area) resolution data over a 12 month period with data transmitted back to a server every 2 hours. In this paper we present the data capture and storage, data accessibility, data mining and visualisation techniques applied to the measurements of the SNAQ Heathrow high density sensor network, the preliminary results of which provide an insight into the potential use of such networks in characterising air quality, emissions and validating dispersion models on local scales. We also present a web based interface developed for the sensor network that allows users to access archived data and assess meteorological conditions, atmospheric dispersion, pollutant levels and emission rates.
Integrated optics ring-resonator chemical sensor with polymer transduction layer
NASA Technical Reports Server (NTRS)
Ksendzov, A.; Homer, M. L.; Manfreda, A. M.
2004-01-01
An integrated optics chemical sensor based on a ring resonator with an ethyl cellulose polymer coating has been demonstrated. The measured sensitivity to isopropanol in air is 50 ppm-the level immediately useful for health-related air quality monitoring. The resonator was fabricated using SiO2 and SixNy materials. The signal readout is based on tracking the wavelength of a resonance peak. The resonator layout optimisation for sensing applications is discussed.
Moiş, George Dan; Sanislav, Teodora; Folea, Silviu Corneliu; Zeadally, Sherali
2018-05-25
Environmental conditions and air quality monitoring have become crucial today due to the undeniable changes of the climate and accelerated urbanization. To efficiently monitor environmental parameters such as temperature, humidity, and the levels of pollutants, such as fine particulate matter (PM2.5) and volatile organic compounds (VOCs) in the air, and to collect data covering vast geographical areas, the development of cheap energy-autonomous sensors for large scale deployment and fine-grained data acquisition is required. Rapid advances in electronics and communication technologies along with the emergence of paradigms such as Cyber-Physical Systems (CPSs) and the Internet of Things (IoT) have led to the development of low-cost sensor devices that can operate unattended for long periods of time and communicate using wired or wireless connections through the Internet. We investigate the energy efficiency of an environmental monitoring system based on Bluetooth Low Energy (BLE) beacons that operate in the IoT environment. The beacons developed measure the temperature, the relative humidity, the light intensity, and the CO₂ and VOC levels in the air. Based on our analysis we have developed efficient sleep scheduling algorithms that allow the sensor nodes developed to operate autonomously without requiring the replacement of the power supply. The experimental results show that low-power sensors communicating using BLE technology can operate autonomously (from the energy perspective) in applications that monitor the environment or the air quality in indoor or outdoor settings.
Automated Data Quality Assurance using OGC Sensor Web Enablement Frameworks for Marine Observatories
NASA Astrophysics Data System (ADS)
Toma, Daniel; Bghiel, Ikram; del Rio, Joaquin; Hidalgo, Alberto; Carreras, Normandino; Manuel, Antoni
2014-05-01
Over the past years, environmental sensors have continuously improved by becoming smaller, cheaper, and more intelligent. Therefore, many sensor networks are increasingly deployed to monitor our environment. But due to the large number of sensor manufacturers, accompanying protocols and data encoding, automated integration and data quality assurance of diverse sensors in an observing systems is not straightforward, requiring development of data management code and manual tedious configuration. However, over the past few years it has been demonstrated that Open-Geospatial Consortium (OGC) frameworks can enable web services with fully-described sensor systems, including data processing, sensor characteristics and quality control tests and results. So far, the SWE framework does not describe how to integrate sensors on-the-fly with minimal human intervention. The data management software which enables access to sensors, data processing and quality control tests has to be implemented and the results have to be manually mapped to the SWE models. In this contribution, we describe a Sensor Plug & Play infrastructure for the Sensor Web by combining (1) OGC PUCK protocol - a simple standard embedded instrument protocol to store and retrieve directly from the devices the declarative description of sensor characteristics and quality control tests, (2) an automatic mechanism for data processing and quality control tests underlying the Sensor Web - the Sensor Interface Descriptor (SID) concept, as well as (3) a model for the declarative description of sensor which serves as a generic data management mechanism - designed as a profile and extension of OGC SWE's SensorML standard. We implement and evaluate our approach by applying it to the OBSEA Observatory, and can be used to demonstrate the ability to assess data quality for temperature, salinity, air pressure and wind speed and direction observations off the coast of Garraf, in the north-eastern Spain.
NASA Astrophysics Data System (ADS)
Zurawski, A. M.
2016-12-01
The objective of this research is to study how emissions from a fossil fuel power plant compare to emissions from a biomass power plant, and how these results can be used to improve current air-quality regulations. Outdoor air quality transcends national and political boundaries. Air pollution monitoring is essential to maintaining quality of life for humans and ecosystems. Due to anthropogenic disturbances (primarily related to burning of fossil fuels), air- quality management has become a priority on a long list of environmental issues. Quantifying and monitoring the largest emitters of greenhouse gases and toxic pollutants is crucial to the creation and enforcement of appropriate environmental protection regulations. Emissions data were collected from January 2010 to January 2016 from sensors installed close to a biomass power plant, and sensors installed close to a fossil fuel and natural gas power plant, in Humboldt County, California. In Humboldt County, where air quality serves as a baseline of air pollution in the United States, data showed that the "green" biomass power plant emitted higher levels of particulate matter compared to the fossil fuel power plant. Additionally, the biomass power plant showed levels of CO2, NOx, and SO2 emissions that suggest its place as a "green" power source should be reconsidered. Our research suggests that regulations need to be reconsidered given the potential for high pollutant emissions from biomass plants.
Ning, Zhi; Ye, Sheng; Sun, Li; Yang, Fenhuan; Wong, Ka Chun; Westerdahl, Dane; Louie, Peter K. K.
2018-01-01
The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and oxidants (Ox) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO2 and ozone on a newly introduced oxidant sensor. PMID:29360749
Wei, Peng; Ning, Zhi; Ye, Sheng; Sun, Li; Yang, Fenhuan; Wong, Ka Chun; Westerdahl, Dane; Louie, Peter K K
2018-01-23
The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂), and oxidants (O x ) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO₂ and ozone on a newly introduced oxidant sensor.
NASA Astrophysics Data System (ADS)
Fleming, Z.; Monks, P. S.; McKenzie, K.
2014-12-01
The increasing range of low cost air quality sensors entering the market-place or being developed in-house in the last couple of years has led to many possibilities for using these instruments for public outreach activities or citizen science projects. A range of instruments sent out into local schools for the children to interpret and analyse the data and put the air quality in their area into context. A teaching package with tutorials has been developed to bring the data to life and link in with curriculum.The instruments have also been positioned around the city of Leicester in the UK to help understand the spatial variations in air quality and to assess the impact of retro-fitting buses on a busy bus route. The data is easily accessible online on a near real time basis and the various instruments can be compared with others around the country or the world from classrooms around the world.We will give an overview of the instrumentation with a comparison with commercial and cutting edge research instrumentation, the type of activities that were carried out and the public outreach forums where the data can be used.
Faster Array Training and Rapid Analysis for a Sensor Array Intended for an Event Monitor in Air
NASA Technical Reports Server (NTRS)
Homer, Margie L.; Shevade, A. V.; Fonollosa, J.; Huerta, R.
2013-01-01
Environmental monitoring, in particular, air monitoring, is a critical need for human space flight. Both monitoring and life support systems have needs for closed loop process feedback and quality control for environmental factors. Monitoring protects the air environment and water supply for the astronaut crew and different sensors help ensure that the habitat falls within acceptable limits, and that the life support system is functioning properly and efficiently. The longer the flight duration and the farther the destination, the more critical it becomes to have carefully monitored and automated control systems for life support. There is an acknowledged need for an event monitor which samples the air continuously and provides near real-time information on changes in the air. Past experiments with the JPL ENose have demonstrated a lifetime of the sensor array, with the software, of around 18 months. We are working on a sensor array and new algorithms that will incorporate transient sensor responses in the analysis. Preliminary work has already showed more rapid quantification and identification of analytes and the potential for faster training time of the array. We will look at some of the factors that contribute to demonstrating faster training time for the array. Faster training will decrease the integrated sensor exposure to training analytes, which will also help extend sensor lifetime.
The PerkinElmer Elm (formerly the AirBase CanarIT) is a multi-sensor air quality monitoring device that measures particulate matter (PM), total volatile organic compounds (VOCs), nitrogen dioxide (NO2), and several other atmospheric components. PM, VOCs, and NO2
NASA Astrophysics Data System (ADS)
Stanier, C. O.; Dong, C.; Janechek, N. J.; Bryngelson, N.; Schultz, P.; Heimbinder, M.
2017-12-01
As part of the CLE4R air quality education project, the University of Iowa has been working with AirBeam low-cost consumer-grade fine particulate matter (PM2.5) sensors in educational and outreach settings, both in K-12 environments and in informal settings such as science days and technology fairs. Users are attracted to the AirBeam device, in part, because of the easy creation of crowd-sourced maps of air pollution. With over 1000 AirBeam devices in use, extensive measurements are now available at aircasting.org. The AirBeam sensor is a portable, low-cost sensor which measures light scattering due to aerosols as a single bin converting the detected signal to a particle count and uses a calibration fit to estimate particle mass. The AirBeam is able to detect particle sizes of 0.5 - 2.5 µm, concentrations up to 400 µg m-3, and with a time resolution of 1 s. A corresponding Android device is used to visualize, record, and upload measured data to a community website (aircasting.org) that maps the spatial and temporal resolved data. The non-profit vendor's website constructs crowdsourced maps of air quality, environmental, and meteorological variables. As of April 1st, 2017, through the CLE4R project, 109 people had used the AirBeam sensors for educational purposes, for a total of 271 person hours. In the poster, we will explain the outreach that was done, and share best practices for education and outreach using consumer-grade PM sensors. Strengths and needed improvements to the technology for these outreach, education, and classroom uses will also be detailed. Sources of particles that can be artificially generated for educational use, including authentic smoke, spray smoke, and various dust sources will be enumerated. For use in K-12 classrooms, requirements for robust startup, operation, and ease-of-use are high. Mapping of concentrations is a desirable attribute but adds additional sources of failure to the hardware-software system used for education/outreach.
Mukherjee, Anondo; Stanton, Levi G; Graham, Ashley R; Roberts, Paul T
2017-08-05
The use of low-cost air quality sensors has proliferated among non-profits and citizen scientists, due to their portability, affordability, and ease of use. Researchers are examining the sensors for their potential use in a wide range of applications, including the examination of the spatial and temporal variability of particulate matter (PM). However, few studies have quantified the performance (e.g., accuracy, precision, and reliability) of the sensors under real-world conditions. This study examined the performance of two models of PM sensors, the AirBeam and the Alphasense Optical Particle Counter (OPC-N2), over a 12-week period in the Cuyama Valley of California, where PM concentrations are impacted by wind-blown dust events and regional transport. The sensor measurements were compared with observations from two well-characterized instruments: the GRIMM 11-R optical particle counter, and the Met One beta attenuation monitor (BAM). Both sensor models demonstrated a high degree of collocated precision (R² = 0.8-0.99), and a moderate degree of correlation against the reference instruments (R² = 0.6-0.76). Sensor measurements were influenced by the meteorological environment and the aerosol size distribution. Quantifying the performance of sensors in real-world conditions is a requisite step to ensuring that sensors will be used in ways commensurate with their data quality.
Sun, Li; Westerdahl, Dane; Ning, Zhi
2017-01-01
Emerging low-cost gas sensor technologies have received increasing attention in recent years for air quality measurements due to their small size and convenient deployment. However, in the diverse applications these sensors face many technological challenges, including sensor drift over long-term deployment that cannot be easily addressed using mathematical correction algorithms or machine learning methods. This study aims to develop a novel approach to auto-correct the drift of commonly used electrochemical nitrogen dioxide (NO2) sensor with comprehensive evaluation of its application. The impact of environmental factors on the NO2 electrochemical sensor in low-ppb concentration level measurement was evaluated in laboratory and the temperature and relative humidity correction algorithm was evaluated. An automated zeroing protocol was developed and assessed using a chemical absorbent to remove NO2 as a means to perform zero correction in varying ambient conditions. The sensor system was operated in three different environments in which data were compared to a reference NO2 analyzer. The results showed that the zero-calibration protocol effectively corrected the observed drift of the sensor output. This technique offers the ability to enhance the performance of low-cost sensor based systems and these findings suggest extension of the approach to improve data quality from sensors measuring other gaseous pollutants in urban air. PMID:28825633
Roberts, Paul T.
2017-01-01
The use of low-cost air quality sensors has proliferated among non-profits and citizen scientists, due to their portability, affordability, and ease of use. Researchers are examining the sensors for their potential use in a wide range of applications, including the examination of the spatial and temporal variability of particulate matter (PM). However, few studies have quantified the performance (e.g., accuracy, precision, and reliability) of the sensors under real-world conditions. This study examined the performance of two models of PM sensors, the AirBeam and the Alphasense Optical Particle Counter (OPC-N2), over a 12-week period in the Cuyama Valley of California, where PM concentrations are impacted by wind-blown dust events and regional transport. The sensor measurements were compared with observations from two well-characterized instruments: the GRIMM 11-R optical particle counter, and the Met One beta attenuation monitor (BAM). Both sensor models demonstrated a high degree of collocated precision (R2 = 0.8–0.99), and a moderate degree of correlation against the reference instruments (R2 = 0.6–0.76). Sensor measurements were influenced by the meteorological environment and the aerosol size distribution. Quantifying the performance of sensors in real-world conditions is a requisite step to ensuring that sensors will be used in ways commensurate with their data quality. PMID:28783065
Miniaturized Monitors for Assessment of Exposure to Air Pollutants: A Review.
Borghi, Francesca; Spinazzè, Andrea; Rovelli, Sabrina; Campagnolo, Davide; Del Buono, Luca; Cattaneo, Andrea; Cavallo, Domenico M
2017-08-12
Air quality has a huge impact on different aspects of life quality, and for this reason, air quality monitoring is required by national and international regulations. Technical and procedural limitations of traditional fixed-site stations for monitoring or sampling of air pollutants are also well-known. Recently, a different type of miniaturized monitors has been developed. These monitors, due to their characteristics (e.g., low cost, small size, high portability) are becoming increasingly important for individual exposure assessment, especially since this kind of instrument can provide measurements at high spatial and temporal resolution, which is a notable advantage when approaching assessment of exposure to environmental contaminants. The aim of this study is indeed to provide information regarding current knowledge regarding the use of miniaturized air pollutant sensors. A systematic review was performed to identify original articles: a literature search was carried out using an appropriate query for the search of papers across three different databases, and the papers were selected using inclusion/exclusion criteria. The reviewed articles showed that miniaturized sensors are particularly versatile and could be applied in studies with different experimental designs, helping to provide a significant enhancement to exposure assessment, even though studies regarding their performance are still sparse.
NASA Astrophysics Data System (ADS)
Ramadan, A. B. A.
Air pollution is a serious problem in thickly populated and industrialized areas in Egypt, especially in greater Cairo area. Economic growth and industrialization are proceeding at a rapid pace, accompanied by increasing emissions of air polluting sources. Furthermore, though the variety and quantities of polluting sources have increased dramatically, the development of a suitable method for monitoring the pollution causing sources has not followed at the same pace. Environmental impacts of air pollutants have impact on public health, vegetation, material deterioration etc. To prevent or minimize the damage caused by atmospheric pollution, suitable monitoring systems are urgently needed that can rapidly and reliably detect and quantify polluting sources for monitoring by regulating authorities in order to prevent further deterioration of the current pollution levels. Consequently, it is important that the current real-time air quality monitoring system, controlled by the Egyptian Environmental Affairs Agency (EEAA), should be adapted or extended to aid in alleviating this problem. Nanotechnology has been applied to several industrial and domestic fields, for example, applications for gas monitoring systems, gas leak detectors in factories, fire and toxic gas detectors, ventilation control, breath alcohol detectors, and the like. Here we report an application example of studying air quality monitoring based on nanotechnology `solid state gas sensors'. So as to carry out air pollution monitoring over an extensive area, a combination of ground measurements through inexpensive sensors and wireless GIS will be used for this purpose. This portable device, comprising solid state gas sensors integrated to a Personal Digital Assistant (PDA) linked through Bluetooth communication tools and Global Positioning System (GPS), will allow rapid dissemination of information on pollution levels at multiple sites simultaneously.
This report is the result of low cost air quality sensor performance trials conducted in the NERL’s on-site laboratories located in the Research Triangle Park, NC during 2012-2013. Such trials were viewed as highly valuable for all parties following the conclusion of the U.S. E...
Dual resonant frequencies effects on an induction-based oil palm fruit sensor.
Harun, Noor Hasmiza; Misron, Norhisam; Mohd Sidek, Roslina; Aris, Ishak; Wakiwaka, Hiroyuki; Tashiro, Kunihisa
2014-11-19
As the main exporter in the oil palm industry, the need to improve the quality of palm oil has become the main interest among all the palm oil millers in Malaysia. To produce good quality palm oil, it is important for the miller to harvest a good oil palm Fresh Fruit Bunch (FFB). Conventionally, the main reference used by Malaysian harvesters is the manual grading standard published by the Malaysian Palm Oil Board (MPOB). A good oil palm FFB consists of all matured fruitlets, aged between 18 to 21 weeks of antheses (WAA). To expedite the harvesting process, it is crucial to implement an automated detection system for determining the maturity of the oil palm FFB. Various automated detection methods have been proposed by researchers in the field to replace the conventional method. In our preliminary study, a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunch was proposed. The design of the proposed air coil sensor based on the inductive sensor was further investigated mainly in the context of the effect of coil diameter to improve its sensitivity. In this paper, the sensitivity of the inductive sensor was further examined with a dual flat-type shape of air coil. The dual air coils were tested on fifteen samples of fruitlet from two categories, namely ripe and unripe. Samples were tested within 20 Hz to 10 MHz while evaluations on both peaks were done separately before the gap between peaks was analyzed. A comparative analysis was conducted to investigate the improvement in sensitivity of the induction-based oil palm fruit sensor as compared to previous works. Results from the comparative study proved that the inductive sensor using a dual flat-type shape air coil has improved by up to 167%. This provides an indication in the improvement in the coil sensitivity of the palm oil fruit sensor based on the induction concept.
Dual Resonant Frequencies Effects on an Induction-Based Oil Palm Fruit Sensor
Harun, Noor Hasmiza; Misron, Norhisam; Sidek, Roslina Mohd; Aris, Ishak; Wakiwaka, Hiroyuki; Tashiro, Kunihisa
2014-01-01
As the main exporter in the oil palm industry, the need to improve the quality of palm oil has become the main interest among all the palm oil millers in Malaysia. To produce good quality palm oil, it is important for the miller to harvest a good oil palm Fresh Fruit Bunch (FFB). Conventionally, the main reference used by Malaysian harvesters is the manual grading standard published by the Malaysian Palm Oil Board (MPOB). A good oil palm FFB consists of all matured fruitlets, aged between 18 to 21 weeks of antheses (WAA). To expedite the harvesting process, it is crucial to implement an automated detection system for determining the maturity of the oil palm FFB. Various automated detection methods have been proposed by researchers in the field to replace the conventional method. In our preliminary study, a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunch was proposed. The design of the proposed air coil sensor based on the inductive sensor was further investigated mainly in the context of the effect of coil diameter to improve its sensitivity. In this paper, the sensitivity of the inductive sensor was further examined with a dual flat-type shape of air coil. The dual air coils were tested on fifteen samples of fruitlet from two categories, namely ripe and unripe. Samples were tested within 20 Hz to 10 MHz while evaluations on both peaks were done separately before the gap between peaks was analyzed. A comparative analysis was conducted to investigate the improvement in sensitivity of the induction-based oil palm fruit sensor as compared to previous works. Results from the comparative study proved that the inductive sensor using a dual flat-type shape air coil has improved by up to 167%. This provides an indication in the improvement in the coil sensitivity of the palm oil fruit sensor based on the induction concept. PMID:25414970
A Modular IoT Platform for Real-Time Indoor Air Quality Monitoring
Abdaoui, Abderrazak; Ahmad, Sabbir H.M.; Touati, Farid; Kadri, Abdullah
2018-01-01
The impact of air quality on health and on life comfort is well established. In many societies, vulnerable elderly and young populations spend most of their time indoors. Therefore, indoor air quality monitoring (IAQM) is of great importance to human health. Engineers and researchers are increasingly focusing their efforts on the design of real-time IAQM systems using wireless sensor networks. This paper presents an end-to-end IAQM system enabling measurement of CO2, CO, SO2, NO2, O3, Cl2, ambient temperature, and relative humidity. In IAQM systems, remote users usually use a local gateway to connect wireless sensor nodes in a given monitoring site to the external world for ubiquitous access of data. In this work, the role of the gateway in processing collected air quality data and its reliable dissemination to end-users through a web-server is emphasized. A mechanism for the backup and the restoration of the collected data in the case of Internet outage is presented. The system is adapted to an open-source Internet-of-Things (IoT) web-server platform, called Emoncms, for live monitoring and long-term storage of the collected IAQM data. A modular IAQM architecture is adopted, which results in a smart scalable system that allows seamless integration of various sensing technologies, wireless sensor networks (WSNs) and smart mobile standards. The paper gives full hardware and software details of the proposed solution. Sample IAQM results collected in various locations are also presented to demonstrate the abilities of the system. PMID:29443893
The Role of Unmanned Aerial Systems/Sensors in Air Quality Research
The use of unmanned aerial systems (UASs) for a variety of scientific and security purposes has rapidly increased. UASs include aerostats (tethered balloons) and remotely controlled, unmanned aerial vehicles (UAVs) including lighter-than-air vessels, fixed wing airplanes, and he...
Tissue-based standoff biosensors for detecting chemical warfare agents
Greenbaum, Elias; Sanders, Charlene A.
2003-11-18
A tissue-based, deployable, standoff air quality sensor for detecting the presence of at least one chemical or biological warfare agent, includes: a cell containing entrapped photosynthetic tissue, the cell adapted for analyzing photosynthetic activity of the entrapped photosynthetic tissue; means for introducing an air sample into the cell and contacting the air sample with the entrapped photosynthetic tissue; a fluorometer in operable relationship with the cell for measuring photosynthetic activity of the entrapped photosynthetic tissue; and transmitting means for transmitting analytical data generated by the fluorometer relating to the presence of at least one chemical or biological warfare agent in the air sample, the sensor adapted for deployment into a selected area.
USDA-ARS?s Scientific Manuscript database
Electronic nose sensors are designed to detect differences in complex air sample matrices. For example, they have been used in the food industry to monitor process performance and quality control. However, no information is available on the application of sensor arrays to monitor process performanc...
Measuring PM and related air pollutants using low-cost ...
Emerging air quality sensors may play a key role in better characterizing levels of air pollution in a variety of settings There are a wide range of low-cost (< $500 US) sensors on the market, but few have been characterized. If accurate, this new generation of inexpensive sensors can potentially allow larger fleets of monitors to be deployed to better study the spatial and temporal variability of pollutants. The small size and light weight of these sensors also allows for the possibility of wearable or drone applications. Sensor networks will very likely play a key role in future estimates of human health impacts of pollutants, in particular particulate matter (PM), and will allow for the better characterization of pollutant sources and source regions.We will present measurements from an assortment of sensors, costing $20-$700, that have been used to measure air pollution in the US, India, and China with a focus on estimating PM concentrations. Their performance has been evaluated in these very different settings with low concentrations seen in the US (up to approximately 20 ug m-3) and much higher concentrations measured in India and China (up to approximately 300 ug m-3). Based on these studies the optimal concentration ranges of these sensors have been determined. Used in conjunction with data from a carbon dioxide sensor, emissions factors were estimated in some of the locations. In addition temperature and humidity sensors can be used to calculate c
2017-10-26
NASA is working with the Robert Wood Johnson Foundation (RWJF) to sponsor the Earth and Space Air Prize competition for a solution that could improve air quality and health in space and on Earth. This project is a technology innovation challenge to promote the development of robust, durable, inexpensive, efficient, lightweight, and easy-to-use aerosol sensors for space and Earth environments.
Development and Validation of a UAV Based System for Air Pollution Measurements
Villa, Tommaso Francesco; Salimi, Farhad; Morton, Kye; Morawska, Lidia; Gonzalez, Felipe
2016-01-01
Air quality data collection near pollution sources is difficult, particularly when sites are complex, have physical barriers, or are themselves moving. Small Unmanned Aerial Vehicles (UAVs) offer new approaches to air pollution and atmospheric studies. However, there are a number of critical design decisions which need to be made to enable representative data collection, in particular the location of the air sampler or air sensor intake. The aim of this research was to establish the best mounting point for four gas sensors and a Particle Number Concentration (PNC) monitor, onboard a hexacopter, so to develop a UAV system capable of measuring point source emissions. The research included two different tests: (1) evaluate the air flow behavior of a hexacopter, its downwash and upwash effect, by measuring air speed along three axes to determine the location where the sensors should be mounted; (2) evaluate the use of gas sensors for CO2, CO, NO2 and NO, and the PNC monitor (DISCmini) to assess the efficiency and performance of the UAV based system by measuring emissions from a diesel engine. The air speed behavior map produced by test 1 shows the best mounting point for the sensors to be alongside the UAV. This position is less affected by the propeller downwash effect. Test 2 results demonstrated that the UAV propellers cause a dispersion effect shown by the decrease of gas and PN concentration measured in real time. A Linear Regression model was used to estimate how the sensor position, relative to the UAV center, affects pollutant concentration measurements when the propellers are turned on. This research establishes guidelines on how to develop a UAV system to measure point source emissions. Such research should be undertaken before any UAV system is developed for real world data collection. PMID:28009820
Development and Validation of a UAV Based System for Air Pollution Measurements.
Villa, Tommaso Francesco; Salimi, Farhad; Morton, Kye; Morawska, Lidia; Gonzalez, Felipe
2016-12-21
Air quality data collection near pollution sources is difficult, particularly when sites are complex, have physical barriers, or are themselves moving. Small Unmanned Aerial Vehicles (UAVs) offer new approaches to air pollution and atmospheric studies. However, there are a number of critical design decisions which need to be made to enable representative data collection, in particular the location of the air sampler or air sensor intake. The aim of this research was to establish the best mounting point for four gas sensors and a Particle Number Concentration (PNC) monitor, onboard a hexacopter, so to develop a UAV system capable of measuring point source emissions. The research included two different tests: (1) evaluate the air flow behavior of a hexacopter, its downwash and upwash effect, by measuring air speed along three axes to determine the location where the sensors should be mounted; (2) evaluate the use of gas sensors for CO₂, CO, NO₂ and NO, and the PNC monitor (DISCmini) to assess the efficiency and performance of the UAV based system by measuring emissions from a diesel engine. The air speed behavior map produced by test 1 shows the best mounting point for the sensors to be alongside the UAV. This position is less affected by the propeller downwash effect. Test 2 results demonstrated that the UAV propellers cause a dispersion effect shown by the decrease of gas and PN concentration measured in real time. A Linear Regression model was used to estimate how the sensor position, relative to the UAV center, affects pollutant concentration measurements when the propellers are turned on. This research establishes guidelines on how to develop a UAV system to measure point source emissions. Such research should be undertaken before any UAV system is developed for real world data collection.
NASA Astrophysics Data System (ADS)
Orlando, P.; Vo, D.; Giossi, C.; George, L.
2017-12-01
With the world-wide increase in urbanization and the increasing usage of combustion vehicles in urban areas, traffic-related air pollution is a growing health hazard. However, there are limited studies that examine the spatial and temporal impacts of traffic-related pollutants within cities. In particular, there are few studies that look at traffic management and its potential for pollution mitigation. In a previous study we examined roadway pollution and traffic parameters with one roadway station instrumented with standard measurement instruments. With the advent of low-cost air pollution sensors, we have expanded our work by observing multiple sites within a neighborhood to understand spatial and temporal exposures. We have deployed a high-density sensor network around urban arterial corridors in SE Portland, Oregon. This network consisted of ten nodes measuring CO, NO, NO2 and O3, and ten nodes measuring CO, CO2, VOC and PM2.5. The co-location of standard measurement instruments provided insight towards the utility of our low-cost sensor network, as the different nodes varied in cost, and potentially in quality. We have identified near-real-time temporal trends and local-scale spatial patterns during the summer of 2017. Meteorological and traffic data were included to further characterize these patterns, exploring the potential for pollution mitigation.
On the feasibility of measuring urban air pollution by wireless distributed sensor networks.
Moltchanov, Sharon; Levy, Ilan; Etzion, Yael; Lerner, Uri; Broday, David M; Fishbain, Barak
2015-01-01
Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability to capture spatiotemporal concentration variations at an exceptional fine resolution but highlight the need for a frequent in-situ calibration to maintain the consistency of some sensors. Accordingly, a procedure for a field calibration is proposed and shown to improve the system's performance. Overall, our results support the compatibility of wireless distributed sensor networks for measuring urban air pollution at a sub-neighborhood spatial resolution, which suits the requirement for highly spatiotemporal resolved measurements at the breathing-height when assessing exposure to urban air pollution. Copyright © 2014 Elsevier B.V. All rights reserved.
Indoor air quality analysis based on Hadoop
NASA Astrophysics Data System (ADS)
Tuo, Wang; Yunhua, Sun; Song, Tian; Liang, Yu; Weihong, Cui
2014-03-01
The air of the office environment is our research object. The data of temperature, humidity, concentrations of carbon dioxide, carbon monoxide and ammonia are collected peer one to eight seconds by the sensor monitoring system. And all the data are stored in the Hbase database of Hadoop platform. With the help of HBase feature of column-oriented store and versioned (automatically add the time column), the time-series data sets are bulit based on the primary key Row-key and timestamp. The parallel computing programming model MapReduce is used to process millions of data collected by sensors. By analysing the changing trend of parameters' value at different time of the same day and at the same time of various dates, the impact of human factor and other factors on the room microenvironment is achieved according to the liquidity of the office staff. Moreover, the effective way to improve indoor air quality is proposed in the end of this paper.
Automatic Multi-sensor Data Quality Checking and Event Detection for Environmental Sensing
NASA Astrophysics Data System (ADS)
LIU, Q.; Zhang, Y.; Zhao, Y.; Gao, D.; Gallaher, D. W.; Lv, Q.; Shang, L.
2017-12-01
With the advances in sensing technologies, large-scale environmental sensing infrastructures are pervasively deployed to continuously collect data for various research and application fields, such as air quality study and weather condition monitoring. In such infrastructures, many sensor nodes are distributed in a specific area and each individual sensor node is capable of measuring several parameters (e.g., humidity, temperature, and pressure), providing massive data for natural event detection and analysis. However, due to the dynamics of the ambient environment, sensor data can be contaminated by errors or noise. Thus, data quality is still a primary concern for scientists before drawing any reliable scientific conclusions. To help researchers identify potential data quality issues and detect meaningful natural events, this work proposes a novel algorithm to automatically identify and rank anomalous time windows from multiple sensor data streams. More specifically, (1) the algorithm adaptively learns the characteristics of normal evolving time series and (2) models the spatial-temporal relationship among multiple sensor nodes to infer the anomaly likelihood of a time series window for a particular parameter in a sensor node. Case studies using different data sets are presented and the experimental results demonstrate that the proposed algorithm can effectively identify anomalous time windows, which may resulted from data quality issues and natural events.
Principal Component Analysis for Enhancement of Infrared Spectra Monitoring
NASA Astrophysics Data System (ADS)
Haney, Ricky Lance
The issue of air quality within the aircraft cabin is receiving increasing attention from both pilot and flight attendant unions. This is due to exposure events caused by poor air quality that in some cases may have contained toxic oil components due to bleed air that flows from outside the aircraft and then through the engines into the aircraft cabin. Significant short and long-term medical issues for aircraft crew have been attributed to exposure. The need for air quality monitoring is especially evident in the fact that currently within an aircraft there are no sensors to monitor the air quality and potentially harmful gas levels (detect-to-warn sensors), much less systems to monitor and purify the air (detect-to-treat sensors) within the aircraft cabin. The specific purpose of this research is to utilize a mathematical technique called principal component analysis (PCA) in conjunction with principal component regression (PCR) and proportionality constant calculations (PCC) to simplify complex, multi-component infrared (IR) spectra data sets into a reduced data set used for determination of the concentrations of the individual components. Use of PCA can significantly simplify data analysis as well as improve the ability to determine concentrations of individual target species in gas mixtures where significant band overlap occurs in the IR spectrum region. Application of this analytical numerical technique to IR spectrum analysis is important in improving performance of commercial sensors that airlines and aircraft manufacturers could potentially use in an aircraft cabin environment for multi-gas component monitoring. The approach of this research is two-fold, consisting of a PCA application to compare simulation and experimental results with the corresponding PCR and PCC to determine quantitatively the component concentrations within a mixture. The experimental data sets consist of both two and three component systems that could potentially be present as air contaminants in an aircraft cabin. In addition, experimental data sets are analyzed for a hydrogen peroxide (H2O2) aqueous solution mixture to determine H2O2 concentrations at various levels that could be produced during use of a vapor phase hydrogen peroxide (VPHP) decontamination system. After the PCA application to two and three component systems, the analysis technique is further expanded to include the monitoring of potential bleed air contaminants from engine oil combustion. Simulation data sets created from database spectra were utilized to predict gas components and concentrations in unknown engine oil samples at high temperatures as well as time-evolved gases from the heating of engine oils.
A gas sensor array for the simultaneous detection of multiple VOCs.
Zhang, Yumin; Zhao, Jianhong; Du, Tengfei; Zhu, Zhongqi; Zhang, Jin; Liu, Qingju
2017-05-16
Air quality around the globe is declining and public health is seriously threatened by indoor air pollution. Typically, indoor air pollutants are composed of a series of volatile organic compounds (VOCs) that are generally harmful to the human body, especially VOCs with low molecular weights (less than 100 Da). Moreover, in some situations, more than one type of VOC is present; thus, a device that can detect one or more VOCs simultaneously would be most beneficial. Here, we synthesized a sensor array with 4 units to detect 4 VOCs: acetone (unit 1), benzene (unit 2), methanol (unit 3) and formaldehyde (unit 4) simultaneously. All units were simultaneously exposed to 2.5 ppm of all four VOCs. The sensitivity of unit 1 was 14.67 for acetone and less than 2.54 for the other VOCs. The sensitivities of units 2, 3 and 4 to benzene, methanol and formaldehyde were 2 18.64, 20.98 and 17.26, respectively, and less than 4.01 for the other VOCs. These results indicated that the sensor array exhibited good selectivity and could be used for the real-time monitoring of indoor air quality. Thus, this device will be useful in situations requiring the simultaneous detection of multiple VOCs.
Open hardware, low cost, air quality stations for monitoring ozone in coastal area
NASA Astrophysics Data System (ADS)
Lima, Marco; Donzella, Davide; Pintus, Fabio; Fedi, Adriano; Ferrari, Daniele; Massabò, Marco
2014-05-01
Ozone concentrations in urban and coastal area are a great concern for citizens and, consequently regulator. In the last 20 years the Ozone concentration is almost doubled and it has attracted the public attention because of the well know harmful impacts on human health and biosphere in general. Official monitoring networks usually comprise high precision, high accuracy observation stations, usually managed by public administrations and environmental agency; unfortunately due to their high costs of installation and maintenance, the monitoring stations are relatively sparse. This kind of monitoring networks have been recognized to be unsuitable to effectively characterize the high variability of air quality, especially in areas where pollution sources are various and often not static. We present a prototype of a low cost station for air quality monitoring, specifically developed for complementing the official monitoring stations improving the representation of air quality spatial distribution. We focused on a semi-professional product that could guarantee the highest reliability at the lowest possible cost, supported by a consistent infrastructure for data management. We test two type of Ozone sensor electrochemical and metal oxide. This work is integrated in the ACRONET Paradigm ® project: an open-hardware platform strongly oriented on environmental monitoring. All software and hardware sources will be available on the web. Thus, a computer and a small amount of work tools will be sufficient to create new monitoring networks, with the only constraint to share all the data obtained. It will so possible to create a real "sensing community". The prototype is currently able to measure ozone level, temperature and relative humidity, but soon, with the upcoming changes, it will be able also to monitor dust, carbon monoxide and nitrogen dioxide, always through the use of commercial sensors. The sensors are grouped in a compact board that interfaces with a data-logger able to transmit data to a dedicated server through a GPRS module (no ad hoc radio infrastructure needed). Due to the GPRS low latency transmission the data are transmitted in near-real time. The prototype has an independent power supply. The sensors outputs are directly compared with the measurement of the official fixed monitoring stations. We present preliminary tests of a ozone level assessment obtained without laboratory calibration during a first field campaign in Savona (Italy); the preliminary verification and test show reasonable agreement between low cost sensors and fixed monitoring station ozone level trends (low cost sensors detect gas concentration at ppb level). The preliminary results are promising for complementing the fixed official monitoring networks with low-cost sensors.
Robert, Clélia; Michau, Vincent; Fleury, Bruno; Magli, Serge; Vial, Laurent
2012-07-02
Adaptive optics provide real-time compensation for atmospheric turbulence. The correction quality relies on a key element: the wavefront sensor. We have designed an adaptive optics system in the mid-infrared range providing high spatial resolution for ground-to-air applications, integrating a Shack-Hartmann infrared wavefront sensor operating on an extended source. This paper describes and justifies the design of the infrared wavefront sensor, while defining and characterizing the Shack-Hartmann wavefront sensor camera. Performance and illustration of field tests are also reported.
Real-Time Environmental Sensors to Improve Health in the Sensing City
NASA Astrophysics Data System (ADS)
Marek, L.; Campbell, M.; Epton, M.; Storer, M.; Kingham, S.
2016-06-01
The opportunity of an emerging smart city in post-disaster Christchurch has been explored as a way to improve the quality of life of people suffering Chronic Obstructive Pulmonary Disease (COPD), which is a progressive disease that affects respiratory function. It affects 1 in 15 New Zealanders and is the 4th largest cause of death, with significant costs to the health system. While, cigarette smoking is the leading cause of COPD, long-term exposure to other lung irritants, such as air pollution, chemical fumes, or dust can also cause and exacerbate it. Currently, we do know little what happens to the patients with COPD after they leave a doctor's care. By learning more about patients' movements in space and time, we can better understand the impacts of both the environment and personal mobility on the disease. This research is studying patients with COPD by using GPS-enabled smartphones, combined with the data about their spatiotemporal movements and information about their actual usage of medication in near real-time. We measure environmental data in the city, including air pollution, humidity and temperature and how this may subsequently be associated with COPD symptoms. In addition to the existing air quality monitoring network, to improve the spatial scale of our analysis, we deployed a series of low-cost Internet of Things (IoT) air quality sensors as well. The study demonstrates how health devices, smartphones and IoT sensors are becoming a part of a new health data ecosystem and how their usage could provide information about high-risk health hotspots, which, in the longer term, could lead to improvement in the quality of life for patients with COPD.
Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System
Bermudez, Sergio A.; Schrott, Alejandro G.; Tsukada, Masahiko; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F.; López, Vanessa; Leona, Marco
2017-01-01
Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects. PMID:28858223
Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System.
Klein, Levente J; Bermudez, Sergio A; Schrott, Alejandro G; Tsukada, Masahiko; Dionisi-Vici, Paolo; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F; López, Vanessa; Leona, Marco
2017-08-31
Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects.
Combining the AIRS, CrIS and IASI Radiance Records for Climate Level Retrievals
NASA Astrophysics Data System (ADS)
Strow, L. L.
2016-12-01
The AIRS record is now 14+ years long, and with the addition of CrIS should provide a 30+ year long hyperspectral radiance record that can be supplemented with another two times in the diurnal cycle with IASI starting in 2007. The stability of these sensors can be established by comparisons to CO2 variability and to tropical sea surface temperature trends. At present the observed stabilities are much better than climate requirements of 0.01/year. SNO observations indicate radiometric agreement among these sensors of 0.1 - 0.3K before any empirical adjustments. A 1-year set of SNO overlaps have statistical uncertainties of less than 0.01K between these three sensors. Moreover, we show that IASI can be used as a transfer standard between AIRS and CrIS (or between CrIS-1 and CrIS-2) should there be a gap in overlap of sensors in the PM orbit. We have done these SNO comparisons by converting AIRS and IASI spectral to the CrIS instrument lineshape (ILS). Achieving climate quality retrievals, trends, and anomalies of temperature and humidity is non-trivial and requires error characterization (not validation) that to date has not been done with single-footprint hyperspectral sensor retrievals. We suggest that the infrared hyperspectral community utilize a common ILS radiance product as a first-step in achieving climate-quality retrievals in order to remove uncertainties in differential instrument sensitivies and in different forward radiative transfer models. We propose a very different approach for Level 3 (climate) products where anomalies and trends (one of the main products of interest to the climate community) are derived directly from Level 3 radiance products, giving far superior error traceability and retrieval regularization in the vertical. Tempertature and humidity trends and anomalies for 14-years of AIRS will be presented and compared to those provided by ERA-Interim, AIRS Level3 data, and microwave sensors. A significant advantage of this approach, which uses small subsets of averaged radiance data, is the ability to re-process the Level 3 type products over and over again since they are so small. In addition, this approach allows others in the community to peform climate-level studies with thes sensors without needing large data processing and storage capabilities.
NASA Technical Reports Server (NTRS)
Greeley, R. S. (Principal Investigator); Ward, E. A.; Elliott, J. C.; Friedman, E. J.; Riley, E. L.; Stryker, S.
1974-01-01
The author has identified the following significant results. Land use change, water quality, and air quality indices have been calculated from analysis of ERTS-1 multispectral scanning imagery and computer compatible tapes. Specifications have been developed and discussed for an ERTS-1 environmental monitoring system which help to serve the information needs of environmental managers at the Federal, state, regional, and local level. General conclusions of the investigation are that ERTS-1 data is very useful in land use mapping and updating to 10-15 categories, and can provide an overall measure of air and water turbidity; however, more and better ground truth and possibly additional spacecraft sensors will be required if specific air and water pollutants are to be quantified from satellite data.
FPGA-based Fused Smart Sensor for Real-Time Plant-Transpiration Dynamic Estimation
Millan-Almaraz, Jesus Roberto; de Jesus Romero-Troncoso, Rene; Guevara-Gonzalez, Ramon Gerardo; Contreras-Medina, Luis Miguel; Carrillo-Serrano, Roberto Valentin; Osornio-Rios, Roque Alfredo; Duarte-Galvan, Carlos; Rios-Alcaraz, Miguel Angel; Torres-Pacheco, Irineo
2010-01-01
Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities. PMID:22163656
Characterizing Intra-Urban Air Quality Gradients with a Spatially-Distributed Network
NASA Astrophysics Data System (ADS)
Zimmerman, N.; Ellis, A.; Schurman, M. I.; Gu, P.; Li, H.; Snell, L.; Gu, J.; Subramanian, R.; Robinson, A. L.; Apte, J.; Presto, A. A.
2016-12-01
City-wide air pollution measurements have typically relied on regulatory or research monitoring sites with low spatial density to assess population-scale exposure. However, air pollutant concentrations exhibit significant spatial variability depending on local sources and features of the built environment, which may not be well captured by the existing monitoring regime. To better understand urban spatial and temporal pollution gradients at 1 km resolution, a network of 12 real-time air quality monitoring stations was deployed beginning July 2016 in Pittsburgh, PA. The stations were deployed at sites along an urban-rural transect and in urban locations with a range of traffic, restaurant, and tall building densities to examine the impact of various modifiable factors. Measurements from the stationary monitoring stations were further supported by mobile monitoring, which provided higher spatial resolution pollutant measurements on nearby roadways and enabled routine calibration checks. The stationary monitoring measurements comprise ultrafine particle number (Aerosol Dynamics "MAGIC" CPC), PM2.5 (Met One Neighborhood PM Monitor), black carbon (Met One BC 1050), and a new low-cost air quality monitor, the Real-time Affordable Multi-Pollutant (RAMP) sensor package for measuring CO, NO2, SO2, O3, CO2, temperature and relative humidity. High time-resolution (sub-minute) measurements across the distributed monitoring network enable insight into dynamic pollutant behaviour. Our preliminary findings show that our instruments are sensitive to PM2.5 gradients exceeding 2 micro-grams per cubic meter and ultrafine particle gradients exceeding 1000 particles per cubic centimeter. Additionally, we have developed rigorous calibration protocols to characterize the RAMP sensor response and drift, as well as multiple linear regression models to convert sensor response into pollutant concentrations that are comparable to reference instrumentation.
A low-cost sensing system for cooperative air quality monitoring in urban areas.
Brienza, Simone; Galli, Andrea; Anastasi, Giuseppe; Bruschi, Paolo
2015-05-26
Air quality in urban areas is a very important topic as it closely affects the health of citizens. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring, so as to allow appropriate and timely decisions. In this paper, we present uSense, a low-cost cooperative monitoring tool that allows knowing, in real-time, the concentrations of polluting gases in various areas of the city. Specifically, users monitor the areas of their interest by deploying low-cost and low-power sensor nodes. In addition, they can share the collected data following a social networking approach. uSense has been tested through an in-field experimentation performed in different areas of a city. The obtained results are in line with those provided by the local environmental control authority and show that uSense can be profitably used for air quality monitoring.
Yang, Chao-Tung; Liao, Chi-Jui; Liu, Jung-Chun; Den, Walter; Chou, Ying-Chyi; Tsai, Jaw-Ji
2014-02-01
Indoor air quality monitoring in healthcare environment has become a critical part of hospital management and policy. Manual air sampling and analysis are cost-inhibitive and do not provide real-time air quality data and response measures. In this month-long study over 14 sampling locations in a public hospital in Taiwan, we observed a positive correlation between CO(2) concentration and population, total bacteria, and particulate matter concentrations, thus monitoring CO(2) concentration as a general indicator for air quality could be a viable option. Consequently, an intelligent environmental monitoring system consisting of a CO(2)/temperature/humidity sensor, a digital plug, and a ZigBee Router and Coordinator was developed and tested. The system also included a backend server that received and analyzed data, as well as activating ventilation and air purifiers when CO(2) concentration exceeded a pre-set value. Alert messages can also be delivered to offsite users through mobile devices.
NASA Astrophysics Data System (ADS)
Osterman, G. B.; Neu, J. L.; Eldering, A.; Pinder, R. W.; Tang, Y.; McQueen, J.
2012-12-01
At night, ozone can be transported long distances above the surface inversion layer without chemical destruction or deposition. As the boundary layer breaks up in the morning, this nocturnal ozone can be mixed down to the surface and rapidly increase ozone concentrations at a rate that can rival chemical ozone production. Most regional scale models that are used for air quality forecasts and ozone source attribution do not adequately capture nighttime ozone concentrations and transport. We combine ozone profile data from the NASA Earth Observing System (EOS) Tropospheric Emission Spectrometer (TES) and other sensors, ozonesonde data collected during the INTEX Ozonesonde Network Study (IONS), EPA AirNow ground station ozone data, the Community Multi-Scale Air Quality (CMAQ) model, and the National Air Quality Forecast Capability (NAQFC) model to examine air quality events during August 2006. We present both aggregated statistics and case-study analyses that assess the relationship between the models' ability to reproduce surface air quality events and their ability to capture the vertical distribution of ozone both during the day and at night. We perform the comparisons looking at the geospatial dependence in the differences between the measurements and models under different surface ozone conditions.
Carbon Dioxide Detection and Indoor Air Quality Control.
Bonino, Steve
2016-04-01
When building ventilation is reduced, energy is saved because it is not necessary to heat or cool as much outside air. Reduced ventilation can result in higher levels of carbon dioxide, which may cause building occupants to experience symptoms. Heating or cooling for ventilation air can be enhanced by a DCV system, which can save energy while providing a comfortable environment. Carbon dioxide concentrations within a building are often used to indicate whether adequate fresh air is being supplied to the building. These DCV systems use carbon dioxide sensors in each space or in the return air and adjust the ventilation based on carbon dioxide concentration; the higher the concentration, the more people occupy the space relative to the ventilation rate. With a carbon dioxide sensor DCV system, the fresh air ventilation rate varies based on the number ofpeople in the space, saving energy while maintaining a safe and comfortable environment.
NASA Astrophysics Data System (ADS)
Showstack, Randy
2010-10-01
A new smartphone application takes advantage of various technological capabilities and sensors to help users monitor air quality. Tapping into smartphone cameras, Global Positioning System (GPS) sensors, compasses, and accelerometers, computer scientists with the University of Southern California's (USC) Viterbi School of Engineering have developed a new application, provisionally entitled “Visibility.” Currently available for the Android telephone operating system, the application is available for free download at http://robotics.usc.edu/˜mobilesensing/Projects/AirVisibilityMonitoring. An iPhone application may be introduced soon. Smartphone users can take a picture of the sky and then compare it with models of sky luminance to estimate visibility. While conventional air pollution monitors are costly and thinly deployed in some areas, the smartphone application potentially could help fill in some blanks in existing air pollution maps, according to USC computer science professor Gaurav Sukhatme.
The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA F...
Performance Evaluation of the United Nations Environment ...
A request for technical collaboration between the UNEP and the US EPA resulted in the establishment of a MCRADA. The purpose of this agreement was to evaluate an air quality monitoring system (referred to as the UNEP pod) developed by the UNEP for use in environmental situations where more sophisticated monitoring instrumentation was not available. The US EPA has conducted numerous evaluations of other similar sensor pods at its Research Triangle Park, NC research campus and has trained staff as well as established research designs for such efforts. Under the terms of the MCRADA, the US EPA would operate the pod using UNEP provided operating procedures in a manner consistent with its planned intent of deployment. The US EPA would collect air quality monitoring data from the pod involving select environmental measures over a period of approximately one month. Reference monitoring data collected from collocated federal regulatory monitors would be used to establish a comparison between the two systems and thus establishment of performance characteristics. In addition, the US EPA would provide feedback information to the UNEP as to observed ease of use features of the pod that would be beneficial in its future evolution and deployment. The UNEP recently developed a multipollutant sensor pod called the UNEP Air Quality Monitoring Unit, herein simply defined as the UNEP pod (http://aqicn.org/faq/2015-10-28/unep-air-quality-monitoring-station/). First introduced in 20
Li, Haitao; Boling, C Sam; Mason, Andrew J
2016-08-01
Airborne pollutants are a leading cause of illness and mortality globally. Electrochemical gas sensors show great promise for personal air quality monitoring to address this worldwide health crisis. However, implementing miniaturized arrays of such sensors demands high performance instrumentation circuits that simultaneously meet challenging power, area, sensitivity, noise and dynamic range goals. This paper presents a new multi-channel CMOS amperometric ADC featuring pixel-level architecture for gas sensor arrays. The circuit combines digital modulation of input currents and an incremental Σ∆ ADC to achieve wide dynamic range and high sensitivity with very high power efficiency and compact size. Fabricated in 0.5 [Formula: see text] CMOS, the circuit was measured to have 164 dB cross-scale dynamic range, 100 fA sensitivity while consuming only 241 [Formula: see text] and 0.157 [Formula: see text] active area per channel. Electrochemical experiments with liquid and gas targets demonstrate the circuit's real-time response to a wide range of analyte concentrations.
NASA Astrophysics Data System (ADS)
Leidinger, Martin; Schultealbert, Caroline; Neu, Julian; Schütze, Andreas; Sauerwald, Tilman
2018-01-01
This article presents a test gas generation system designed to generate ppb level gas concentrations from gas cylinders. The focus is on permanent gases and volatile organic compounds (VOCs) for applications like indoor and outdoor air quality monitoring or breath analysis. In the design and the setup of the system, several issues regarding handling of trace gas concentrations have been considered, addressed and tested. This concerns not only the active fluidic components (flow controllers, valves), which have been chosen specifically for the task, but also the design of the fluidic tubing regarding dead volumes and delay times, which have been simulated for the chosen setup. Different tubing materials have been tested for their adsorption/desorption characteristics regarding naphthalene, a highly relevant gas for indoor air quality monitoring, which has generated high gas exchange times in a previous gas mixing system due to long time adsorption/desorption effects. Residual gas contaminations of the system and the selected carrier air supply have been detected and quantified using both an analytical method (GC-MS analysis according to ISO 16000-6) and a metal oxide semiconductor gas sensor, which detected a maximum contamination equivalent to 28 ppb of carbon monoxide. A measurement strategy for suppressing even this contamination has been devised, which allows the system to be used for gas sensor and gas sensor system characterization and calibration in the low ppb concentration range.
NASA Technical Reports Server (NTRS)
Awtry, A. R.; Miller, J. H.
2002-01-01
The progress in the development of a sensor for the detection of trace air constituents to monitor spacecraft air quality is reported. A continuous-wave (cw), external-cavity tunable diode laser centered at 1.55 micrometers is used to pump an optical cavity absorption cell in cw-cavity ringdown spectroscopy (cw-CRDS). Preliminary results are presented that demonstrate the sensitivity, selectivity and reproducibility of this method. Detection limits of 2.0 ppm for CO, 2.5 ppm for CO2, 1.8 ppm for H2O, 19.4 ppb for NH3, 7.9 ppb for HCN and 4.0 ppb for C2H2 are calculated.
Development and evaluation of a lightweight sensor system ...
A new sensor system for mobile and aerial emission sampling was developed for open area pollutant sources, such as prescribed forest burns. The sensor system, termed “Kolibri”, consists of multiple low-cost air quality sensors measuring CO2, CO, samplers for particulate matter with diameter of 2.5 µm or less (PM2.5), and volatile organic compounds (VOCs). This extended abstract, intended for oral presentation or poster presentation at this summer's AWMA conference, presents some of the first verification data from laboratory and burn calibration of a newly developed sensor and sampler system for ground and aerial sampling.
Saberkari, Hamidreza; Ghavifekr, Habib Badri; Shamsi, Mousa
2015-01-01
In recent years, demand for biological sensors which are capable of fast and accurate detection of minor amounts of pathogens in real-time form has been intensified. Acoustic wave (AW) devices whose performance is determined by mass sensitivity parameters and quality factor are used in biological sensors as platforms with high quality. Yet, current AW devices are facing many challenges such as the low value of their quality factor in practical applications and also their difficulty to use in liquids. The main focus of this article is to study on the magnetostrictive sensors which include milli/microcantilever (MSMC) type. In comparison with AW devices, MSMC has a lot of advantages; (1) its actuation and sensing unit is wirelessly controlled. (2) Its fabrication process is easy. (3) It works well in liquids. (4) It has a high-quality factor (in the air > 500). Simulation results demonstrate that the amount of quality factor depends on environment properties (density and viscosity), MSMC geometry, and its resonant behavior of harmonic modes. PMID:26120566
Over the past decade, a range of sensor technologies became available on the market, enabling a revolutionary shift in air pollution monitoring and assessment. With their cost of up to three orders of magnitude lower than standard/reference instruments, many avenues for applicati...
Recommendations on the use of satellite remote-sensing data for urban air quality.
Engel-Cox, Jill A; Hoff, Raymond M; Haymet, A D J
2004-11-01
In the last 5 yr, the capabilities of earth-observing satellites and the technological tools to share and use satellite data have advanced sufficiently to consider using satellite imagery in conjunction with ground-based data for urban-scale air quality monitoring. Satellite data can add synoptic and geospatial information to ground-based air quality data and modeling. An assessment of the integrated use of ground-based and satellite data for air quality monitoring, including several short case studies, was conducted. Findings identified current U.S. satellites with potential for air quality applications, with others available internationally and several more to be launched within the next 5 yr; several of these sensors are described in this paper as illustrations. However, use of these data for air quality applications has been hindered by historical lack of collaboration between air quality and satellite scientists, difficulty accessing and understanding new data, limited resources and agency priorities to develop new techniques, ill-defined needs, and poor understanding of the potential and limitations of the data. Specialization in organizations and funding sources has limited the resources for cross-disciplinary projects. To successfully use these new data sets requires increased collaboration between organizations, streamlined access to data, and resources for project implementation.
Bearg, D W
1998-09-01
This article summarizes an approach for improving the indoor air quality (IAQ) in a building by providing feedback on the performance of the ventilation system. The delivery of adequate quantities of ventilation to all building occupants is necessary for the achievement of good IAQ. Feedback on the performance includes information on the adequacy of ventilation provided, the effectiveness of the distribution of this air, the adequacy of the duration of operation of the ventilation system, and the identification of leakage into the return plenum, either of outdoor or supply air. Keeping track of ventilation system performance is important not only in terms of maintaining good IAQ, but also making sure that this system continues to perform as intended after changes in building use. Information on the performance of the ventilation system is achieved by means of an automated sampling system that draws air from multiple locations and delivers it to both a carbon dioxide monitor and dew point sensor. The use of single shared sensors facilitates calibration checks as well as helps to guarantee data integrity. This approach to monitoring a building's ventilation system offers the possibility of achieving sustainable performance of this important aspect of good IAQ.
Design of inductive sensors for tongue control system for computers and assistive devices.
Lontis, Eugen R; Struijk, Lotte N S A
2010-07-01
The paper introduces a novel design of air-core inductive sensors in printed circuit board (PCB) technology for a tongue control system. The tongue control system provides a quadriplegic person with a keyboard and a joystick type of mouse for interaction with a computer or for control of an assistive device. Activation of inductive sensors was performed with a cylindrical, soft ferromagnetic material (activation unit). Comparative analysis of inductive sensors in PCB technology with existing hand-made inductive sensors was performed with respect to inductance, resistance, and sensitivity to activation when the activation unit was placed in the center of the sensor. Optimisation of the activation unit was performed in a finite element model. PCBs with air-core inductive sensors were manufactured in a 10 layers, 100 microm and 120 microm line width technology. These sensors provided quality signals that could drive the electronics of the hand-made sensors. Furthermore, changing the geometry of the sensors allowed generation of variable signals correlated with the 2D movement of the activation unit at the sensors' surface. PCB technology for inductive sensors allows flexibility in design, automation of production and ease of possible integration with supplying electronics. The basic switch function of the inductive sensor can be extended to two-dimensional movement detection for pointing devices.
Collier-Oxandale, Ashley; Coffey, Evan; Thorson, Jacob; Johnston, Jill; Hannigan, Michael
2018-04-26
The increased use of low-cost air quality sensor systems, particularly by communities, calls for the further development of best-practices to ensure these systems collect usable data. One area identified as requiring more attention is that of deployment logistics, that is, how to select deployment sites and how to strategically place sensors at these sites. Given that sensors are often placed at homes and businesses, ideal placement is not always possible. Considerations such as convenience, access, aesthetics, and safety are also important. To explore this issue, we placed multiple sensor systems at an existing field site allowing us to examine both neighborhood-level and building-level variability during a concurrent period for CO₂ (a primary pollutant) and O₃ (a secondary pollutant). In line with previous studies, we found that local and transported emissions as well as thermal differences in sensor systems drive variability, particularly for high-time resolution data. While this level of variability is unlikely to affect data on larger averaging scales, this variability could impact analysis if the user is interested in high-time resolution or examining local sources. However, with thoughtful placement and thorough documentation, high-time resolution data at the neighborhood level has the potential to provide us with entirely new information on local air quality trends and emissions.
Plants for Sustainable Improvement of Indoor Air Quality.
Brilli, Federico; Fares, Silvano; Ghirardo, Andrea; de Visser, Pieter; Calatayud, Vicent; Muñoz, Amalia; Annesi-Maesano, Isabella; Sebastiani, Federico; Alivernini, Alessandro; Varriale, Vincenzo; Menghini, Flavio
2018-06-01
Indoor pollution poses a serious threat to human health. Plants represent a sustainable but underexploited solution to enhance indoor air quality. However, the current selection of plants suitable for indoors fails to consider the physiological processes and mechanisms involved in phytoremediation. Therefore, the capacity of plants to remove indoor air pollutants through stomatal uptake (absorption) and non-stomatal deposition (adsorption) remains largely unknown. Moreover, the effects of the indoor plant-associated microbiome still need to be fully analyzed. Here, we discuss how a combination of the enhanced phytoremediation capacity of plants together with cutting-edge air-cleaning and smart sensor technologies can improve indoor life while reducing energy consumption. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Casey, J. G.; Ilie, A. M. C.; Coffey, E.; Collier-Oxandale, A. M.; Hannigan, M.; Vaccaro, C.
2017-12-01
In Colorado and elsewhere in North America, the oil and gas production industry has been growing alongside and in the midst of increasing urban and rural populations. These coinciding trends have resulted in a growing number of people living in close proximity to petroleum production and processing activities, leading to potential public health impacts. Combustion-related emissions from heavy-duty diesel vehicle traffic, generators, compressors, and production stream flaring can potentially lead to locally enhanced levels of nitrogen oxides (NOx), carbon monoxide (CO), and carbon dioxide (CO2). Venting and fugitive emissions of production stream constituents can potentially lead to locally enhanced levels of methane (CH4) and volatile organic compounds (VOCs), some of which (like benzene) are known carcinogens. NOx and VOC emissions can also potentially increase local ozone (O3) production. After learning of a large new multiwell pad on the outskirts of Greeley, Colorado, we were able to quickly mobilize portable air quality monitors outfitted with low-cost gas sensors that respond to CH4, CO2, CO, and O3. The air quality monitors were installed outside homes adjacent to the new multiwell pad several weeks prior to the first spud date. An anemometer was also installed outside one of the homes in order to monitor wind speed and direction. Measurements continued during drilling, hydraulic fracturing, and production phases. The sensors were periodically collocated with reference instruments at a nearby regulatory air quality monitoring site towards calibration via field normalization and validation. Artificial Neural Networks were employed to map sensor signals to trace gas mole fractions during collocation periods. We present measurements of CH4, CO2, CO, and O3 in context with wellpad activities and local meteorology. CO and O3 observations are presented in context with regional measurements and National Ambient Air Quality Standards for each. Wind speed and direction measurements were used to indicate when air masses originated from the direction of the multiwell pad. CO2 mole fractions were used to estimate planetary boundary layer height and CH4 mole fractions were used to identify periods conducive to the pooling and accumulation of production stream venting and fugitive emissions.
NASA Astrophysics Data System (ADS)
Kim, Jinsol; Shusterman, Alexis A.; Lieschke, Kaitlyn J.; Newman, Catherine; Cohen, Ronald C.
2018-04-01
The newest generation of air quality sensors is small, low cost, and easy to deploy. These sensors are an attractive option for developing dense observation networks in support of regulatory activities and scientific research. They are also of interest for use by individuals to characterize their home environment and for citizen science. However, these sensors are difficult to interpret. Although some have an approximately linear response to the target analyte, that response may vary with time, temperature, and/or humidity, and the cross-sensitivity to non-target analytes can be large enough to be confounding. Standard approaches to calibration that are sufficient to account for these variations require a quantity of equipment and labor that negates the attractiveness of the sensors' low cost. Here we describe a novel calibration strategy for a set of sensors, including CO, NO, NO2, and O3, that makes use of (1) multiple co-located sensors, (2) a priori knowledge about the chemistry of NO, NO2, and O3, (3) an estimate of mean emission factors for CO, and (4) the global background of CO. The strategy requires one or more well calibrated anchor points within the network domain, but it does not require direct calibration of any of the individual low-cost sensors. The procedure nonetheless accounts for temperature and drift, in both the sensitivity and zero offset. We demonstrate this calibration on a subset of the sensors comprising BEACO2N, a distributed network of approximately 50 sensor nodes
, each measuring CO2, CO, NO, NO2, O3 and particulate matter at 10 s time resolution and approximately 2 km spacing within the San Francisco Bay Area.
Measuring Infiltration Rates in Homes as a Basis for Understanding Indoor Air Quality
NASA Astrophysics Data System (ADS)
Jerz, G. G.; Lamb, B. K.; Pressley, S. N.; O'Keeffe, P.; Fuchs, M.; Kirk, M.
2015-12-01
Infiltration rates, or the rate of air exchange, of houses are important to understand because ventilation can be a dominate factor in determining indoor air quality. There are chemicals that are emitted from surfaces or point sources inside the home which are harmful to humans; these chemicals come from various objects including furniture, cleaning supplies, building materials, gas stoves, and the surrounding environment. The use of proper ventilation to cycle cleaner outdoor air into the house can be crucial for maintaining healthy living conditions in the home. At the same time, there can also be outdoor pollutants which infiltrate the house and contribute to poor indoor air quality. In either case, it is important to determine infiltration rates as a function of outdoor weather conditions, the house structure properties and indoor heating and cooling systems. In this work, the objective is to measure ventilation rates using periodic releases of a tracer gas and measuring how quickly the tracer concentration decays. CO2 will be used as the tracer gas because it is inert and harmless at low levels. An Arduino timer is connected to a release valve which controls the release of 9.00 SLPM of CO2 into the uptake vent within the test home. CO2 will be released until there is at least a 200 to 300 ppm increase above ambient indoor levels. Computers with CO2 sensors and temperature/pressure sensors attached will be used to record data from different locations within the home which will continuously record data up to a week. The results from these periodic ventilation measurements will be analyzed with respect to outdoor wind and temperature conditions and house structure properties. The data will be used to evaluate an established indoor air quality model.
Morawska, Lidia; Thai, Phong K; Liu, Xiaoting; Asumadu-Sakyi, Akwasi; Ayoko, Godwin; Bartonova, Alena; Bedini, Andrea; Chai, Fahe; Christensen, Bryce; Dunbabin, Matthew; Gao, Jian; Hagler, Gayle S W; Jayaratne, Rohan; Kumar, Prashant; Lau, Alexis K H; Louie, Peter K K; Mazaheri, Mandana; Ning, Zhi; Motta, Nunzio; Mullins, Ben; Rahman, Md Mahmudur; Ristovski, Zoran; Shafiei, Mahnaz; Tjondronegoro, Dian; Westerdahl, Dane; Williams, Ron
2018-07-01
Over the past decade, a range of sensor technologies became available on the market, enabling a revolutionary shift in air pollution monitoring and assessment. With their cost of up to three orders of magnitude lower than standard/reference instruments, many avenues for applications have opened up. In particular, broader participation in air quality discussion and utilisation of information on air pollution by communities has become possible. However, many questions have been also asked about the actual benefits of these technologies. To address this issue, we conducted a comprehensive literature search including both the scientific and grey literature. We focused upon two questions: (1) Are these technologies fit for the various purposes envisaged? and (2) How far have these technologies and their applications progressed to provide answers and solutions? Regarding the former, we concluded that there is no clear answer to the question, due to a lack of: sensor/monitor manufacturers' quantitative specifications of performance, consensus regarding recommended end-use and associated minimal performance targets of these technologies, and the ability of the prospective users to formulate the requirements for their applications, or conditions of the intended use. Numerous studies have assessed and reported sensor/monitor performance under a range of specific conditions, and in many cases the performance was concluded to be satisfactory. The specific use cases for sensors/monitors included outdoor in a stationary mode, outdoor in a mobile mode, indoor environments and personal monitoring. Under certain conditions of application, project goals, and monitoring environments, some sensors/monitors were fit for a specific purpose. Based on analysis of 17 large projects, which reached applied outcome stage, and typically conducted by consortia of organizations, we observed that a sizable fraction of them (~ 30%) were commercial and/or crowd-funded. This fact by itself signals a paradigm change in air quality monitoring, which previously had been primarily implemented by government organizations. An additional paradigm-shift indicator is the growing use of machine learning or other advanced data processing approaches to improve sensor/monitor agreement with reference monitors. There is still some way to go in enhancing application of the technologies for source apportionment, which is of particular necessity and urgency in developing countries. Also, there has been somewhat less progress in wide-scale monitoring of personal exposures. However, it can be argued that with a significant future expansion of monitoring networks, including indoor environments, there may be less need for wearable or portable sensors/monitors to assess personal exposure. Traditional personal monitoring would still be valuable where spatial variability of pollutants of interest is at a finer resolution than the monitoring network can resolve. Copyright © 2018 Elsevier Ltd. All rights reserved.
A Citizen Science and Government Collaboration: Developing ...
The U.S. Environmental Protection Agency (EPA) is actively involved in supporting citizen science projects and providing communities with information and assistance for conducting their own air pollution monitoring. As part of a Regional Applied Research Effort (RARE) project, EPA's Office of Research and Development (ORD) worked collaboratively with EPA Region 2 and the Ironbound Community Corporation (ICC) in Newark, New Jersey, to develop and test the “Air Sensor Toolbox for Citizen Scientists.” In this collaboration, citizen scientists measured local gaseous and particulate air pollution levels by using a customized low-cost sensor pod designed and fabricated by EPA. This citizen science air quality measurement project provided an excellent opportunity for EPA to evaluate and improve the Toolbox resources available to communities. The Air Sensor Toolbox, developed in coordination with the ICC, can serve as a template for communities across the country to use in developing their own air pollution monitoring programs in areas where air pollution is a concern. This pilot project provided an opportunity for a highly motivated citizen science organization and the EPA to work together directly to address environmental concerns within the community. Useful lessons were learned about how to improve coordination between the government and communities and the types of tools and technologies needed for conducting an effective citizen science project that can be app
NASA Astrophysics Data System (ADS)
Hersey, S. P.; DiVerdi, R.; Gadtaula, P.; Sheneman, T.; Flores, K.; Chen, Y. H.; Jayne, J. T.; Cross, E. S.
2017-12-01
Throughout the 2016-2017 academic year, a new partnership between Olin College of Engineering and Aerodyne Research, Inc. developed an affordable, self-contained air quality monitoring instrument called Modulair. The Modulair instrument is based on the same operating principles as Aerodyne's newly-developed ARISense integrated sensor system, employing electrochemical sensors for gas-phase measurements of CO, NO, NO2, and O3 and an off-the-shelf optical particle counter for particle concentration, number, and size distribution information (0.4 < dp < 17 microns). High Dimensional Model Representation (HDMR) has been used to model the interference derived from relative humidity and temperature as well as the cross-sensitivity of the electrochemical sensors to non-target gas-phase species. The aim of the modeling effort is to provide transparent and robust calibration of electrical signals to pollutant concentrations from a set of electrochemical sensors. Modulair was designed from the ground-up, with custom electronics - including a more powerful microcontroller, a fully re-designed housing and a device-specific backend with a mobile, cloud-based data management system for real-time data posting and analysis. Open source tools and software were utilized in the development of the instrument. All initial work was completed by a team of undergraduate students as part of the Senior Capstone Program in Engineering (SCOPE) at Olin College. Deployment strategies for Modulair include distributed, mobile measurements and drone-based aerial sampling. Design goals for the drone integration include maximizing airborne sampling time and laying the foundation for software integration with the drone's autopilot system to allow for autonomous plume sampling across concentration gradients. Modulair and its flexible deployments enable real-time mapping of air quality data at exposure-relevant spatial scales, as well as regular, autonomous characterization of sources and dispersion of atmospheric pollutants. We will present an overview of the Modulair instrument and results from benchtop and field validation, including mobile and drone-based plume sampling in the Boston area.
Large Scale Application of Vibration Sensors for Fan Monitoring at Commercial Layer Hen Houses
Chen, Yan; Ni, Ji-Qin; Diehl, Claude A.; Heber, Albert J.; Bogan, Bill W.; Chai, Li-Long
2010-01-01
Continuously monitoring the operation of each individual fan can significantly improve the measurement quality of aerial pollutant emissions from animal buildings that have a large number of fans. To monitor the fan operation by detecting the fan vibration is a relatively new technique. A low-cost electronic vibration sensor was developed and commercialized. However, its large scale application has not yet been evaluated. This paper presents long-term performance results of this vibration sensor at two large commercial layer houses. Vibration sensors were installed on 164 fans of 130 cm diameter to continuously monitor the fan on/off status for two years. The performance of the vibration sensors was compared with fan rotational speed (FRS) sensors. The vibration sensors exhibited quick response and high sensitivity to fan operations and therefore satisfied the general requirements of air quality research. The study proved that detecting fan vibration was an effective method to monitor the on/off status of a large number of single-speed fans. The vibration sensor itself was $2 more expensive than a magnetic proximity FRS sensor but the overall cost including installation and data acquisition hardware was $77 less expensive than the FRS sensor. A total of nine vibration sensors failed during the study and the failure rate was related to the batches of product. A few sensors also exhibited unsteady sensitivity. As a new product, the quality of the sensor should be improved to make it more reliable and acceptable. PMID:22163544
Carvlin, Graeme N; Lugo, Humberto; Olmedo, Luis; Bejarano, Ester; Wilkie, Alexa; Meltzer, Dan; Wong, Michelle; King, Galatea; Northcross, Amanda; Jerrett, Michael; English, Paul B; Hammond, Donald; Seto, Edmund
2017-12-01
The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM 2.5 and PM 10 (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R 2 for converted hourly averaged Dylos mass measurements versus a PM 2.5 BAM was 0.79 and that versus a PM 10 BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM 2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R 2 = 0.35-0.81). The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.
NASA Astrophysics Data System (ADS)
Chang, C. H.; Pietras, J.; Heppner, P.; Evans, J. D.; Wang, J.
2016-12-01
The Mobile Platform Environmental Data (MoPED) system acquires real-time data on weather conditions from commercial fleet providers and provides them to the National Weather Service (NWS) for use in operations and numerical models. The MoPED system assesses the quality of these data by comparing them to observations from airport weather stations when the mobile platforms are in sufficiently close proximity (in space and time). We have devised a set of quality control algorithms that are applied to vehicle observation datasets to qualify them for dissemination to NWS. Commercial vehicles participating in MoPED have a third-party suite of sensors for ambient air temperature, relative humidity, light level, precipitation intensity, atmospheric pressure, ozone, and road temperature. In addition, some vehicles also generate meteorological data from sensors built into the vehicles themselves (original equipment manufacturer (OEM) sensors) which conform to the SAE J1939 standard for onboard vehicle networking. These sensors, known as OEM J-data sensors, measure numerous parameters associated with emissions control and engine performance - including ambient air temperature and atmospheric pressure. Time-tagged and transmitted to the MoPED system, these OEM J-data measurements can be a tremendous source of weather data for NWS if they can be extracted and communicated in real-time from the vehicles. We are working with a commercial fleet (who have OEM J-data available) to determine suitability of these data for NWS. To ensure the overall quality of the data, we have developed a methodology for assessing the suitability of classes of vehicles and sensors for inclusion in the MoPED dissemination, for the continued assessment of individual vehicles once their class has been accepted into MoPED, and for identifying corrective measures (such as adjusting measurements to correct for individual sensor offsets). A byproduct of that methodology is a multi-component model for sources of errors in mobile meteorological data measurements. We describe this error model, and provide examples of studies of candidate OEM J-data vehicle fleets in which we measured or compensated for various components of the error model.
NASA Astrophysics Data System (ADS)
Garcia, V.; Kondragunta, S.; Holland, D.; Dimmick, F.; Boothe, V.; Szykman, J.; Chu, A.; Kittaka, C.; Al-Saadi, J.; Engel-Cox, J.; Hoff, R.; Wayland, R.; Rao, S.; Remer, L.
2006-05-01
Advancements in remote sensing over the past decade have been recognized by governments around the world and led to the development of the international Global Earth Observation System of Systems 10-Year Implementation Plan. The plan for the U.S. contribution to GEOSS has been put forth in The Strategic Plan for the U.S. Integrated Earth Observation System (IEOS) developed under IWGEO-CENR. The approach for the development of the U.S. IEOS is to focus on specific societal benefits that can be achieved by integrating the nation's Earth observation capabilities. One such challenge is our ability to understand the impact of poor air quality on human health and well being. Historically, the air monitoring networks put in place for the Nations air quality programs provided the only aerosol air quality data on an ongoing and systematic basis at national levels. However, scientific advances in the remote sensing of aerosols from space have improved dramatically. The MODIS sensor and GOES Imager aboard NASA and NOAA satellites, respectively, provide synoptic-scale measurements of aerosol optical depth (AOD) which have been demonstrated to correlate with high levels of PM10 and PM2.5 at the surface. The MODIS sensor has been shown to be capable of a 1 km x 1 km (at nadir) AOD product, while the GOES Imager can provide AOD at 4 km x 4 km every 30 minutes. Within the next several years NOAA and EPA will begin to issue PM2.5 air quality forecasts over the entire domain of the eastern United States, eventually extending to national coverage. These forecasts will provide continuous estimated values of PM2.5 on a daily basis. A multi-agency collaborative project among government and academia is underway to improve the spatial prediction of fine particulate matter through the integration of multi-sensor and multi-platform aerosol observations (MODIS and GOES), numerical model output, and air monitoring data. By giving more weight to monitoring data in monitored areas and relying on adjusted model output and satellite data in non-monitored areas, a Bayesian hierarchical space-time model will be used to improve the accuracy of prediction and associated prediction errors. The improved spatial predictions will be tested as estimates of exposure for input to modeling relationships between air quality and asthma/other respiratory diseases through CDC under the Environmental Public Health Tracking Network. We will also focus on the use of the predictive spatial maps within the EPA AIRNow program which provides near real-time spatial maps of daily average PM2.5 concentrations across the US. We will present the overall project plan and preliminary results with emphasis on how GEOSS framework is facilitating this effort.
NASA Technical Reports Server (NTRS)
Alvarado, D. R.; Bortner, M. H.; Grenda, R. N.; Frippel, G. G.; Halsey, H.; Neste, S. L.; Kritikos, H.; Keafer, L. S.; Deryder, L. J.
1982-01-01
The technology advancements needed to implement the atmospheric observation satellite systems for air quality research were identified. Tropospheric measurements are considered. The measurements and sensors are based on a model of knowledge objectives in atmospheric science. A set of potential missions and attendant spacecraft and sensors is postulated. The results show that the predominant technology needs will be in passive and active sensors for accurate and frequent global measurements of trace gas concentration profiles.
The next generation of low-cost personal air quality sensors for quantitative exposure monitoring
NASA Astrophysics Data System (ADS)
Piedrahita, R.; Xiang, Y.; Masson, N.; Ortega, J.; Collier, A.; Jiang, Y.; Li, K.; Dick, R.; Lv, Q.; Hannigan, M.; Shang, L.
2014-03-01
Advances in embedded systems and low-cost gas sensors are enabling a new wave of low cost air quality monitoring tools. Our team has been engaged in the development of low-cost wearable air quality monitors (M-Pods) using the Arduino platform. The M-Pods use commercially available metal oxide semiconductor (MOx) sensors to measure CO, O3, NO2, and total VOCs, and NDIR sensors to measure CO2. MOx sensors are low in cost and show high sensitivity near ambient levels; however they display non-linear output signals and have cross sensitivity effects. Thus, a quantification system was developed to convert the MOx sensor signals into concentrations. Two deployments were conducted at a regulatory monitoring station in Denver, Colorado. M-Pod concentrations were determined using laboratory calibration techniques and co-location calibrations, in which we place the M-Pods near regulatory monitors to then derive calibration function coefficients using the regulatory monitors as the standard. The form of the calibration function was derived based on laboratory experiments. We discuss various techniques used to estimate measurement uncertainties. A separate user study was also conducted to assess personal exposure and M-Pod reliability. In this study, 10 M-Pods were calibrated via co-location multiple times over 4 weeks and sensor drift was analyzed with the result being a calibration function that included drift. We found that co-location calibrations perform better than laboratory calibrations. Lab calibrations suffer from bias and difficulty in covering the necessary parameter space. During co-location calibrations, median standard errors ranged between 4.0-6.1 ppb for O3, 6.4-8.4 ppb for NO2, 0.28-0.44 ppm for CO, and 16.8 ppm for CO2. Median signal to noise (S/N) ratios for the M-Pod sensors were higher for M-Pods than the regulatory instruments: for NO2, 3.6 compared to 23.4; for O3, 1.4 compared to 1.6; for CO, 1.1 compared to 10.0; and for CO2, 42.2 compared to 300-500. The user study provided trends and location-specific information on pollutants, and affected change in user behavior. The study demonstrated the utility of the M-Pod as a tool to assess personal exposure.
NASA Astrophysics Data System (ADS)
Osterman, G. B.; Eldering, A.; Neu, J. L.; Tang, Y.; McQueen, J.; Pinder, R. W.
2011-12-01
To help protect human health and ecosystems, regional-scale atmospheric chemistry models are used to forecast high ozone events and to design emission control strategies to decrease the frequency and severity of ozone events. Despite the impact that nighttime aloft ozone can have on surface ozone, regional-scale atmospheric chemistry models often do not simulate the nighttime ozone concentrations well and nor do they sufficiently capture the ozone transport patterns. Fully characterizing the importance of the nighttime ozone has been hampered by limited measurements of the vertical distribution of ozone and ozone-precursors. The main focus of this work is to begin to utilize remote sensing data sets to characterize the impact of nighttime aloft ozone to air quality events. We will describe our plans to use NASA satellite data sets, transport models and air quality models to study ozone transport, focusing primarily on nighttime ozone and provide initial results. We will use satellite and ozonesonde data to help understand how well the air quality models are simulating ozone in the lower free troposphere and attempt to characterize the impact of nighttime ozone to air quality events. Our specific objectives are: 1) Characterize nighttime aloft ozone using remote sensing data and sondes. 2) Evaluate the ability of the Community Multi-scale Air Quality (CMAQ) model and the National Air Quality Forecast Capability (NAQFC) model to capture the nighttime aloft ozone and its relationship to air quality events. 3) Analyze a set of air quality events and determine the relationship of air quality events to the nighttime aloft ozone. We will achieve our objectives by utilizing the ozone profile data from the NASA Earth Observing System (EOS) Tropospheric Emission Spectrometer (TES) and other sensors, ozonesonde data collected during the Aura mission (IONS), EPA AirNow ground station ozone data, the CMAQ continental-scale air quality model, and the National Air Quality Forecast model.
Build Your Own Particle Sensor
EPA researchers participate in educational outreach to schools, museums and other locations to teach children about air quality and climate change research. As part of the outreach, researchers have developed several hands-on activities for teachers.
The U.S. Environmental Protection Agency's (EPA) authority for enhanced monitoring activities is provided for in Title I, Section 182 of the Clean Air Act Amendment of 1990. or example, the Photochemical Assessment Monitoring Station (PAMS) network is one such program which requi...
Gutiérrez, Manuel; Llobera, Andreu; Vila-Planas, Jordi; Capdevila, Fina; Demming, Stefanie; Büttgenbach, Stephanus; Mínguez, Santiago; Jiménez-Jorquera, Cecilia
2010-07-01
A multiparametric system able to classify red and white wines according to the grape varieties and for analysing some specific parameters is presented. The system, known as hybrid electronic tongue, consists of an array of electrochemical microsensors and a colorimetric optofluidic system. The array of electrochemical sensors is composed of six ISFETs based sensors, a conductivity sensor, a redox potential sensor and two amperometric electrodes, an Au microelectrode and a microelectrode for sensing electrochemical oxygen demand. The optofluidic system is entirely fabricated in polymer technology and comprises a hollow structure, air mirrors, microlenses and self-alignment structures. The data obtained from these sensors has been treated with multivariate advanced tools; Principal Component Analysis (PCA), for the patterning recognition and classification of wine samples, and Partial-Least Squares (PLS) regression, for quantification of several chemical and optical parameters of interest in wine quality. The results have demonstrated the utility of this system for distinguishing the samples according to the grape variety and year vintage and for quantifying several sample parameters of interest in wine quality control.
Breathable and Stretchable Temperature Sensors Inspired by Skin.
Chen, Ying; Lu, Bingwei; Chen, Yihao; Feng, Xue
2015-06-22
Flexible electronics attached to skin for healthcare, such as epidermal electronics, has to struggle with biocompatibility and adapt to specified environment of skin with respect to breath and perspiration. Here, we report a strategy for biocompatible flexible temperature sensors, inspired by skin, possessing the excellent permeability of air and high quality of water-proof by using semipermeable film with porous structures as substrate. We attach such temperature sensors to underarm and forearm to measure the axillary temperature and body surface temperature respectively. The volunteer wears such sensors for 24 hours with two times of shower and the in vitro test shows no sign of maceration or stimulation to the skin. Especially, precise temperature changes on skin surface caused by flowing air and water dropping are also measured to validate the accuracy and dynamical response. The results show that the biocompatible temperature sensor is soft and breathable on the human skin and has the excellent accuracy compared to mercury thermometer. This demonstrates the possibility and feasibility of fully using the sensors in long term body temperature sensing for medical use as well as sensing function of artificial skin for robots or prosthesis.
Comparison of Calibration Techniques for Low-Cost Air Quality Monitoring
NASA Astrophysics Data System (ADS)
Malings, C.; Ramachandran, S.; Tanzer, R.; Kumar, S. P. N.; Hauryliuk, A.; Zimmerman, N.; Presto, A. A.
2017-12-01
Assessing the intra-city spatial distribution and temporal variability of air quality can be facilitated by a dense network of monitoring stations. However, the cost of implementing such a network can be prohibitive if high-quality but high-cost monitoring systems are used. To this end, the Real-time Affordable Multi-Pollutant (RAMP) sensor package has been developed at the Center for Atmospheric Particle Studies of Carnegie Mellon University, in collaboration with SenSevere LLC. This self-contained unit can measure up to five gases out of CO, SO2, NO, NO2, O3, VOCs, and CO2, along with temperature and relative humidity. Responses of individual gas sensors can vary greatly even when exposed to the same ambient conditions. Those of VOC sensors in particular were observed to vary by a factor-of-8, which suggests that each sensor requires its own calibration model. To this end, we apply and compare two different calibration methods to data collected by RAMP sensors collocated with a reference monitor station. The first method, random forest (RF) modeling, is a rule-based method which maps sensor responses to pollutant concentrations by implementing a trained sequence of decision rules. RF modeling has previously been used for other RAMP gas sensors by the group, and has produced precise calibrated measurements. However, RF models can only predict pollutant concentrations within the range observed in the training data collected during the collocation period. The second method, Gaussian process (GP) modeling, is a probabilistic Bayesian technique whereby broad prior estimates of pollutant concentrations are updated using sensor responses to generate more refined posterior predictions, as well as allowing predictions beyond the range of the training data. The accuracy and precision of these techniques are assessed and compared on VOC data collected during the summer of 2017 in Pittsburgh, PA. By combining pollutant data gathered by each RAMP sensor and applying appropriate calibration techniques, the potentially noisy or biased responses of individual sensors can be mapped to pollutant concentration values which are comparable to those of reference instruments.
NASA Astrophysics Data System (ADS)
Rachmatika, Ratih; Adriyanto, Feri
2017-09-01
Current sensors to monitor water quality are made of manual sensors, which reported to have good performance. However, the major problems, which manual process to get the data. In addition, the data interpretation takes a long time. Due to these problems, a new approach needs to be introduced into the process to prevent a long data acquisition. Therefore, the SIAGA application was proposed. The application of SIAGA is divided into two main applications which are SIBA (Siaga Banjir) and SIAB (Siaga Air Bersih). We using WiFi system which is located at points along the flow of river.. The result can be monitored in the online application based on smartphone which is divided into the river water quality, potential sources of pollution and flood area. Each WiFi point is completed with the instruments which are divided into the sensors that can do the identification of parameters to determine the water quality such as temperature, pH, water level and turbidity. This instrument completed using GPS (Global Positioning System), Full Map menu. The instrument was succesfully monitoredthe flood distribution and water quality in Bengawan Solo river.
Sozzi, R; Bolignano, A; Ceradini, S; Morelli, M; Petenko, I; Argentini, S
2017-10-15
According to the European Directive 2008/50/CE, the air quality assessment consists in the measurement of the concentration fields, and the evaluation of the mean, number of exceedances, etc. of some chemical species dangerous to human health. The measurements provided by an air quality ground-based monitoring network are the main information source but the availability of these data is often limited by several technical and operational problems. In this paper, the best linear unbiased estimator (BLUE) is proposed to validate the pollutant concentration values and to fill the gaps in the measurement of time series collected by a monitoring network. The BLUE algorithm is tested using the daily mean concentrations of particulate matter having aerodynamic diameter less than 10 μ (PM 10 concentrations) measured by the air quality monitoring sensors operating in the Lazio Region in Italy. The comparison between the estimated and measured data evidences an error comparable with the measurement uncertainty. Due to its simplicity and reliability, the BLUE will be used in the routine quality test procedures of the Lazio air quality monitoring network measurements.
Overview of NASA's Observations for Global Air Quality
NASA Astrophysics Data System (ADS)
Kaye, J. A.
2015-12-01
Observations of pollutants are central to the study of air quality. Much focus has been placed on local-scale observations that can help specific geographic areas document their air quality issues, plan abatement strategies, and understand potential impacts. In addition, long-range atmospheric transport of pollutants can cause downwind regions to not meet attainment standards. Satellite observations have shed significant light on air quality from local to regional to global scales, especially for pollutants such as ozone, aerosols, carbon monoxide, sulfur dioxide, and nitrogen dioxide. These observations have made use of multiple techniques and in some cases multiple satellite sensors. The satellite observations are complemented by surface observations, as well as atmospheric (in situ) observations typically made as part of focused airborne field campaigns. The synergy between satellite observations and field campaigns has been an important theme for recent and upcoming activities and plans. In this talk, a review of NASA's investments in observations relevant to global air quality will be presented, with examples given for a range of pollutants and measurement approaches covering the last twenty-five years. These investments have helped build national and international collaborations such that the global satellite community is now preparing to deploy a constellation of satellites that together will provide fundamental advances in global observations for air quality.
The use of modern technologies in carbon dioxide monitoring
NASA Astrophysics Data System (ADS)
Komínek, Petr; Weyr, Jan; Hirš, Jiří
2017-12-01
Indoor environment has huge influence on person's health and overall comfort. It is of great importance that we realize how essential indoor air quality is, considering we spend on average as much as 90% of our time indoors. There are many factors that affect indoor air quality: specifically, inside air temperature, relative humidity, and odors to name the most important factors. One of the key factors indicating indoor air quality is carbon dioxide (CO2) level. The CO2 levels, measured in prefab apartment buildings, indicates substantial indoor air quality issues. Therefore, a proper education of the occupants is of utmost importance. Also, great care should be directed towards technical and technological solutions that would ensure meeting the normative indoor environment criteria, especially indoor air CO2 levels. Thanks to the implementation of new emerging autonomous technologies, such as Internet of Things (IoT), monitoring in real-time is enhanced. An area where IoT plays a major role is in the monitoring of indoor environment. IoT technology (e.g. smart meters and sensors) provide awareness of information about the quality of indoor environment. There is a huge potential for influencing behaviour of the users. Through the web application, it is possible to educate people and ensure fresh air supply.
Real-time GIS data model and sensor web service platform for environmental data management.
Gong, Jianya; Geng, Jing; Chen, Zeqiang
2015-01-09
Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service Web method is proposed that can be employed for environmental data management. The purpose of this study is to determine a method to realize environmental data management under the Geospatial Service Web framework. A real-time GIS (Geographic Information System) data model and a Sensor Web service platform to realize environmental data management under the Geospatial Service Web framework are proposed in this study. The real-time GIS data model manages real-time data. The Sensor Web service platform is applied to support the realization of the real-time GIS data model based on the Sensor Web technologies. To support the realization of the proposed real-time GIS data model, a Sensor Web service platform is implemented. Real-time environmental data, such as meteorological data, air quality data, soil moisture data, soil temperature data, and landslide data, are managed in the Sensor Web service platform. In addition, two use cases of real-time air quality monitoring and real-time soil moisture monitoring based on the real-time GIS data model in the Sensor Web service platform are realized and demonstrated. The total time efficiency of the two experiments is 3.7 s and 9.2 s. The experimental results show that the method integrating real-time GIS data model and Sensor Web Service Platform is an effective way to manage environmental data under the Geospatial Service Web framework.
Evaluation of Elm and Speck Sensors
Particulate matter (PM) is a pollutant of high public interest regulated by national ambient air quality standards (NAAQS) using Federal Reference Method (FRM) and Federal Equivalent Method (FEM) instrumentation identified for environmental monitoring. The US EPA has been evaluat...
Jiang, Yong; Liang, Peng; Huang, Xia; Ren, Zhiyong Jason
2018-07-01
Toxicity monitoring is essential for the protection of public health and ecological safety. Microbial fuel cell (MFC) sensors demonstrated good potential in toxicity monitoring, but current MFC sensors can only be used for anaerobic water monitoring. In this study, a novel gas diffusion (GD)-biocathode sensing element was fabricated using a simple method. The GD-biocathode MFC sensor can directly be used for formaldehyde detection (from 0.0005% to 0.005%) in both aerobic and anaerobic water bodies. Electrochemical analysis indicated that the response by the sensor was caused by the toxic inhibition to the microbial activity for the oxygen reduction reaction (ORR). This study for the first time demonstrated that the GD-biocathode MFC sensor has a detection limit of 20 ppm for formaldehyde and can be used to monitor air pollution. Selective sensitivity to formaldehyde was not achieved as the result of using a mixed-culture, which confirms that it can serve as a generic biosensor for monitoring gaseous pollutants. This study expands the realm of knowledge for MFC sensor applications. Copyright © 2018 Elsevier Ltd. All rights reserved.
Environment quality monitoring using ARM processor
NASA Astrophysics Data System (ADS)
Vinaya, C. H.; Krishna Thanikanti, Vamsi; Ramasamy, Sudha
2017-11-01
This paper of air quality monitoring system describes a model of sensors network to continuously monitoring the environment with low cost developed model. At present time all over the world turned into a great revolution in industrial domain and on the other hand environment get polluting in a dangerous value. There are so many technologies present to reduce the polluting contents but still there is no completely reduction of that pollution. Even there are different methods to monitor the pollution content; these are much costly that not everyone can adapt those methods or devices. Now we are proposing a sensors connected network to monitor the environment continuously and displaying the pollutant gases percentage in air surroundings and can transmit the results to our mobiles by message. The advantage of this system is easy to design, establish at area to monitor, maintenance and most cost effective as well.
NASA Astrophysics Data System (ADS)
Pikelnaya, O.; Polidori, A.; Wimmer, R.; Mellqvist, J.; Samuelsson, J.; Marianne, E.; Andersson, P.; Brohede, S.; Izos, O.
2017-12-01
Industrial facilities such as refineries and oil processing facilities can be sources of chemicals adversely affecting human health, for example aromatic hydrocarbons and formaldehyde. In an urban setting, such as the South Coast Air Basin (SCAB), exposure to harmful air pollutants (HAP's) for residents of communities neighboring such facilities is of serious concern. Traditionally, exposure assessments are performed by modeling a community exposure using emission inventories and data collected at fixed air monitoring sites. However, recent field measurements found that emission inventories may underestimate HAP emissions from refineries; and HAP measurements data from fixed sites is lacking spatial resolution; as a result, the impact of HAP emissions on communities is highly uncertain. The next generation air monitoring technologies can help address these challenges. For example, dense "low-cost" sensors allow continuous monitoring of concentrations of pollutants within communities with high temporal- and spatial- resolution, and optical remote sensing (ORS) technologies offer measurements of emission fluxes and real-time ground-concentration mapping of HAPs. South Coast Air Quality Management District (SCAQMD) is currently conducting a multi-year study using ORS methods and "low-cost" Volatile Organic Compounds (VOCs) sensors to monitor HAP emissions from selected industrial facilities in the SCAB and their ambient concentrations in neighboring communities. For this purpose, quarterly mobile ORS surveys are conducted to quantify facility-wide emissions for VOCs, aromatic hydrocarbons and HCHO, and to collect ground-concentration profiles of these pollutants inside neighboring communities. Additionally, "low-cost" sensor nodes for deployment in neighborhood(s) downwind of the facilities have been developed in order to obtain long-term, granular data on neighborhood VOC concentrations, During this presentation we will discuss initial results of quarterly ORS surveys and pilot "low-cost" sensor deployments. We will also outline benefits of using a combination of mobile ORS surveys and "low-cost" sensor networks for community exposure monitoring.
NASA Astrophysics Data System (ADS)
Raatschen, W.; Sjoegren, M.
The subject of indoor and outdoor air quality has generated a great deal of attention in many countries. Areas of concern include outgassing of building materials as well as occupant-generated pollutants such as carbon dioxide, moisture, and odors. Progress has also been made towards addressing issues relating to the air tightness of the building envelope. Indoor air quality studies indicate that better control of supply flow rates as well as the air distribution pattern within buildings are necessary. One method of maintaining good indoor air quality without extensive energy consumption is to control the ventilation rate according to the needs and demands of the occupants, or to preserve the building envelope. This is accomplished through the use of demand controlled ventilating (DCV) systems. The specific objective of Annex 18 is to develop guidelines for demand controlled ventilating systems based on state of the art analyses, case studies on ventilation effectiveness, and proposed ventilation rates for different users in domestic, office, and school buildings.
Fine Resolution Air Quality Monitoring from a Small Satellite: CHRIS/PROBA.
Nichol, Janet E; Wong, Man Sing; Chan, Yuk Ying
2008-11-27
Current remote sensing techniques fail to address the task of air quality monitoring over complex regions where multiple pollution sources produce high spatial variability. This is due to a lack of suitable satellite-sensor combinations and appropriate aerosol optical thickness (AOT) retrieval algorithms. The new generation of small satellites, with their lower costs and greater flexibility has the potential to address this problem, with customised platform-sensor combinations dedicated to monitoring single complex regions or mega-cities. This paper demonstrates the ability of the European Space Agency's small satellite sensor CHRIS/PROBA to provide reliable AOT estimates at a spatially detailed level over Hong Kong, using a modified version of the dense dark vegetation (DDV) algorithm devised for MODIS. Since CHRIS has no middle-IR band such as the MODIS 2,100 nm band which is transparent to fine aerosols, the longest waveband of CHRIS, the 1,019 nm band was used to approximate surface reflectance, by the subtraction of an offset derived from synchronous field reflectance spectra. Aerosol reflectance in the blue and red bands was then obtained from the strong empirical relationship observed between the CHRIS 1,019 nm, and the blue and red bands respectively. AOT retrievals for three different dates were shown to be reliable, when compared with AERONET and Microtops II sunphotometers, and a Lidar, as well as air quality data at ground stations. The AOT images exhibited considerable spatial variability over the 11 x 11km image area and were able to indicate both local and long distance sources.
NASA Technical Reports Server (NTRS)
Kibler, J. F.; Suttles, J. T.
1977-01-01
One way to obtain estimates of the unknown parameters in a pollution dispersion model is to compare the model predictions with remotely sensed air quality data. A ground-based LIDAR sensor provides relative pollution concentration measurements as a function of space and time. The measured sensor data are compared with the dispersion model output through a numerical estimation procedure to yield parameter estimates which best fit the data. This overall process is tested in a computer simulation to study the effects of various measurement strategies. Such a simulation is useful prior to a field measurement exercise to maximize the information content in the collected data. Parametric studies of simulated data matched to a Gaussian plume dispersion model indicate the trade offs available between estimation accuracy and data acquisition strategy.
Evaluation of Field-deployed Low Cost PM Sensors
Background Particulate matter (PM) is a pollutant of high public interest regulated by national ambient air quality standards (NAAQS) using federal reference method (FRM) and federal equivalent method (FEM) instrumentation identified for environmental monitoring. PM is present i...
Polymer-carbon black composite sensors in an electronic nose for air-quality monitoring
NASA Technical Reports Server (NTRS)
Ryan, M. A.; Shevade, A. V.; Zhou, H.; Homer, M. L.
2004-01-01
An electronic nose that uses an array of 32 polymer-carbon black composite sensors has been developed, trained, and tested. By selecting a variety of chemical functionalities in the polymers used to make sensors, it is possible to construct an array capable of identifying and quantifying a broad range of target compounds, such as alcohols and aromatics, and distinguishing isomers and enantiomers (mirror-image isomers). A model of the interaction between target molecules and the polymer-carbon black composite sensors is under development to aid in selecting the array members and to enable identification of compounds with responses not stored in the analysis library.
Willa, Christoph; Schmid, Alexander; Briand, Danick; Yuan, Jiayin; Koziej, Dorota
2017-08-02
We report a light, flexible, and low-power poly(ionic liquid)/alumina composite CO 2 sensor. We monitor the direct-current resistance changes as a function of CO 2 concentration and relative humidity and demonstrate fast and reversible sensing kinetics. Moreover, on the basis of the alternating-current impedance measurements we propose a sensing mechanism related to proton conduction and gas diffusion. The findings presented herein will promote the development of organic/inorganic composite CO 2 gas sensors. In the future, such sensors will be useful for numerous practical applications ranging from indoor air quality control to the monitoring of manufacturing processes.
Indoor Environment in Residential Prefabricated Buildings
NASA Astrophysics Data System (ADS)
Kraus, Michal; Juhásová Šenitková, Ingrid
2017-10-01
The contribution presents results of the experimental measurement of indoor air quality in residential prefabricated buildings. People spend about 90% of their life in the indoor environment of buildings. Hygrothermal parameters and indoor air quality are the essential component that define the quality of the indoor environment. The results of case study characterize the quality of the indoor environment of the ordinary occupants in housing unit of residential prefabricated building. A current problem of revitalized prefabricated buildings is inadequate air exchange and related thereto to poor indoor air quality. The experimental measurements were carried out just before and at the beginning of the heating season (from 1st October to 30th November 2016). Heating season was launched in the middle of experimental measurement. The wireless indoor sensor Elgato Eve Room was used for measurements. The obtained values of indoor air temperature [°C], relative humidity [%] and indoor air quality [ppm] are describe and analysis in this study. The results of the study indicate that the values of temperature and indoor air quality meet optimal levels during the experiment with nuances. The mean air temperature in the indoor environment is 22.43 °C. The temperature of the indoor environment is held at the optimum level (18-24 °C) for 94.50% time of the experimental measurements. In addition, the indoor air quality in the context of the content of harmful volatile organic compounds (VOCs) has been excellent for almost 91% time of the total experiment. However, the values of relative humidity were less than the optimum value nearly 40% of the total observed time. The mean 10-minutes values of relative humidity during the heating season is about 10% lower than the mean 10-minutes relative humidity before the heating season.
NASA Technical Reports Server (NTRS)
Shuman, Christopher A.; Hall, Dorothy K.; DiGirolamo, Nicolo E.; Mefford, Thomas K.; Schnaubelt, Michael J.
2014-01-01
We have investigated the stability of the MODerate resolution Imaging Spectroradiometer (MODIS) infrared-derived ice surface temperature (IST) data from Terra for use as a climate quality data record. The availability of climate quality air temperature data (TA) from a NOAA Global Monitoring Division observatory at Greenlands Summit station has enabled this high temporal resolution study of MODIS ISTs. During a 5 year period (July 2008 to August 2013), more than 2500 IST values were compared with 3-minute average TA values derived from the 1-minute data from NOAAs primary 2 m air temperature sensor. These data enabled an expected small offset between air and surface temperatures at this the ice sheet location to be investigated over multiple annual cycles.
Sensor-Web Operations Explorer
NASA Technical Reports Server (NTRS)
Meemong, Lee; Miller, Charles; Bowman, Kevin; Weidner, Richard
2008-01-01
Understanding the atmospheric state and its impact on air quality requires observations of trace gases, aerosols, clouds, and physical parameters across temporal and spatial scales that range from minutes to days and from meters to more than 10,000 kilometers. Observations include continuous local monitoring for particle formation; field campaigns for emissions, local transport, and chemistry; and periodic global measurements for continental transport and chemistry. Understanding includes global data assimilation framework capable of hierarchical coupling, dynamic integration of chemical data and atmospheric models, and feedback loops between models and observations. The objective of the sensor-web system is to observe trace gases, aerosols, clouds, and physical parameters, an integrated observation infrastructure composed of space-borne, air-borne, and in-situ sensors will be simulated based on their measurement physics properties. The objective of the sensor-web operation is to optimally plan for heterogeneous multiple sensors, the sampling strategies will be explored and science impact will be analyzed based on comprehensive modeling of atmospheric phenomena including convection, transport, and chemical process. Topics include system architecture, software architecture, hardware architecture, process flow, technology infusion, challenges, and future direction.
Classification of buildings mold threat using electronic nose
NASA Astrophysics Data System (ADS)
Łagód, Grzegorz; Suchorab, Zbigniew; Guz, Łukasz; Sobczuk, Henryk
2017-07-01
Mold is considered to be one of the most important features of Sick Building Syndrome and is an important problem in current building industry. In many cases it is caused by the rising moisture of building envelopes surface and exaggerated humidity of indoor air. Concerning historical buildings it is mostly caused by outdated raising techniques among that is absence of horizontal isolation against moisture and hygroscopic materials applied for construction. Recent buildings also suffer problem of mold risk which is caused in many cases by hermetization leading to improper performance of gravitational ventilation systems that make suitable conditions for mold development. Basing on our research there is proposed a method of buildings mold threat classification using electronic nose, based on a gas sensors array which consists of MOS sensors (metal oxide semiconductor). Used device is frequently applied for air quality assessment in environmental engineering branches. Presented results show the interpretation of e-nose readouts of indoor air sampled in rooms threatened with mold development in comparison with clean reference rooms and synthetic air. Obtained multivariate data were processed, visualized and classified using a PCA (Principal Component Analysis) and ANN (Artificial Neural Network) methods. Described investigation confirmed that electronic nose - gas sensors array supported with data processing enables to classify air samples taken from different rooms affected with mold.
Salamone, Francesco; Belussi, Lorenzo; Danza, Ludovico; Galanos, Theodore; Ghellere, Matteo; Meroni, Italo
2017-05-04
The article describes the results of the project "open source smart lamp" aimed at designing and developing a smart object able to manage and control the indoor environmental quality (IEQ) of the built environment. A first version of this smart object, built following a do-it-yourself (DIY) approach using a microcontroller, an integrated temperature and relative humidity sensor, and techniques of additive manufacturing, allows the adjustment of the indoor thermal comfort quality (ICQ), by interacting directly with the air conditioner. As is well known, the IEQ is a holistic concept including indoor air quality (IAQ), indoor lighting quality (ILQ) and acoustic comfort, besides thermal comfort. The upgrade of the smart lamp bridges the gap of the first version of the device providing the possibility of interaction with the air exchange unit and lighting system in order to get an overview of the potential of a nearable device in the management of the IEQ. The upgraded version was tested in a real office equipped with mechanical ventilation and an air conditioning system. This office was occupied by four workers. The experiment is compared with a baseline scenario and the results show how the application of the nearable device effectively optimizes both IAQ and ILQ.
Salamone, Francesco; Belussi, Lorenzo; Danza, Ludovico; Galanos, Theodore; Ghellere, Matteo; Meroni, Italo
2017-01-01
The article describes the results of the project “open source smart lamp” aimed at designing and developing a smart object able to manage and control the indoor environmental quality (IEQ) of the built environment. A first version of this smart object, built following a do-it-yourself (DIY) approach using a microcontroller, an integrated temperature and relative humidity sensor, and techniques of additive manufacturing, allows the adjustment of the indoor thermal comfort quality (ICQ), by interacting directly with the air conditioner. As is well known, the IEQ is a holistic concept including indoor air quality (IAQ), indoor lighting quality (ILQ) and acoustic comfort, besides thermal comfort. The upgrade of the smart lamp bridges the gap of the first version of the device providing the possibility of interaction with the air exchange unit and lighting system in order to get an overview of the potential of a nearable device in the management of the IEQ. The upgraded version was tested in a real office equipped with mechanical ventilation and an air conditioning system. This office was occupied by four workers. The experiment is compared with a baseline scenario and the results show how the application of the nearable device effectively optimizes both IAQ and ILQ. PMID:28471398
The UniTec Sens-It is a small gas-sensing device that can measure volatile organic compounds (VOCs). This sensor is used to measure VOCs in applications such as urban air quality, roadside pollution, and (solid waste) landfill monitoring. This operating procedure explains what yo...
Breathable and Stretchable Temperature Sensors Inspired by Skin
NASA Astrophysics Data System (ADS)
Chen, Ying; Lu, Bingwei; Chen, Yihao; Feng, Xue
2015-06-01
Flexible electronics attached to skin for healthcare, such as epidermal electronics, has to struggle with biocompatibility and adapt to specified environment of skin with respect to breath and perspiration. Here, we report a strategy for biocompatible flexible temperature sensors, inspired by skin, possessing the excellent permeability of air and high quality of water-proof by using semipermeable film with porous structures as substrate. We attach such temperature sensors to underarm and forearm to measure the axillary temperature and body surface temperature respectively. The volunteer wears such sensors for 24 hours with two times of shower and the in vitro test shows no sign of maceration or stimulation to the skin. Especially, precise temperature changes on skin surface caused by flowing air and water dropping are also measured to validate the accuracy and dynamical response. The results show that the biocompatible temperature sensor is soft and breathable on the human skin and has the excellent accuracy compared to mercury thermometer. This demonstrates the possibility and feasibility of fully using the sensors in long term body temperature sensing for medical use as well as sensing function of artificial skin for robots or prosthesis.
Breathable and Stretchable Temperature Sensors Inspired by Skin
Chen, Ying; Lu, Bingwei; Chen, Yihao; Feng, Xue
2015-01-01
Flexible electronics attached to skin for healthcare, such as epidermal electronics, has to struggle with biocompatibility and adapt to specified environment of skin with respect to breath and perspiration. Here, we report a strategy for biocompatible flexible temperature sensors, inspired by skin, possessing the excellent permeability of air and high quality of water-proof by using semipermeable film with porous structures as substrate. We attach such temperature sensors to underarm and forearm to measure the axillary temperature and body surface temperature respectively. The volunteer wears such sensors for 24 hours with two times of shower and the in vitro test shows no sign of maceration or stimulation to the skin. Especially, precise temperature changes on skin surface caused by flowing air and water dropping are also measured to validate the accuracy and dynamical response. The results show that the biocompatible temperature sensor is soft and breathable on the human skin and has the excellent accuracy compared to mercury thermometer. This demonstrates the possibility and feasibility of fully using the sensors in long term body temperature sensing for medical use as well as sensing function of artificial skin for robots or prosthesis. PMID:26095941
NASA Astrophysics Data System (ADS)
Nowlan, C. R.; Liu, X.; Janz, S. J.; Leitch, J. W.; Al-Saadi, J. A.; Chance, K.; Cole, J.; Delker, T.; Follette-Cook, M. B.; Gonzalez Abad, G.; Good, W. S.; Kowalewski, M. G.; Loughner, C.; Pickering, K. E.; Ruppert, L.; Soo, D.; Szykman, J.; Valin, L.; Zoogman, P.
2016-12-01
The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) and the GEO-CAPE Airborne Simulator (GCAS) instruments are pushbroom sensors capable of making remote sensing measurements of air quality and ocean color. Originally developed as test-bed instruments for the Geostationary Coastal and Air Pollution Events (GEO-CAPE) decadal survey, these instruments are now also part of risk reduction for the upcoming Tropospheric Emissions: Monitoring of Pollution (TEMPO) and Geostationary Environment Monitoring Spectrometer (GEMS) geostationary satellite missions, and will provide validation capabilities after the satellite instruments are in orbit. GeoTASO and GCAS flew on two different aircraft in their first intensive air quality field campaigns during the DISCOVER-AQ missions over Texas in 2013 and Colorado in 2014. GeoTASO was also deployed in 2016 during the KORUS-AQ field campaign to make measurements of trace gases and aerosols over Korea. GeoTASO and GCAS collect spectra of backscattered solar radiation in the UV and visible that can be used to derive 2-D maps of trace gas columns below the aircraft at spatial resolutions on the order of 250 x 500 m. We present spatially resolved maps of trace gas retrievals of ozone, nitrogen dioxide, formaldehyde and sulfur dioxide over urban areas and power plants from flights during the field campaigns, and comparisons with data from ground-based spectrometers, in situ monitoring instruments, and satellites.
Long-Term Stability of Oxide Nanowire Sensors via Heavily Doped Oxide Contact.
Zeng, Hao; Takahashi, Tsunaki; Kanai, Masaki; Zhang, Guozhu; He, Yong; Nagashima, Kazuki; Yanagida, Takeshi
2017-12-22
Long-term stability of a chemical sensor is an essential quality for long-term collection of data related to exhaled breath, environmental air, and other sources in the Internet of things (IoT) era. Although an oxide nanowire sensor has shown great potential as a chemical sensor, the long-term stability of sensitivity has not been realized yet due to electrical degradation under harsh sensing conditions. Here, we report a rational concept to accomplish long-term electrical stability of metal oxide nanowire sensors via introduction of a heavily doped metal oxide contact layer. Antimony-doped SnO 2 (ATO) contacts on SnO 2 nanowires show much more stable and lower electrical contact resistance than conventional Ti contacts for high temperature (200 °C) conditions, which are required to operate chemical sensors. The stable and low contact resistance of ATO was confirmed for at least 1960 h under 200 °C in open air. This heavily doped oxide contact enables us to realize the long-term stability of SnO 2 nanowire sensors while maintaining the sensitivity for both NO 2 gas and light (photo) detections. The applicability of our method is confirmed for sensors on a flexible polyethylene naphthalate (PEN) substrate. Since the proposed fundamental concept can be applied to various oxide nanostructures, it will give a foundation for designing long-term stable oxide nanomaterial-based IoT sensors.
NASA Technical Reports Server (NTRS)
Gregory, G. L.; Mcdougal, D. S.; Mathis, J. J., Jr.
1980-01-01
Ozone data from the 1979 Southeastern Virginia Urban Study (SEV-UPS) field program are presented. The SEV-UPS was conducted for evaluation of an ozone remote sensor, the Laser Absorption Spectrometer. During the measurement program, remote-sensor evaluation was in two areas; (1) determination of the remote sensor's accuracy, repeatability, and operational characteristics, and (2) demonstration of the application of remotely sensed ozone data in air-quality studies. Data from six experiments designed to provide in situ ozone data for evaluation of the sensor in area 1, above, are presented. Experiments consisted of overflights of a test area with the remote sensor aircraft while in situ measurements with a second aircraft and selected surface stations provided correlative ozone data within the viewing area of the remote sensor.
Use of the JPL Electronic Nose to detect leaks and spills in an enclosed environment
NASA Technical Reports Server (NTRS)
Ryan, Margaret A.; Homer, M. L.; Zhou, H.; Pelletier, C. C.; Manatt, K.; Jewell, A. D.; Kisor, A.; Shevade, A. V.; Lewis, C. R.; Taylor, C. J.;
2006-01-01
An electronic nose to be used as an air quality monitor in human habitats in space has been developed at the Jet Propulsion Laboratory. This device is capable of detecting, identifying and quantifying several organic and inorganic chemical species which might be present as contaminants in spacecraft air. The complete portable device, including sensors, electronics, and software for data analysis, has been extensively tested.
Solution to the Problem of Calibration of Low-Cost Air Quality Measurement Sensors in Networks.
Miskell, Georgia; Salmond, Jennifer A; Williams, David E
2018-04-27
We provide a simple, remote, continuous calibration technique suitable for application in a hierarchical network featuring a few well-maintained, high-quality instruments ("proxies") and a larger number of low-cost devices. The ideas are grounded in a clear definition of the purpose of a low-cost network, defined here as providing reliable information on air quality at small spatiotemporal scales. The technique assumes linearity of the sensor signal. It derives running slope and offset estimates by matching mean and standard deviations of the sensor data to values derived from proxies over the same time. The idea is extremely simple: choose an appropriate proxy and an averaging-time that is sufficiently long to remove the influence of short-term fluctuations but sufficiently short that it preserves the regular diurnal variations. The use of running statistical measures rather than cross-correlation of sites means that the method is robust against periods of missing data. Ideas are first developed using simulated data and then demonstrated using field data, at hourly and 1 min time-scales, from a real network of low-cost semiconductor-based sensors. Despite the almost naïve simplicity of the method, it was robust for both drift detection and calibration correction applications. We discuss the use of generally available geographic and environmental data as well as microscale land-use regression as means to enhance the proxy estimates and to generalize the ideas to other pollutants with high spatial variability, such as nitrogen dioxide and particulates. These improvements can also be used to minimize the required number of proxy sites.
The Improvement of Spatial-Temporal PM2.5 Resolution in Taiwan by Using Data Assimilation Method
NASA Astrophysics Data System (ADS)
Lin, Yong-Qing; Lin, Yuan-Chien
2017-04-01
Forecasting air pollution concentration, e.g., the concentration of PM2.5, is of great significance to protect human health and the environment. Accurate prediction of PM2.5 concentrations is limited in number and the data quality of air quality monitoring stations. The spatial and temporal variations of PM2.5 concentrations are measured by 76 National Air Quality Monitoring Stations (built by the TW-EPA) in Taiwan. The National Air Quality Monitoring Stations are costly and scarce because of the highly precise instrument and their size. Therefore, many places still out of the range of National Air Quality Monitoring Stations. Recently, there are an enormous number of portable air quality sensors called "AirBox" developed jointly by the Taiwan government and a private company. By virtue of its price and portative, the AirBox can provide higher resolution of space-time PM2.5 measurement. However, the spatiotemporal distribution and data quality are different between AirBox and National Air Quality Monitoring Stations. To integrate the heterogeneous PM2.5 data, the data assimilation method should be performed before further analysis. In this study, we propose a data assimilation method based on Ensemble Kalman Filter (EnKF), which is a variant of classic Kalman Filter, can be used to combine additional heterogeneous data from different source while modeling to improve the estimation of spatial-temporal PM2.5 concentration. The assimilation procedure uses the advantages of the two kinds of heterogeneous data and merges them to produce the final estimation. The results have shown that by combining AirBox PM2.5 data as additional information in our model based EnKF can bring the better estimation of spatial-temporal PM2.5 concentration and improve the it's space-time resolution. Under the approach proposed in this study, higher spatial-temporal resoultion could provide a very useful information for a better spatial-temporal data analysis and further environmental management, such as air pollution source localization and micro-scale air pollution analysis. Keywords: PM2.5, Data Assimilation, Ensemble Kalman Filter, Air Quality
A Context-Aware Indoor Air Quality System for Sudden Infant Death Syndrome Prevention
De Paz, Juan F.; Barriuso, Alberto L.
2018-01-01
Context-aware monitoring systems designed for e-Health solutions and ambient assisted living (AAL) play an important role in today’s personalized health-care services. The majority of these systems are intended for the monitoring of patients’ vital signs by means of bio-sensors. At present, there are very few systems that monitor environmental conditions and air quality in the homes of users. A home’s environmental conditions can have a significant influence on the state of the health of its residents. Monitoring the environment is the key to preventing possible diseases caused by conditions that do not favor health. This paper presents a context-aware system that monitors air quality to prevent a specific health problem at home. The aim of this system is to reduce the incidence of the Sudden Infant Death Syndrome, which is triggered mainly by environmental factors. In the conducted case study, the system monitored the state of the neonate and the quality of air while it was asleep. The designed proposal is characterized by its low cost and non-intrusive nature. The results are promising. PMID:29498653
A Context-Aware Indoor Air Quality System for Sudden Infant Death Syndrome Prevention.
De La Iglesia, Daniel H; De Paz, Juan F; Villarrubia González, Gabriel; Barriuso, Alberto L; Bajo, Javier
2018-03-02
Context-aware monitoring systems designed for e-Health solutions and ambient assisted living (AAL) play an important role in today's personalized health-care services. The majority of these systems are intended for the monitoring of patients' vital signs by means of bio-sensors. At present, there are very few systems that monitor environmental conditions and air quality in the homes of users. A home's environmental conditions can have a significant influence on the state of the health of its residents. Monitoring the environment is the key to preventing possible diseases caused by conditions that do not favor health. This paper presents a context-aware system that monitors air quality to prevent a specific health problem at home. The aim of this system is to reduce the incidence of the Sudden Infant Death Syndrome, which is triggered mainly by environmental factors. In the conducted case study, the system monitored the state of the neonate and the quality of air while it was asleep. The designed proposal is characterized by its low cost and non-intrusive nature. The results are promising.
Warm Dry Weather Conditions Cause of 2016 Fort McMurray Wild Forest Fire and Associated Air Quality
NASA Astrophysics Data System (ADS)
de Azevedo, S. C.; Singh, R. P.; da Silva, E. A., Sr.
2016-12-01
The climate change is evident from the increasing temperature around the world, day to day life and increasing frequency of natural hazards. The warm and dry conditions are the cause of frequent forest fires around the globe. Forest fires severely affect the air quality and human health. Multi sensor satellites and dense network of ground stations provide information about vegetation health, meteorological, air quality and atmospheric parameters. We have carried out detailed analysis of satellite and ground data of wild forest fire that occurred in May 2016 in Fort McMurray, Alberta, Canada. This wild forest fire destroyed 10 per cent of Fort McMurray's housing and forced more than 90,000 people to evacuate the surrounding areas. Our results show that the warm and dry conditions with low rainfall were the cause of Fort McMurray wild fire. The air quality parameters (particulate matter, CO, ozone, NO2, methane) and greenhouse gases measured from Atmospheric Infrared Sounder (AIRS) satellite show enhanced levels soon after the forest fire. The emissions from the forest fire affected health of population living in surrounding areas up to 300 km radius.
NASA Astrophysics Data System (ADS)
Dominguez, A.; Kleissl, J.; Farhadi, M.; Kim, D.; Liu, W.; Mao, Y.; Nguyen, H. T.; Roshandell, M.; Sankur, M.; Shiga, Y.; Linden, P.; Hodgkiss, W.
2007-12-01
Meteorological conditions have important implications on human activities. They affect human comfort, productivity, and health, and contribute to material wear and tear. The University of California, San Diego (UCSD)'s proximity to the Pacific Ocean places it in a temperate microclimate which has unique advantages and disadvantages for campus water and energy use and air quality. In particular, the daily sea-breezes provide cool, moist, and salt-laden air to campus. For the Decision-Making Using Real-Time Observations for Environmental Sustainability (DEMROES) project a heterogeneous wireless network of monitoring stations is being set up across the UCSD campus and beyond. Conditions to be monitored include temperature, humidity, wind speed and direction, surface temperatures, solar radiation, particulate matter, CO, NO2, rainfall, and soil moisture. Stations are strategically placed on rooftops and lampposts across campus, as well as select off-campus locations and will transmit data over the UCSD 802.11 wireless network. In addition to rooftop and lamppost stations, mobile stations will be deployed via remotely controlled ground and air units, and stations affixed to campus shuttle busses. These mobile stations will allow for greater spatial resolution of the environmental conditions across campus and inter-sensor calibration. The hardware consists of meteorological, hydrological, and air quality sensors connected to (a) commercial Campbell datalogging systems with serial2IP modules and wireless bridges, and (b) sensor and 802.11 boards based on the dpac technology developed in-house. The measurements will serve campus facilities management with information to feed the energy management system (EMS) for building operation and energy conservation, and irrigation management. The technology developed for this project can be applied elsewhere thereby contributing to hydrologic and ecologic observatories. Through extensive student involvement a new generation of environmental scientists and engineers will be trained to work on the planning and execution of national observatories.
2017-01-01
We report a light, flexible, and low-power poly(ionic liquid)/alumina composite CO2 sensor. We monitor the direct-current resistance changes as a function of CO2 concentration and relative humidity and demonstrate fast and reversible sensing kinetics. Moreover, on the basis of the alternating-current impedance measurements we propose a sensing mechanism related to proton conduction and gas diffusion. The findings presented herein will promote the development of organic/inorganic composite CO2 gas sensors. In the future, such sensors will be useful for numerous practical applications ranging from indoor air quality control to the monitoring of manufacturing processes. PMID:28726384
Lu, Chia Jung; Jin, Chunguang; Zellers, Edward T
2006-02-01
The evaluation of a novel prototype instrument designed for on-site determinations of VOC mixtures found in indoor working environments is described. The instrument contains a miniature multi-stage preconcentrator, a dual-column separation module with pressure-tunable retention capabilities, and an integrated array of three polymer-coated surface acoustic wave sensors. It was challenged with dynamic test-atmospheres of a set of 15 common indoor air contaminants at parts-per-billion concentrations within a stainless-steel chamber under a range of conditions. Vapours were reliably identified at a known level of confidence by combining column retention times with sensor-array response patterns and applying a multivariate statistical test of pattern fidelity for the chromatographically resolved vapours. Estimates of vapour concentrations fell within 7% on average of those determined by EPA Method TO-17, and limits of detection ranged from 0.2 to 28 ppb at 25 degrees C for 1 L samples collected and analyzed in <12 min. No significant humidity effects were observed (0-90% RH). Increasing the chamber temperature from 25 to 30 degrees C reduced the retention times of the more volatile analytes which, in turn, demanded alterations in the scheduling of column-junction-point pressure (flow) modulations performed during the analysis. Reductions in sensor sensitivities with increasing temperature were predictable and similar among the sensors in the array such that most response patterns were not altered significantly. Short-term fluctuations in concentration were accurately tracked by the instrument. Results indicate that this type of instrument could provide routine, semi-autonomous, near-real-time, multi-vapour monitoring in support of efforts to assess air quality in office environments.
Development of a Personal Integrated Environmental Monitoring System
Wong, Man Sing; Yip, Tsan Pong; Mok, Esmond
2014-01-01
Environmental pollution in the urban areas of Hong Kong has become a serious public issue but most urban inhabitants have no means of judging their own living environment in terms of dangerous threshold and overall livability. Currently there exist many low-cost sensors such as ultra-violet, temperature and air quality sensors that provide reasonably accurate data quality. In this paper, the development and evaluation of Integrated Environmental Monitoring System (IEMS) are illustrated. This system consists of three components: (i) position determination and sensor data collection for real-time geospatial-based environmental monitoring; (ii) on-site data communication and visualization with the aid of an Android-based application; and (iii) data analysis on a web server. This system has shown to be working well during field tests in a bus journey and a construction site. It provides an effective service platform for collecting environmental data in near real-time, and raises the public awareness of environmental quality in micro-environments. PMID:25420154
Air Quality Study Using Satellites - Current Capability and Future Plans
NASA Technical Reports Server (NTRS)
Bhartia, Pawan K.; Joiner, Joanna; Gleason, James; Liu, Xiong; Torres, Omar; Krotkov, Nickolay; Ziemke, Jerry; Chandra, Sushil
2008-01-01
Satellite instruments have had great success in monitoring the stratospheric ozone and in understanding the processes that control its daily to decadal scale variations. This field is now reaching its zenith with a number of satellite instruments from the US, Europe and Canada capping several decades of active research in this field. The primary public policy imperative of this research was to make reliable prediction of increases in biologically active surface UV radiation due to human activity. By contrast retrieval from satellite data of atmospheric constituents and photo-chemically active radiation that affect air quality is a new and growing field that is presenting us with unique challenges in measurement and data interpretation. A key distinction compared to stratospheric sensors is the greatly enhanced role of clouds, aerosols, and surfaces (CAS) in determining the quality and quantity of useful data that is available for air quality research. In our presentation we will use data from several sensors that are currently flying on the A-train satellite constellation, including OMI, MODIS, CLOUDSAT, and CALIPSO, to highlight that CAS can have both positive and negative effects on the information content of satellite measurements. This is in sharp contrast to other fields of remote sensing where CAS are usually considered an interference except in those cases when they are the primary subject of study. Our analysis has revealed that in the reflected wavelengths one often sees much further down into the atmosphere, through most cirrus, than one does in the emitted wavelengths. The lower level clouds provide a nice background against which one can track long-range transport of trace gases and aerosols. In addition, differences in trace gas columns estimated over cloudy and adjacent clear pixels can be used to measure boundary layer trace gases. However, in order to take full advantage of these features it will be necessary to greatly advance our understanding of how CAS affect the radiation at wavelengths that are used to derive the atmospheric constituents that affect air quality as well as the radiation that controls the photolysis of chemically active trace gases. We will discuss how we are using these new insights to design future satellite missions to study air quality.
NASA Astrophysics Data System (ADS)
Augere, B.; Besson, B.; Fleury, D.; Goular, D.; Planchat, C.; Valla, M.
2016-05-01
Lidar (light detection and ranging) is a well-established measurement method for the prediction of atmospheric motions through velocity measurements. Recent advances in 1.5 μm Lidars show that the technology is mature, offers great ease of use, and is reliable and compact. A 1.5 μm airborne Lidar appears to be a good candidate for airborne in-flight measurement systems. It allows measurements remotely, outside aircraft aerodynamic disturbance, and absolute air speed (no need for calibration) with great precision in all aircraft flight domains. In the framework of the EU AIM2 project, the ONERA task has consisted of developing and testing a 1.5 μm anemometer sensor for in-flight airspeed measurements. The objective of this work is to demonstrate that the 1.5 μm Lidar sensor can increase the quality of the data acquisition procedure for aircraft flight test certification. This article presents the 1.5 μm anemometer sensor dedicated to in-flight airspeed measurements and describes the flight tests performed successfully on-board the Piaggio P180 aircraft. Lidar air data have been graphically compared to the air data provided by the aircraft flight test instrumentation (FTI) in the reference frame of the Lidar sensor head. Very good agreement of true air speed (TAS) by a fraction of ms-1, angle of sideslip (AOS), and angle of attack (AOA) by a fraction of degree were observed.
The State of Sensor Technology and Air Quality Monitoring
Produces data of known value and highly reliableStationary- cannot be easily relocatedInstruments are often large and require a building to support their operationExpensive to purchase and operate (typically > $20K each)Requires frequent visits by highly trained staff to check on...
Peterson, Philip J. D.; Aujla, Amrita; Brundle, Alex G.; Thompson, Martin R.; Vande Hey, Josh; Leigh, Roland J.
2017-01-01
The potential of inexpensive Metal Oxide Semiconductor (MOS) gas sensors to be used for urban air quality monitoring has been the topic of increasing interest in the last decade. This paper discusses some of the lessons of three years of experience working with such sensors on a novel instrument platform (Small Open General purpose Sensor (SOGS)) in the measurement of atmospheric nitrogen dioxide and ozone concentrations. Analytic methods for increasing long-term accuracy of measurements are discussed, which permit nitrogen dioxide measurements with 95% confidence intervals of 20.0 μg m−3 and ozone precision of 26.8 μg m−3, for measurements over a period one month away from calibration, averaged over 18 months of such calibrations. Beyond four months from calibration, sensor drift becomes significant, and accuracy is significantly reduced. Successful calibration schemes are discussed with the use of controlled artificial atmospheres complementing deployment on a reference weather station exposed to the elements. Manufacturing variation in the attributes of individual sensors are examined, an experiment possible due to the instrument being equipped with pairs of sensors of the same kind. Good repeatability (better than 0.7 correlation) between individual sensor elements is shown. The results from sensors that used fans to push air past an internal sensor element are compared with mounting the sensors on the outside of the enclosure, the latter design increasing effective integration time to more than a day. Finally, possible paths forward are suggested for improving the reliability of this promising sensor technology for measuring pollution in an urban environment. PMID:28753910
Peterson, Philip J D; Aujla, Amrita; Grant, Kirsty H; Brundle, Alex G; Thompson, Martin R; Vande Hey, Josh; Leigh, Roland J
2017-07-19
The potential of inexpensive Metal Oxide Semiconductor (MOS) gas sensors to be used for urban air quality monitoring has been the topic of increasing interest in the last decade. This paper discusses some of the lessons of three years of experience working with such sensors on a novel instrument platform (Small Open General purpose Sensor (SOGS)) in the measurement of atmospheric nitrogen dioxide and ozone concentrations. Analytic methods for increasing long-term accuracy of measurements are discussed, which permit nitrogen dioxide measurements with 95% confidence intervals of 20.0 μ g m - 3 and ozone precision of 26.8 μ g m - 3 , for measurements over a period one month away from calibration, averaged over 18 months of such calibrations. Beyond four months from calibration, sensor drift becomes significant, and accuracy is significantly reduced. Successful calibration schemes are discussed with the use of controlled artificial atmospheres complementing deployment on a reference weather station exposed to the elements. Manufacturing variation in the attributes of individual sensors are examined, an experiment possible due to the instrument being equipped with pairs of sensors of the same kind. Good repeatability (better than 0.7 correlation) between individual sensor elements is shown. The results from sensors that used fans to push air past an internal sensor element are compared with mounting the sensors on the outside of the enclosure, the latter design increasing effective integration time to more than a day. Finally, possible paths forward are suggested for improving the reliability of this promising sensor technology for measuring pollution in an urban environment.
Planetary Boundary Layer Dynamics over Reno, Nevada in Summer
NASA Astrophysics Data System (ADS)
Liming, A.; Sumlin, B.; Loria Salazar, S. M.; Holmes, H.; Arnott, W. P.
2014-12-01
Quantifying the height of the planetary boundary layer (PBL) is important to understand the transport behavior, mixing, and surface concentrations of air pollutants. In Reno, NV, located in complex, mountainous terrain with high desert climate, the daytime boundary layer can rise to an estimated 3km or more on a summer day due to surface heating and convection. The nocturnal boundary layer, conversely, tends to be much lower and highly stable due to radiative cooling from the surface at night and downslope flow of cool air from nearby mountains. With limited availability of radiosonde data, current estimates of the PBL height at any given time or location are potentially over or underestimated. To better quantify the height and characterize the PBL physics, we developed portable, lightweight sensors that measure CO2 concentrations, temperature, pressure, and humidity every 5 seconds. Four of these sensors are used on a tethered balloon system to monitor CO2 concentrations from the surface up to 300m. We will combine this data with Radio Acoustic Sounding System (RASS) data that measures vertical profiles of wind speed, temperature, and humidity from 40m to 400m. This experiment will characterize the diurnal evolution of CO2 concentrations at multiple heights in the PBL, provide insight into PBL physics during stability transition periods at sunrise and sunset, and estimate the nighttime PBL depth during August in Reno. Further, we expect to gain a better understanding of the impact of mixing volume changes (i.e., PBL height) on air quality and pollution concentrations in Reno. The custom portable sensor design will also be presented. It is expected that these instruments can be used for indoor or outdoor air quality studies, where lightness, small size, and battery operation can be of benefit.
Sensor-based demand controlled ventilation
DOE Office of Scientific and Technical Information (OSTI.GOV)
De Almeida, A.T.; Fisk, W.J.
In most buildings, occupancy and indoor pollutant emission rates vary with time. With sensor-based demand-controlled ventilation (SBDCV), the rate of ventilation (i.e., rate of outside air supply) also varies with time to compensate for the changes in pollutant generation. In other words, SBDCV involves the application of sensing, feedback and control to modulate ventilation. Compared to ventilation without feedback, SBDCV offers two potential advantages: (1) better control of indoor pollutant concentrations; and (2) lower energy use and peak energy demand. SBDCV has the potential to improve indoor air quality by increasing the rate of ventilation when indoor pollutant generation ratesmore » are high and occupants are present. SBDCV can also save energy by decreasing the rate of ventilation when indoor pollutant generation rates are low or occupants are absent. After providing background information on indoor air quality and ventilation, this report provides a relatively comprehensive discussion of SBDCV. Topics covered in the report include basic principles of SBDCV, sensor technologies, technologies for controlling air flow rates, case studies of SBDCV, application of SBDCV to laboratory buildings, and research needs. SBDCV appears to be an increasingly attractive technology option. Based on the review of literature and theoretical considerations, the application of SBDCV has the potential to be cost-effective in applications with the following characteristics: (a) a single or small number of dominant pollutants, so that ventilation sufficient to control the concentration of the dominant pollutants provides effective control of all other pollutants; (b) large buildings or rooms with unpredictable temporally variable occupancy or pollutant emission; and (c) climates with high heating or cooling loads or locations with expensive energy.« less
Temporal variation of indoor air quality in an enclosed swine confinement building.
O'Shaughnessy, P T; Achutan, C; Karsten, A W
2002-11-01
Human health hazards can exist in swine confinement buildings due to poor indoor air quality (IAQ). During this study, airborne dust and ammonia concentrations were monitored within a working farrowing facility as indicators of IAQ. The purposes of this study were to assess the temporal variability of the airborne dust and ammonia levels over both a daily and seasonal basis, and to determine the accuracy of real-time sensors relative to actively sampled data. An ammonia sensor, aerosol photometer, indoor relative humidity sensor, and datalogger containing an indoor temperature sensor were mounted on a board 180 cm above the floor in the center of a room in the facility. Sensor readings were taken once every 4 minutes during animal occupancy (3-week intervals). Measurements of total and respirable dust concentrations by standard method, aerosol size distribution, and ammonia concentrations were taken once per week, in addition to temperature and relative humidity measurements using a thermometer and sling psychrometer, respectively. Samples were taken between September 1999 and August 2000. Diurnal variations in airborne dust revealed an inverse relationship with changes in indoor temperature and, by association, changes in airflow rate. Ammonia levels changed despite relatively stable internal temperatures. This change may be related to both changes in flow rates and in volatility rates. As expected, contaminant concentrations increased during the cold weather months, but these differences were not significantly different from other seasons. However, total dust concentrations were very low (geometric mean = 0.8 mg/m3) throughout the year. Likewise, ammonia concentrations averaged only 3.6 ppm in the well-maintained study site.
INFLUENCE OF RESIDENTIAL HVAC DUTY CYCLE ON INDOOR AIR QUALITY
Measurements of duty cycle, the fraction of time the heating and cooling (HVAC) system was operating, were made in homes during the spring season of the RTP Particulate Matter Panel Study and the Tampa Asthmatic Children's Study. A temperature sensor/logger placed on an outlet...
Huck, J J; Whyatt, J D; Coulton, P; Davison, B; Gradinar, A
2017-03-01
This work investigates the potential of combining the outputs of multiple low-cost sensor technologies for the direct measurement of spatio-temporal variations in phenomena that exist at the interface between our bodies and the environment. The example used herein is the measurement of personal exposure to traffic pollution, which may be considered as a function of the concentration of pollutants in the air and the frequency and volume of that air which enters our lungs. The sensor-based approach described in this paper removes the 'traditional' requirements either to model or interpolate pollution levels or to make assumptions about the physiology of an individual. Rather, a wholly empirical analysis into pollution exposure is possible, based upon high-resolution spatio-temporal data drawn from sensors for NO 2 , nasal airflow and location (GPS). Data are collected via a custom smartphone application and mapped to give an unprecedented insight into exposure to traffic pollution at the individual level. Whilst the quality of data from low-cost miniaturised sensors is not suitable for all applications, there certainly are many applications for which these data would be well suited, particularly those in the field of citizen science. This paper demonstrates both the potential and limitations of sensor-based approaches and discusses the wider relevance of these technologies for the advancement of citizen science.
A Combustion Products Analyzer for contingency use during thermodegradation events on spacecraft
NASA Technical Reports Server (NTRS)
Limero, Thomas; James, John T.; Beck, Steven; Cromer, Raymond
1991-01-01
This paper will describe the Combustion Products Analyzer (CPA), which is being developed under the direction of the Toxicology Laboratory at Johnson Space Center to provide necessary data on air quality in the Shuttle following a thermodegradation incident. Using separate electrochemical sensors, the CPA monitors four gases (hydrogen fluoride/carbonyl fluoride, hydrogen chloride, hydrogen cyanide, and carbon monoxide), which were selected as the most hazardous compounds likely to be released during thermodegradation of synthetic materials. Electrochemical sensors have been available for several years; the CPA sensors, which are unique because of their small size and zero-gravity compatibility, will be described in detail.
Work on power-plant (air) plumes involving remote sensing of SO2
NASA Technical Reports Server (NTRS)
White, C. L., Jr.
1978-01-01
Acquisition of air quality and concurrent meteorological data was used for dispersion model development and plant siting needs of the Maryland power plants. One of the major instruments in these studies was the Barringer correlation spectrometer, a remote sensor, using atmospherically scattered sunlight that was used to measure the total amount of SO2 in a cross section of the plume. Correlation spectrometer and its role in this measurement program are described.
Development of a Data Acquisition System for Unmanned Aerial Vehicle (UAV) System Identification
NASA Astrophysics Data System (ADS)
Lear, Donald Joseph
Aircraft system identification techniques are developed for fixed wing Unmanned Aerial Vehicles (UAV). The use of a designed flight experiment with measured system inputs/outputs can be used to derive aircraft stability derivatives. This project set out to develop a methodology to support an experiment to model pitch damping in the longitudinal short-period mode of a UAV. A Central Composite Response Surface Design was formed using angle of attack and power levels as factors to test for the pitching moment coefficient response induced by a multistep pitching maneuver. Selecting a high-quality data acquisition platform was critical to the success of the project. This system was designed to support fixed wing research through the addition of a custom air data vane capable of measuring angle of attack and sideslip, as well as an airspeed sensor. A Pixhawk autopilot system serves as the core and modification of the device firmware allowed for the integration of custom sensors and custom RC channels dedicated to performing system identification maneuvers. Tests were performed on all existing Pixhawk sensors to validate stated uncertainty values. The air data system was calibrated in a low speed wind tunnel and dynamic performance was verified. The assembled system was then installed in a commercially available UAV known as an Air Titan FPV in order to test the Pixhawk's automated flight maneuvers and determine the final performance of each sensor. Flight testing showed all the critical sensors produced acceptable data for further research. The Air Titan FPV airframe was found to be very flexible and did not lend itself well to accurate measurement of inertial properties. This realization prohibited the construction of the required math models for longitudinal dynamics. It is recommended that future projects using the developed methods choose an aircraft with a more rigid airframe.
Mobile Air Quality Studies (MAQS)-an international project.
Groneberg, David A; Scutaru, Cristian; Lauks, Mathias; Takemura, Masaya; Fischer, Tanja C; Kölzow, Silvana; van Mark, Anke; Uibel, Stefanie; Wagner, Ulrich; Vitzthum, Karin; Beck, Fabian; Mache, Stefanie; Kreiter, Carolin; Kusma, Bianca; Friedebold, Annika; Zell, Hanna; Gerber, Alexander; Bock, Johanna; Al-Mutawakl, Khaled; Donat, Johannes; Geier, Maria Victoria; Pilzner, Carolin; Welker, Pia; Joachim, Ricarda; Bias, Harald; Götting, Michael; Sakr, Mohannad; Addicks, Johann P; Börger, Julia-Annik; Jensen, Anna-Maria; Grajewski, Sonja; Shami, Awfa; Neye, Niko; Kröger, Stefan; Hoffmann, Sarah; Kloss, Lisa; Mayer, Sebastian; Puk, Clemens; Henkel, Ulrich; Rospino, Robert; Schilling, Ute; Krieger, Evelyn; Westphal, Gesa; Meyer-Falcke, Andreas; Hupperts, Hagen; de Roux, Andrés; Tropp, Salome; Weiland, Marco; Mühlbach, Janette; Steinberg, Johannes; Szerwinski, Anne; Falahkohan, Sepiede; Sudik, Claudia; Bircks, Anna; Noga, Oliver; Dickgreber, Nicolas; Dinh, Q Thai; Golpon, Heiko; Kloft, Beatrix; Groneberg, Rafael Neill B; Witt, Christian; Wicker, Sabine; Zhang, Li; Springer, Jochen; Kütting, Birgitta; Mingomataj, Ervin C; Fischer, Axel; Schöffel, Norman; Unger, Volker; Quarcoo, David
2010-04-09
Due to an increasing awareness of the potential hazardousness of air pollutants, new laws, rules and guidelines have recently been implemented globally. In this respect, numerous studies have addressed traffic-related exposure to particulate matter using stationary technology so far. By contrast, only few studies used the advanced technology of mobile exposure analysis. The Mobile Air Quality Study (MAQS) addresses the issue of air pollutant exposure by combining advanced high-granularity spatial-temporal analysis with vehicle-mounted, person-mounted and roadside sensors. The MAQS-platform will be used by international collaborators in order 1) to assess air pollutant exposure in relation to road structure, 2) to assess air pollutant exposure in relation to traffic density, 3) to assess air pollutant exposure in relation to weather conditions, 4) to compare exposure within vehicles between front and back seat (children) positions, and 5) to evaluate "traffic zone"-exposure in relation to non-"traffic zone"-exposure.Primarily, the MAQS-platform will focus on particulate matter. With the establishment of advanced mobile analysis tools, it is planed to extend the analysis to other pollutants including NO2, SO2, nanoparticles and ozone.
2004-03-06
DC-8 Quality Inspector Scott Silver signs documents while Acting Crew Chief Mike Bereda looks on prior to a DC-8 AirSAR flight in Costa Rica. AirSAR 2004 Mesoamerica is a three-week expedition by an international team of scientists that uses an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR) which is located onboard NASA's DC-8 airborne laboratory. Scientists from many parts of the world including NASA's Jet Propulsion Laboratory are combining ground research done in several areas in Central America with NASA's AirSAR technology to improve and expand on the quality of research they are able to conduct. The radar, developed by NASA's Jet Propulsion Laboratory, can penetrate clouds and also collect data at night. Its high-resolution sensors operate at multiple wavelengths and modes, allowing AirSAR to see beneath treetops, through thin sand, and dry snow pack. AirSAR's 2004 campaign is a collaboration of many U.S. and Central American institutions and scientists, including NASA; the National Science Foundation; the Smithsonian Institution; National Geographic; Conservation International; the Organization of Tropical Studies; the Central American Commission for Environment and Development; and the Inter-American Development Bank.
The CairPol CairClip O3-NO2 is a lightweight, portable sensor for measuring ozone (O3) and nitrogen dioxide (NO2) in parts per billion (ppb) or micrograms per cubic meter (µg/m3) in applications such as personal exposure and indoor and outdoor air quality monitoring. It uses a mi...
Theory of Near-Field Scanning with a Probe Array
2014-01-01
AIR FORCE RESEARCH LABORATORY SENSORS DIRECTORATE WRIGHT-PATTERSON AIR FORCE BASE, OH 45433-7320 AIR FORCE MATERIEL COMMAND...AFRL/RYMH) Sensors Directorate, Air Force Research Laboratory Wright-Patterson Air Force Base, OH 45433-7320 Air Force Materiel Command, United...S) AND ADDRESS(ES) 10. SPONSORING/MONITORING AGENCY ACRONYM(S) Air Force Research Laboratory Sensors Directorate Wright-Patterson Air Force Base
NASA Astrophysics Data System (ADS)
Burk, Laurel M.; Lee, Yueh Z.; Wait, J. Matthew; Lu, Jianping; Zhou, Otto Z.
2012-09-01
A cone beam micro-CT has previously been utilized along with a pressure-tracking respiration sensor to acquire prospectively gated images of both wild-type mice and various adult murine disease models. While the pressure applied to the abdomen of the subject by this sensor is small and is generally without physiological effect, certain disease models of interest, as well as very young animals, are prone to atelectasis with added pressure, or they generate too weak a respiration signal with this method to achieve optimal prospective gating. In this work we present a new fibre-optic displacement sensor which monitors respiratory motion of a subject without requiring physical contact. The sensor outputs an analogue signal which can be used for prospective respiration gating in micro-CT imaging. The device was characterized and compared against a pneumatic air chamber pressure sensor for the imaging of adult wild-type mice. The resulting images were found to be of similar quality with respect to physiological motion blur; the quality of the respiration signal trace obtained using the non-contact sensor was comparable to that of the pressure sensor and was superior for gating purposes due to its better signal-to-noise ratio. The non-contact sensor was then used to acquire in-vivo micro-CT images of a murine model for congenital diaphragmatic hernia and of 11-day-old mouse pups. In both cases, quality CT images were successfully acquired using this new respiration sensor. Despite the presence of beam hardening artefacts arising from the presence of a fibre-optic cable in the imaging field, we believe this new technique for respiration monitoring and gating presents an opportunity for in-vivo imaging of disease models which were previously considered too delicate for established animal handling methods.
The next generation of low-cost personal air quality sensors for quantitative exposure monitoring
NASA Astrophysics Data System (ADS)
Piedrahita, R.; Xiang, Y.; Masson, N.; Ortega, J.; Collier, A.; Jiang, Y.; Li, K.; Dick, R. P.; Lv, Q.; Hannigan, M.; Shang, L.
2014-10-01
Advances in embedded systems and low-cost gas sensors are enabling a new wave of low-cost air quality monitoring tools. Our team has been engaged in the development of low-cost, wearable, air quality monitors (M-Pods) using the Arduino platform. These M-Pods house two types of sensors - commercially available metal oxide semiconductor (MOx) sensors used to measure CO, O3, NO2, and total VOCs, and NDIR sensors used to measure CO2. The MOx sensors are low in cost and show high sensitivity near ambient levels; however they display non-linear output signals and have cross-sensitivity effects. Thus, a quantification system was developed to convert the MOx sensor signals into concentrations. We conducted two types of validation studies - first, deployments at a regulatory monitoring station in Denver, Colorado, and second, a user study. In the two deployments (at the regulatory monitoring station), M-Pod concentrations were determined using collocation calibrations and laboratory calibration techniques. M-Pods were placed near regulatory monitors to derive calibration function coefficients using the regulatory monitors as the standard. The form of the calibration function was derived based on laboratory experiments. We discuss various techniques used to estimate measurement uncertainties. The deployments revealed that collocation calibrations provide more accurate concentration estimates than laboratory calibrations. During collocation calibrations, median standard errors ranged between 4.0-6.1 ppb for O3, 6.4-8.4 ppb for NO2, 0.28-0.44 ppm for CO, and 16.8 ppm for CO2. Median signal to noise (S / N) ratios for the M-Pod sensors were higher than the regulatory instruments: for NO2, 3.6 compared to 23.4; for O3, 1.4 compared to 1.6; for CO, 1.1 compared to 10.0; and for CO2, 42.2 compared to 300-500. By contrast, lab calibrations added bias and made it difficult to cover the necessary range of environmental conditions to obtain a good calibration. A separate user study was also conducted to assess uncertainty estimates and sensor variability. In this study, 9 M-Pods were calibrated via collocation multiple times over 4 weeks, and sensor drift was analyzed, with the result being a calibration function that included baseline drift. Three pairs of M-Pods were deployed, while users individually carried the other three. The user study suggested that inter-M-Pod variability between paired units was on the same order as calibration uncertainty; however, it is difficult to make conclusions about the actual personal exposure levels due to the level of user engagement. The user study provided real-world sensor drift data, showing limited CO drift (under -0.05 ppm day-1), and higher for O3 (-2.6 to 2.0 ppb day-1), NO2 (-1.56 to 0.51 ppb day-1), and CO2 (-4.2 to 3.1 ppm day-1). Overall, the user study confirmed the utility of the M-Pod as a low-cost tool to assess personal exposure.
NASA Astrophysics Data System (ADS)
Berkoff, T.; Sullivan, J.; Pippin, M. R.; Gronoff, G.; Knepp, T. N.; Twigg, L.; Schroeder, J.; Carrion, W.; Farris, B.; Kowalewski, M. G.; Nino, L.; Gargulinski, E.; Rodio, L.; Sanchez, P.; Desorae Davis, A. A.; Janz, S. J.; Judd, L.; Pusede, S.; Wolfe, G. M.; Stauffer, R. M.; Munyan, J.; Flynn, J.; Moore, B.; Dreessen, J.; Salkovitz, D.; Stumpf, K.; King, B.; Hanisco, T. F.; Brandt, J.; Blake, D. R.; Abuhassan, N.; Cede, A.; Tzortziou, M.; Demoz, B.; Tsay, S. C.; Swap, R.; Holben, B. N.; Szykman, J.; McGee, T. J.; Neilan, J.; Allen, D.
2017-12-01
The monitoring of ozone (O3) in the troposphere is of pronounced interest due to its known toxicity and health hazard as a photo-chemically generated pollutant. One of the major difficulties for the air quality modeling, forecasting and satellite communities is the validation of O3 levels in sharp transition regions, as well as near-surface vertical gradients. Land-water gradients of O3 near coastal regions can be large due to differences in surface deposition, boundary layer height, and cloud coverage. Observations in horizontal and vertical directions over the Chesapeake Bay are needed to better understand O3 formation and redistribution within regional recirculation patterns. The O3 Water-Land Environmental Transition Study (OWLETS) was a field campaign conducted in the summer 2017 in the VA Tidewater region to better characterize O3 across the coastal boundary. To obtain over-water measurements, the NASA Langley Ozone Lidar as well as supplemental measurements from other sensors (e.g. Pandora, AERONET) were deployed on the Chesapeake Bay Bridge Tunnel (CBBT) 7-8 miles offshore. These observations were complimented by NASA Goddard's Tropospheric Ozone Lidar along with ground-based measurements over-land at the NASA Langley Research Center (LaRC) in Hampton, VA. On measurement days, time-synchronized data were collected, including launches of ozonesondes from CBBT and LaRC sites that provided additional O3, wind, and temperature vertical distribution differences between land and water. These measurements were complimented with: in-situ O3 sensors on two mobile cars, a micro-pulse lidar at Hampton University, an in-situ O3 sensor on a small UAV-drone, and Virginia DEQ air-quality sites. Two aircraft and a research vessel also contributed to OWLETS at various points during the campaign: the NASA UC-12B with the GeoTASO passive remote sensor, the NASA C-23 with an in-situ chemistry analysis suite, and a SERC research vessel with both remote and in-situ sensors. This combination of observations provided a unique 4-D (horizontal, vertical, and time) view of O3 to help provide feedback to air quality forecast models as well as future satellite remote sensing systems such as NASA's TEMPO mission. In this presentation, a summary of observations and initial results will be presented from the OWLETS campaign.
High-Q, in-plane modes of nanomechanical resonators operated in air
NASA Astrophysics Data System (ADS)
Waggoner, Philip S.; Tan, Christine P.; Bellan, Leon; Craighead, Harold G.
2009-05-01
Nanomechanical resonators have traditionally been limited to use in vacuum due to low quality factors that come as a result of viscous damping effects in air or liquid. We have fabricated arrays of 90 nm thick trampoline-shaped resonators, studied their resonant frequency spectrum as a function of pressure, and found that some high frequency modes exhibit quality factors over 2000 at atmospheric pressure. We have excited the in-plane resonances of these devices, verified their identities both experimentally and with finite element modeling, and demonstrated their advantageous characteristics for ambient sensing. Even after deposition of a relatively thick polymer layer, the in-plane resonant modes still boast quality factors on the order of 2000. These results show promise for the use of nanomechanical resonant sensors in real-time atmospheric sensing applications.
Network of Environmental Sensors in Tropical Rain Forests
NASA Astrophysics Data System (ADS)
von Randow, C.; Dos Santos, R. D.; Da Rocha, H.
2010-12-01
The interaction between the Earth’s atmosphere and the terrestrial biosphere plays a fundamental role in the climate system and in biogeochemical and hydrological cycles, through the exchange of energy and mass (for example, water and carbon), between the vegetation and the atmospheric boundary layer, and the main focus of many environmental studies is to quantify this exchange over several terrestrial biomes. Over natural surfaces like the tropical forests, factors like spatial variations in topography or in the vegetation cover can significantly affect the air flow and pose big challenges for the monitoring of the regional carbon budget of terrestrial biomes. It is hardly possible to understand the air flow and reduce the uncertainties of flux measurements in complex terrains like tropical forests without an approach that recognizes the complexity of the spatial variability of the environmental variables. With this motivation, a partnership involving Microsoft Research, Johns Hopkins University, University of São Paulo and Instituto Nacional de Pesquisas Espaciais (INPE, the Brazilian national institute for space research) has been developing research activities to test the use of prototypes of environmental sensors (geosensors) in the Atlantic coastal and in the Amazonian rain forests in Brazil, forming sensor networks with high spatial and temporal resolution, and to develop software tools for data quality control and integration. The main premise is that the geosensors should have relatively low cost, what enables the formation of monitoring networks with a large number of sensors spatially distributed. A pilot study deployed 200+ sensors over the Atlantic coastal forest in Sao Paulo state, Brazil. Here we present the results from this study, highlighting the current discussions on applications of this type of measurements in studies of biosphere-atmosphere interaction in the tropics. Envisioning a possible wide deployment of geosensors in Amazonia in the future, the team is currently working on three main components: 1) assembly and calibration of prototypes of geosensors of air temperature and humidity, with reproductive and reliable ceramic sensor elements that will adequately operate under the environmental conditions observed in the tropics; 2) development of software tools for management, quality control, visualization and integration of data collected in geosensor networks; and 3) planning of the Amazon experimental campaign, with the installation of the first tens to hundreds of sensors within and above the rainforest canopy, aiming at a test of the system to study the spatial variability of temperature and humidity.
Afshar-Mohajer, Nima; Zuidema, Christopher; Sousan, Sinan; Hallett, Laura; Tatum, Marcus; Rule, Ana M; Thomas, Geb; Peters, Thomas M; Koehler, Kirsten
2018-02-01
Development of an air quality monitoring network with high spatio-temporal resolution requires installation of a large number of air pollutant monitors. However, state-of-the-art monitors are costly and may not be compatible with wireless data logging systems. In this study, low-cost electro-chemical sensors manufactured by Alphasense Ltd. for detection of CO and oxidative gases (predominantly O 3 and NO 2 ) were evaluated. The voltages from three oxidative gas sensors and three CO sensors were recorded every 2.5 sec when exposed to controlled gas concentrations in a 0.125-m 3 acrylic glass chamber. Electro-chemical sensors for detection of oxidative gases demonstrated sensitivity to both NO 2 and O 3 with similar voltages recorded when exposed to equivalent environmental concentrations of NO 2 or O 3 gases, when evaluated separately. There was a strong linear relationship between the recorded voltages and target concentrations of oxidative gases (R 2 > 0.98) over a wide range of concentrations. Although a strong linear relationship was also observed for CO concentrations below 12 ppm, a saturation effect was observed wherein the voltage only changes minimally for higher CO concentrations (12-50 ppm). The nonlinear behavior of the CO sensors implied their unsuitability for environments where high CO concentrations are expected. Using a manufacturer-supplied shroud, sensors were tested at 2 different flow rates (0.25 and 0.5 Lpm) to mimic field calibration of the sensors with zero air and a span gas concentration (2 ppm NO2 or 15 ppm CO). As with all electrochemical sensors, the tested devices were subject to drift with a bias up to 20% after 9 months of continuous operation. Alphasense CO sensors were found to be a proper choice for occupational and environmental CO monitoring with maximum concentration of 12 ppm, especially due to the field-ready calibration capability. Alphasense oxidative gas sensors are usable only if it is valuable to know the sum of the NO 2 and O 3 concentrations.
Kok, Gertjan; Persijn, Stefan; Sauerwald, Tilman
2017-01-01
This article presents a literature review of sensors for the monitoring of benzene in ambient air and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considers commercially available sensors, including PID-based sensors, semiconductor (resistive gas sensors) and portable on-line measuring devices as for example sensor arrays. The bibliographic collection includes the following topics: sensor description, field of application at fixed sites, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions. PMID:28657595
Spinelle, Laurent; Gerboles, Michel; Kok, Gertjan; Persijn, Stefan; Sauerwald, Tilman
2017-06-28
This article presents a literature review of sensors for the monitoring of benzene in ambient air and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considers commercially available sensors, including PID-based sensors, semiconductor (resistive gas sensors) and portable on-line measuring devices as for example sensor arrays. The bibliographic collection includes the following topics: sensor description, field of application at fixed sites, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions.
NASA Technical Reports Server (NTRS)
Tibbitts, T. W. (Principal Investigator)
1986-01-01
This report includes procedures for ensuring the quality of the environment provided for plant growth in controlled environment facilities. Biologists and engineers may use these procedures for ensuring quality control during experiments or for ensuring quality control in the design of plant growth facilities. Environmental monitoring prior to and during experiments is included in these procedures. Specific recommendations cover control, acquisition, and calibration for sensor types for the separate parameters of radiation (light), temperature, humidity, carbon dioxide, and air movement.
NASA Astrophysics Data System (ADS)
Soeharwinto; Sinulingga, Emerson; Siregar, Baihaqi
2017-01-01
An accurate information can be useful for authorities to make good policies for preventive and mitigation after volcano eruption disaster. Monitoring of environmental parameters of post-eruption volcano provides an important information for authorities. Such monitoring system can be develop using the Wireless Network Sensor technology. Many application has been developed using the Wireless Sensor Network technology, such as floods early warning system, sun radiation mapping, and watershed monitoring. This paper describes the implementation of a remote environment monitoring system of mount Sinabung post-eruption. The system monitor three environmental parameters: soil condition, water quality and air quality (outdoor). Motes equipped with proper sensors, as components of the monitoring system placed in sample locations. The measured value from the sensors periodically sends to data server using 3G/GPRS communication module. The data can be downloaded by the user for further analysis.The measurement and data analysis results generally indicate that the environmental parameters in the range of normal/standard condition. The sample locations are safe for living and suitable for cultivation, but awareness is strictly required due to the uncertainty of Sinabung status.
Corrosion detector apparatus for universal assessment of pollution in data centers
Hamann, Hendrik F.; Klein, Levente I.
2015-08-18
A compact corrosion measurement apparatus and system includes an air fan, a corrosion sensor, a temperature sensor, a humidity sensor, a heater element, and an air flow sensor all under control to monitor and maintain constant air parameters in an environment and minimize environmental fluctuations around the corrosion sensor to overcome the variation commonly encountered in corrosion rate measurement. The corrosion measurement apparatus includes a structure providing an enclosure within which are located the sensors. Constant air flow and temperature is maintained within the enclosure where the corrosion sensor is located by integrating a variable speed air fan and a heater with the corresponding feedback loop control. Temperature and air flow control loops ensure that corrosivity is measured under similar conditions in different facilities offering a general reference point that allow a one to one comparison between facilities with similar or different pollution levels.
A Visual Analytics Approach for Station-Based Air Quality Data
Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui
2016-01-01
With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support. PMID:28029117
A Visual Analytics Approach for Station-Based Air Quality Data.
Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui
2016-12-24
With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.
NASA Technical Reports Server (NTRS)
Nowlan, Caroline R.; Liu, Xiong; Leitch, James W.; Chance, Kelly; Abad, Gonzalo Gonzalez; Liu, Xiaojun; Zoogman, Peter; Cole, Joshua; Delker, Thomas; Good, William;
2016-01-01
The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m x 250 m spatial resolution with a fitting precision of 2.2 x 10(exp 15) molecules/sq cm. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.
Noncontact Monitoring of Respiration by Dynamic Air-Pressure Sensor.
Takarada, Tohru; Asada, Tetsunosuke; Sumi, Yoshihisa; Higuchi, Yoshinori
2015-01-01
We have previously reported that a dynamic air-pressure sensor system allows respiratory status to be visually monitored for patients in minimally clothed condition. The dynamic air-pressure sensor measures vital information using changes in air pressure. To utilize this device in the field, we must clarify the influence of clothing conditions on measurement. The present study evaluated use of the dynamic air-pressure sensor system as a respiratory monitor that can reliably detect change in breathing patterns irrespective of clothing. Twelve healthy volunteers reclined on a dental chair positioned horizontally with the sensor pad for measuring air-pressure signals corresponding to respiration placed on the seat back of the dental chair in the central lumbar region. Respiratory measurements were taken under 2 conditions: (a) thinly clothed (subject lying directly on the sensor pad); and (b) thickly clothed (subject lying on the sensor pad covered with a pressure-reducing sheet). Air-pressure signals were recorded and time integration values for air pressure during each expiration were calculated. This information was compared with expiratory tidal volume measured simultaneously by a respirometer connected to the subject via face mask. The dynamic air-pressure sensor was able to receive the signal corresponding to respiration regardless of clothing conditions. A strong correlation was identified between expiratory tidal volume and time integration values for air pressure during each expiration for all subjects under both clothing conditions (0.840-0.988 for the thinly clothed condition and 0.867-0.992 for the thickly clothed condition). These results show that the dynamic air-pressure sensor is useful for monitoring respiratory physiology irrespective of clothing.
Rapid Analysis, Self-Calibrating Array for Air Monitoring
NASA Technical Reports Server (NTRS)
Homer, Margie L.; Shevade, Abhijit V.; Lara, Liana; Huerta, Ramon; Vergara, Alexander; Muezzinoglua, Mehmet K.
2012-01-01
Human space missions have critical needs for monitoring and control for life support systems. These systems have monitoring needs that include feedback for closed loop processes and quality control for environmental factors. Sensors and monitoring technologies assure that the air environment and water supply for the astronaut crew habitat fall within acceptable limits, and that the life support system is functioning properly and efficiently. The longer the flight duration and the more distant the destination, the more critical it becomes to have carefully monitored and automated control systems for life support. Past experiments with the JPL ENose have demonstrated a lifetime of the sensor array, with the software, of around 18 months. The lifetime of the calibration, for some analytes, was as long as 24 months. We are working on a sensor array and new algorithms that will include sensor response time in the analysis. The preliminary array analysis for two analytes shows that the analysis time, of an event, can be dropped from 45 minutes to less than10 minutes and array training time can be cut substantially. We will describe the lifetime testing of an array and show lifetime data on individual sensors. This progress will lead to more rapid identification of analytes, and faster training time of the array.
MOF-Based Membrane Encapsulated ZnO Nanowires for Enhanced Gas Sensor Selectivity.
Drobek, Martin; Kim, Jae-Hun; Bechelany, Mikhael; Vallicari, Cyril; Julbe, Anne; Kim, Sang Sub
2016-04-06
Gas sensors are of a great interest for applications including toxic or explosive gases detection in both in-house and industrial environments, air quality monitoring, medical diagnostics, or control of food/cosmetic properties. In the area of semiconductor metal oxides (SMOs)-based sensors, a lot of effort has been devoted to improve the sensing characteristics. In this work, we report on a general methodology for improving the selectivity of SMOx nanowires sensors, based on the coverage of ZnO nanowires with a thin ZIF-8 molecular sieve membrane. The optimized ZnO@ZIF-8-based nanocomposite sensor shows markedly selective response to H2 in comparison with the pristine ZnO nanowires sensor, while showing the negligible sensing response to C7H8 and C6H6. This original MOF-membrane encapsulation strategy applied to nanowires sensor architecture pave the way for other complex 3D architectures and various types of applications requiring either gas or ion selectivity, such as biosensors, photo(catalysts), and electrodes.
Bluetooth gas sensing module combined with smartphones for air quality monitoring.
Suárez, José Ignacio; Arroyo, Patricia; Lozano, Jesús; Herrero, José Luis; Padilla, Manuel
2018-08-01
This study addresses the development of a miniaturized (60 × 60 mm) Wireless Sensing Module (WSM) for environmental application and air quality detection. The proposed prototype has six sensors: one for humidity, one for ambient temperature (SHT21 from Sensirion), and four for gas detection (MiCS-4514, MiCS-5526 and MiCS-5914 from SGX Sensortech). The core of the system is based on a high performance 8-bit microcontroller, model PIC18F46K80, from Microchip. The obtained data values were transmitted to the Smartphone through a Bluetooth communication module and a home-developed Android app. The discrimination capability of the module is tested with 10 volatile organic compounds (acetone, acetic acid, benzene, ethanol, ethyl acetate, ethylbenzene, formaldehyde, toluene, xylene, and dimethylacetamide) and the effect of humidity and drift of the sensors is also studied. Results show that 88.33% and 92.22% success rates in classification stage are obtained using Multilayer Perceptron with BackPropagation Learning algorithm and Radial-Basis based Neural Networks, respectively. Copyright © 2018 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Amrani, D.
2013-01-01
This paper deals with the comparison of sound speed measurements in air using two types of sensor that are widely employed in physics and engineering education, namely a pressure sensor and a sound sensor. A computer-based laboratory with pressure and sound sensors was used to carry out measurements of air through a 60 ml syringe. The fast Fourier…
Community Air Sensor Network CAIRSENSE Project: Lower ...
Presentation slides on the CAIRSENSE project, Atlanta field study testing low cost air sensors against FEM instruments. To be presented at the Air and Waste Management Association conference. Presentation slides on the CAIRSENSE project, Atlanta field study testing low cost air sensors against FEM instruments. To be presented at the Air and Waste Management Association conference.
Highlights from the Air Sensors 2014 Workshop
In June 2014, the U.S. Environmental Protection Agency (EPA) hosted its fourth next-generation air monitoring workshop to discuss the current state of the science in air sensor technologies and their applications for environmental monitoring, Air Sensors 2014: A New Frontier. Th...
Architecture for an integrated real-time air combat and sensor network simulation
NASA Astrophysics Data System (ADS)
Criswell, Evans A.; Rushing, John; Lin, Hong; Graves, Sara
2007-04-01
An architecture for an integrated air combat and sensor network simulation is presented. The architecture integrates two components: a parallel real-time sensor fusion and target tracking simulation, and an air combat simulation. By integrating these two simulations, it becomes possible to experiment with scenarios in which one or both sides in a battle have very large numbers of primitive passive sensors, and to assess the likely effects of those sensors on the outcome of the battle. Modern Air Power is a real-time theater-level air combat simulation that is currently being used as a part of the USAF Air and Space Basic Course (ASBC). The simulation includes a variety of scenarios from the Vietnam war to the present day, and also includes several hypothetical future scenarios. Modern Air Power includes a scenario editor, an order of battle editor, and full AI customization features that make it possible to quickly construct scenarios for any conflict of interest. The scenario editor makes it possible to place a wide variety of sensors including both high fidelity sensors such as radars, and primitive passive sensors that provide only very limited information. The parallel real-time sensor network simulation is capable of handling very large numbers of sensors on a computing cluster of modest size. It can fuse information provided by disparate sensors to detect and track targets, and produce target tracks.
Double air-fuel ratio sensor system having double-skip function
DOE Office of Scientific and Technical Information (OSTI.GOV)
Katsuno, T.
1988-01-26
A method for controlling the air-fuel ratio in an internal combustion engine is described having a catalyst converter for removing pollutants in the exhaust gas thereof, and upstream-side and downstream-side air-fuel ratio sensors disposed upstream and downstream, respectively, of the catalyst converter for detecting a concentration of a specific component in an exhaust gas, comprising the steps of: comparing the output of the upstream-side air-fuel ratio sensor with a first predetermined value; gradually changing a first air-fuel ratio correction amount in accordance with a result of the comparison of the output of the upstream-side air-fuel ratio sensor with the predeterminedmore » value; shifting the first air-fuel ratio correction amount by a first skip amount during a predetermined time period after the result of the comparison of the upstream-side air-fuel ratio sensor is changed; shifting the first air-fuel ratio correction amount by a second skip amount smaller than the first skip amount after the predetermined time period has passed; comparing the output of the downstream-side air-fuel ratio with a second predetermined value, calculating a second air-fuel ratio correction amount in accordance with the comparison result of the output of the downstream-side air-fuel ratio sensor with the second predetermined value; and adjusting the actual air-fuel ratio in accordance with the first and second air-fuel ratio correction amounts; wherein the gradually-changing step comprises the steps of: gradually decreasing the first air-fuel ratio correction amount when the output of the upstream-side air-fuel sensor is on the rich side with respect to the first predetermined value; and gradually increasing the first air-fuel ratio correction amount when the output of the upstream-side air-fuel sensor is on the lean side with respect to the first predetermined value.« less
NASA Astrophysics Data System (ADS)
de Podesta, Michael; Bell, Stephanie; Underwood, Robin
2018-04-01
In both meteorological and metrological applications, it is well known that air temperature sensors are susceptible to radiative errors. However, it is not widely known that the radiative error measured by an air temperature sensor in flowing air depends upon the sensor diameter, with smaller sensors reporting values closer to true air temperature. This is not a transient effect related to sensor heat capacity, but a fluid-dynamical effect arising from heat and mass flow in cylindrical geometries. This result has been known historically and is in meteorology text books. However, its significance does not appear to be widely appreciated and, as a consequence, air temperature can be—and probably is being—widely mis-estimated. In this paper, we first review prior descriptions of the ‘sensor size’ effect from the metrological and meteorological literature. We develop a heat transfer model to describe the process for cylindrical sensors, and evaluate the predicted temperature error for a range of sensor sizes and air speeds. We compare these predictions with published predictions and measurements. We report measurements demonstrating this effect in two laboratories at NPL in which the air flow and temperature are exceptionally closely controlled. The results are consistent with the heat-transfer model, and show that the air temperature error is proportional to the square root of the sensor diameter and that, even under good laboratory conditions, it can exceed 0.1 °C for a 6 mm diameter sensor. We then consider the implications of this result. In metrological applications, errors of the order of 0.1 °C are significant, representing limiting uncertainties in dimensional and mass measurements. In meteorological applications, radiative errors can easily be much larger. But in both cases, an understanding of the diameter dependence allows assessment and correction of the radiative error using a multi-sensor technique.
Modeling, Monitoring and Fault Diagnosis of Spacecraft Air Contaminants
NASA Technical Reports Server (NTRS)
Ramirez, W. Fred; Skliar, Mikhail; Narayan, Anand; Morgenthaler, George W.; Smith, Gerald J.
1996-01-01
Progress and results in the development of an integrated air quality modeling, monitoring, fault detection, and isolation system are presented. The focus was on development of distributed models of the air contaminants transport, the study of air quality monitoring techniques based on the model of transport process and on-line contaminant concentration measurements, and sensor placement. Different approaches to the modeling of spacecraft air contamination are discussed, and a three-dimensional distributed parameter air contaminant dispersion model applicable to both laminar and turbulent transport is proposed. A two-dimensional approximation of a full scale transport model is also proposed based on the spatial averaging of the three dimensional model over the least important space coordinate. A computer implementation of the transport model is considered and a detailed development of two- and three-dimensional models illustrated by contaminant transport simulation results is presented. The use of a well established Kalman filtering approach is suggested as a method for generating on-line contaminant concentration estimates based on both real time measurements and the model of contaminant transport process. It is shown that high computational requirements of the traditional Kalman filter can render difficult its real-time implementation for high-dimensional transport model and a novel implicit Kalman filtering algorithm is proposed which is shown to lead to an order of magnitude faster computer implementation in the case of air quality monitoring.
NASA Astrophysics Data System (ADS)
Haderman, M.; Dye, T. S.; White, J. E.; Dickerson, P.; Pasch, A. N.; Miller, D. S.; Chan, A. C.
2012-12-01
Built upon the success of the U.S. Environmental Protection Agency's (EPA) AirNow program (www.AirNow.gov), the AirNow-International (AirNow-I) system contains an enhanced suite of software programs that process and quality control real-time air quality and environmental data and distribute customized maps, files, and data feeds. The goals of the AirNow-I program are similar to those of the successful U.S. program and include fostering the exchange of environmental data; making advances in air quality knowledge and applications; and building a community of people, organizations, and decision makers in environmental management. In 2010, Shanghai became the first city in China to run this state-of-the-art air quality data management and notification system. AirNow-I consists of a suite of modules (software programs and schedulers) centered on a database. One such module is the Information Management System (IMS), which can automatically produce maps and other data products through the use of GIS software to provide the most current air quality information to the public. Developed with Global Earth Observation System of Systems (GEOSS) interoperability in mind, IMS is based on non-proprietary standards, with preference to formal international standards. The system depends on data and information providers accepting and implementing a set of interoperability arrangements, including technical specifications for collecting, processing, storing, and disseminating shared data, metadata, and products. In particular, the specifications include standards for service-oriented architecture and web-based interfaces, such as a web mapping service (WMS), web coverage service (WCS), web feature service (WFS), sensor web services, and Really Simple Syndication (RSS) feeds. IMS is flexible, open, redundant, and modular. It also allows the merging of data grids to create complex grids that show comprehensive air quality conditions. For example, the AirNow Satellite Data Processor (ASDP) was recently developed to merge PM2.5 estimates from National Aeronautics and Space Administration (NASA) satellite data and AirNow observational data, creating more precise maps and gridded data products for under-monitored areas. The ASDP can easily incorporate other data feeds, including fire and smoke locations, to build enhanced real-time air quality data products. In this presentation, we provide an overview of the features and functions of IMS, an explanation of how data moves through IMS, the rationale of the system architecture, and highlights of the ASDP as an example of the modularity and scalability of IMS.
NASA Astrophysics Data System (ADS)
Ya, Y. H.; Poh, K. S.
2015-09-01
The performance of an existing underfloor air distribution (UFAD) system in a renowned high-rise office tower in Malaysia was studied to identify the root cause issues behind the poor indoor air quality. Occupants are the best thermal sensor. The building was detected with the sick building syndrome (SBS) that causes runny noses, flu-like symptoms, irritated skin, and etc. Long period of exposure to indoor air pollutants may increase the occupant's health risk. The parameters such as the space temperature, relative humidity, air movement, air change, fresh air flow rate, chilled water supply and return are evaluated at three stories that consist of five open offices. A full traverse study was carried out at one of the fresh air duct. A simplified duct flow measurement method using pitot-tubes was developed. The results showed that the diffusers were not effective in creating the swirl effect to the space. Internal heat gain from human and office electrical equipment were not drawn out effectively. Besides, relative humidity has exceeded the recommended level. These issues were caused by the poor maintenance of the building. The energy efficiency strategy of the UFAD system comes from the higher supply air temperature. It may leads to insufficient cooling load for the latent heat gained under improper system performance. Special care and considerations in design, construction and maintenance are needed to ensure the indoor air quality to be maintained. Several improvements were recommended to tackle the existing indoor air quality issues. Solar system was studied as one of the innovative method for retrofitting.
Clustering approaches to improve the performance of low cost air pollution sensors.
Smith, Katie R; Edwards, Peter M; Evans, Mathew J; Lee, James D; Shaw, Marvin D; Squires, Freya; Wilde, Shona; Lewis, Alastair C
2017-08-24
Low cost air pollution sensors have substantial potential for atmospheric research and for the applied control of pollution in the urban environment, including more localized warnings to the public. The current generation of single-chemical gas sensors experience degrees of interference from other co-pollutants and have sensitivity to environmental factors such as temperature, wind speed and supply voltage. There are uncertainties introduced also because of sensor-to-sensor response variability, although this is less well reported. The sensitivity of Metal Oxide Sensors (MOS) to volatile organic compounds (VOCs) changed with relative humidity (RH) by up to a factor of five over the range of 19-90% RH and with an uncertainty in the correction of a factor of two at any given RH. The short-term (second to minute) stabilities of MOS and electrochemical CO sensor responses were reasonable. During more extended use, inter-sensor quantitative comparability was degraded due to unpredictable variability in individual sensor responses (to either measurand or interference or both) drifting over timescales of several hours to days. For timescales longer than a week identical sensors showed slow, often downwards, drifts in their responses which diverged across six CO sensors by up to 30% after two weeks. The measurement derived from the median sensor within clusters of 6, 8 and up to 21 sensors was evaluated against individual sensor performance and external reference values. The clustered approach maintained the cost competitiveness of a sensor device, but the median concentration from the ensemble of sensor signals largely eliminated the randomised hour-to-day response drift seen in individual sensors and excluded the effects of small numbers of poorly performing sensors that drifted significantly over longer time periods. The results demonstrate that for individual sensors to be optimally comparable to one another, and to reference instruments, they would likely require frequent calibration. The use of a cluster median value eliminates unpredictable medium term response changes, and other longer term outlier behaviours, extending the likely period needed between calibration and making a linear interpolation between calibrations more appropriate. Through the use of sensor clusters rather than individual sensors, existing low cost technologies could deliver significantly improved quality of observations.
Wireless Sensor Network Applications for the Combat Air Forces
2006-06-13
WIRELESS SENSOR NETWORK APPLICATIONS FOR THE COMBAT AIR FORCES GRADUATE RESEARCH PROJECT...Government. AFIT/IC4/ENG/06-05 WIRELESS SENSOR NETWORK APPLICATIONS FOR THE COMBAT AIR FORCES GRADUATE RESEARCH PROJECT Presented to the...Major, USAF June 2006 APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED AFIT/IC4/ENG/06-05 WIRELESS SENSOR NETWORK APPLICATIONS
NASA Astrophysics Data System (ADS)
Atutov, S. N.; Galeyev, A. E.; Plekhanov, A. I.; Yakovlev, A. V.
2018-03-01
A sensitive and versatile sensor for the detection of traces of atoms or molecules in air based on the emission spectroscopy of glow discharge in air has been developed and studied. The advantages of this sensor compared to other well-known methods are that it renders the use of ultrahigh vacuum or cryogenic temperatures superfluous. The sensor is insensitive to the presence of water vapor (for example, in exhaled air) because of the absence of strong water lines in the visible spectral range. It has a high spectral selectivity limited only by Doppler broadening of the emission lines. The high selectivity of the sensor combined with a wide spectral range allows the detection of many toxic impurities, which can be present in air. Moreover, the spectral range used covers almost all biomarkers in exhaled air, making the proposed sensor extremely interesting for medical applications. To our knowledge, the proposed method is the first based on a glow discharge in air.
Real-time indoor monitoring system based on wireless sensor networks
NASA Astrophysics Data System (ADS)
Wu, Zhengzhong; Liu, Zilin; Huang, Xiaowei; Liu, Jun
2008-10-01
Wireless sensor networks (WSN) greatly extend our ability to monitor and control the physical world. It can collaborate and aggregate a huge amount of sensed data to provide continuous and spatially dense observation of environment. The control and monitoring of indoor atmosphere conditions represents an important task with the aim of ensuring suitable working and living spaces to people. However, the comprehensive air quality, which includes monitoring of humidity, temperature, gas concentrations, etc., is not so easy to be monitored and controlled. In this paper an indoor WSN monitoring system was developed. In the system several sensors such as temperature sensor, humidity sensor, gases sensor, were built in a RF transceiver board for monitoring indoor environment conditions. The indoor environmental monitoring parameters can be transmitted by wireless to database server and then viewed throw PC or PDA accessed to the local area networks by administrators. The system, which was also field-tested and showed a reliable and robust characteristic, is significant and valuable to people.
Image quality on the Kuiper Airborne Observatory. I - Results of the first flight series
NASA Technical Reports Server (NTRS)
Elliot, J. L.; Dunham, E. W.; Baron, R. L.; Watts, A. W.; Kruse, S. E.; Rose, W. C.; Gillespie, C. M., Jr.
1989-01-01
The NASA Kuiper Airborne Observatory (KAO) was flown three times during June and July, 1984 in order to study the causes of the poor seeing obtained with the 0.9-m telescope. High-speed pressure and temperature sensors were placed in the telescope cavity. Several thousand stellar images were recorded under various flight and optical configurations. It is found that the long-exposure image size is affected by telescope tracking errors, imperfect optics, poor optical alignment, telescope and instrument vibration, thermal fluctuations in the telescope cavity, and density fluctuations in the shear layer that forms the boundary between the cavity air and outside air. Possible ways to improve the quality of the images are discussed.
Web Information Systems for Monitoring and Control of Indoor Air Quality at Subway Stations
NASA Astrophysics Data System (ADS)
Choi, Gi Heung; Choi, Gi Sang; Jang, Joo Hyoung
In crowded subway stations indoor air quality (IAQ) is a key factor for ensuring the safety, health and comfort of passengers. In this study, a framework for web-based information system in VDN environment for monitoring and control of IAQ in subway stations is suggested. Since physical variables that describing IAQ need to be closely monitored and controlled in multiple locations in subway stations, concept of distributed monitoring and control network using wireless media needs to be implemented. Connecting remote wireless sensor network and device (LonWorks) networks to the IP network based on the concept of VDN can provide a powerful, integrated, distributed monitoring and control performance, making a web-based information system possible.
Greenhouse intelligent control system based on microcontroller
NASA Astrophysics Data System (ADS)
Zhang, Congwei
2018-04-01
As one of the hallmarks of agricultural modernization, intelligent greenhouse has the advantages of high yield, excellent quality, no pollution and continuous planting. Taking AT89S52 microcontroller as the main controller, the greenhouse intelligent control system uses soil moisture sensor, temperature and humidity sensors, light intensity sensor and CO2 concentration sensor to collect measurements and display them on the 12864 LCD screen real-time. Meantime, climate parameter values can be manually set online. The collected measured values are compared with the set standard values, and then the lighting, ventilation fans, warming lamps, water pumps and other facilities automatically start to adjust the climate such as light intensity, CO2 concentration, temperature, air humidity and soil moisture of the greenhouse parameter. So, the state of the environment in the greenhouse Stabilizes and the crop grows in a suitable environment.
Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring n...
NASA Astrophysics Data System (ADS)
Valasek, John; Henrickson, James V.; Bowden, Ezekiel; Shi, Yeyin; Morgan, Cristine L. S.; Neely, Haly L.
2016-05-01
As small unmanned aircraft systems become increasingly affordable, reliable, and formally recognized under federal regulation, they become increasingly attractive as novel platforms for civil applications. This paper details the development and demonstration of fixed-wing unmanned aircraft systems for precision agriculture tasks. Tasks such as soil moisture content and high throughput phenotyping are considered. Rationale for sensor, vehicle, and ground equipment selections are provided, in addition to developed flight operation procedures for minimal numbers of crew. Preliminary imagery results are presented and analyzed, and these results demonstrate that fixed-wing unmanned aircraft systems modified to carry non-traditional sensors at extended endurance durations can provide high quality data that is usable for serious scientific analysis.
Molecular modeling of interactions in electronic nose sensors for environmental monitoring
NASA Technical Reports Server (NTRS)
Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Manfreda, A. M.; Yen, S. -P. S.; Zhou, H.; Manatt, K.
2002-01-01
We report a study aimed at understanding analyte interactions with sensors made from polymer-carbon black composite films. The sensors are used in an Electronic Nose (ENose) which is used for monitoring the breathing air quality in human habitats. The model mimics the experimental conditions of the composite film deposition and formation and was developed using molecular modeling and simulation tools. The Dreiding 2.21 Force Field was used for the polymer and analyte molecules while graphite parameters were assigned to the carbon black atoms. The polymer considered for this work is methyl vinyl ether / maleic acid copolymer. The target analytes include both inorganic (NH3) and organic (methanol) types of compound. Results indicate different composite-analyte interaction behavior.
Evaluating signal and noise spectral density of a qPlus sensor with an active feedback control
NASA Astrophysics Data System (ADS)
Lee, Manhee; An, Sangmin; Jhe, Wonho
2018-05-01
Q-control technique enables to actively change the quality factor of the probe oscillation in dynamic atomic force microscopy. The Q-control is realized by adding a self-feedback loop into the original actuation-detection system, in which a damping force with controllable damping coefficient in magnitude and sign is applied to the oscillating probe. While the applied force alters the total damping interaction and thus the overall `signal' of the probe motion, the added feedback system changes the `noise' of the motion as well. Here, we systematically investigate the signal, the noise, and the signal-to-noise ratio of the qPlus sensor under the active Q-control. We quantify the noise of the qPlus motion by measuring the noise spectral density, which is reproduced by a harmonic oscillator model including the thermal and the measurement noises. We show that the noise signal increases with the quality factor controlled, scaling as the square root of the quality factor. Because the overall signal is linearly proportional to the quality factor, the signal-to-noise ratio scales as the square root of the quality factor. The Q-controlled qPlus with a highly enhanced Q, up to 10,000 in air, leads to the minimum detectable force gradient of 0.001 N/m, which would enhance the capability of the qPlus sensor for atomic force microscopy and spectroscopy.
Air Force Research Laboratory Sensors Directorate Leadership Legacy, 1960-2011
2011-03-01
AFRL -RY-WP-TM-2011-1017 AIR FORCE RESEARCH LABORATORY SENSORS DIRECTORATE LEADERSHIP LEGACY, 1960-2011 Compiled by Raymond C. Rang...Structures Divi- sion, Space Vehicles Directorate, Air Force Research Laboratory , Kirtland AFB, N.M. 7. March 1998 - July 1999, Chief, Integration and... Research Laboratory ( AFRL ), and Deputy Director of the Sensors Direc- torate, Air Force Research
Fully wireless pressure sensor based on endoscopy images
NASA Astrophysics Data System (ADS)
Maeda, Yusaku; Mori, Hirohito; Nakagawa, Tomoaki; Takao, Hidekuni
2018-04-01
In this paper, the result of developing a fully wireless pressure sensor based on endoscopy images for an endoscopic surgery is reported for the first time. The sensor device has structural color with a nm-scale narrow gap, and the gap is changed by air pressure. The structural color of the sensor is acquired from camera images. Pressure detection can be realized with existing endoscope configurations only. The inner air pressure of the human body should be measured under flexible-endoscope operation using the sensor. Air pressure monitoring, has two important purposes. The first is to quantitatively measure tumor size under a constant air pressure for treatment selection. The second purpose is to prevent the endangerment of a patient due to over transmission of air. The developed sensor was evaluated, and the detection principle based on only endoscopy images has been successfully demonstrated.
Lin, Jesun; Pai, Jar-Yuan; Chen, Chih-Cheng
2012-12-01
RFID technology, an automatic identification and data capture technology to provide identification, tracing, security and so on, was widely applied to healthcare industry in these years. Employing HEPA ventilation system in hospital is a way to ensure healthful indoor air quality to protect patients and healthcare workers against hospital-acquired infections. However, the system consumes lots of electricity which cost a lot. This study aims to apply the RFID technology to offer a unique medical staff and patient identification, and reacting HEPA air ventilation system in order to reduce the cost, save energy and prevent the prevalence of hospital-acquired infection. The system, reacting HEPA air ventilation system, contains RFID tags (for medical staffs and patients), sensor, and reacting system which receives the information regarding the number of medical staff and the status of the surgery, and controls the air volume of the HEPA air ventilation system accordingly. A pilot program was carried out in a unit of operation rooms of a medical center with 1,500 beds located in central Taiwan from Jan to Aug 2010. The results found the air ventilation system was able to function much more efficiently with less energy consumed. Furthermore, the indoor air quality could still keep qualified and hospital-acquired infection or other occupational diseases could be prevented.
Environment and health: Probes and sensors for environment digital control
NASA Astrophysics Data System (ADS)
Schettini, Chiara
2014-05-01
The idea of studying the environment using New Technologies (NT) came from a MIUR (Ministry of Education of the Italian Government) notice that allocated funds for the realization of innovative school science projects. The "Environment and Health" project uses probes and sensors for digital control of environment (water, air and soil). The working group was composed of 4 Science teachers from 'Liceo Statale G. Mazzini ', under the coordination of teacher Chiara Schettini. The Didactic Section of Naples City of Sciences helped the teachers in developing the project and it organized a refresher course for them on the utilization of digital control sensors. The project connects Environment and Technology because the study of the natural aspects and the analysis of the chemical-physical parameters give students and teachers skills for studying the environment based on the utilization of NT in computing data elaboration. During the practical project, samples of air, water and soil are gathered in different contexts. Sample analysis was done in the school's scientific laboratory with digitally controlled sensors. The data are elaborated with specific software and the results have been written in a booklet and in a computing database. During the first year, the project involved 6 school classes (age of the students 14—15 years), under the coordination of Science teachers. The project aims are: 1) making students more aware about environmental matters 2) achieving basic skills for evaluating air, water and soil quality. 3) achieving strong skills for the utilization of digitally controlled sensors. 4) achieving computing skills for elaborating and presenting data. The project aims to develop a large environmental conscience and the need of a ' good ' environment for defending our health. Moreover it would increase the importance of NT as an instrument of knowledge.
A Low-Power Thermal-Based Sensor System for Low Air Flow Detection
Arifuzzman, AKM; Haider, Mohammad Rafiqul; Allison, David B.
2016-01-01
Being able to rapidly detect a low air flow rate with high accuracy is essential for various applications in the automotive and biomedical industries. We have developed a thermal-based low air flow sensor with a low-power sensor readout for biomedical applications. The thermal-based air flow sensor comprises a heater and three pairs of temperature sensors that sense temperature differences due to laminar air flow. The thermal-based flow sensor was designed and simulated by using laminar flow, heat transfer in solids and fluids physics in COMSOL MultiPhysics software. The proposed sensor can detect air flow as low as 0.0064 m/sec. The readout circuit is based on a current- controlled ring oscillator in which the output frequency of the ring oscillator is proportional to the temperature differences of the sensors. The entire readout circuit was designed and simulated by using a 130-nm standard CMOS process. The sensor circuit features a small area and low-power consumption of about 22.6 µW with an 800 mV power supply. In the simulation, the output frequency of the ring oscillator and the change in thermistor resistance showed a high linearity with an R2 value of 0.9987. The low-power dissipation, high linearity and small dimensions of the proposed flow sensor and circuit make the system highly suitable for biomedical applications. PMID:28435186
Community Air Sensor Network (CAIRSENSE) Project: Lower Cost, Continuous Ambient Monitoring Methods
Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of numerous sensors across a small geographic area would have potential benefits to supplement existing monitoring networks and ...
CO and NO2 Selective Monitoring by ZnO-Based Sensors
Hjiri, Mokhtar; El Mir, Lassaad; Leonardi, Salvatore Gianluca; Donato, Nicola; Neri, Giovanni
2013-01-01
ZnO nanomaterials with different shapes were synthesized, characterized and tested in the selective monitoring of low concentration of CO and NO2 in air. ZnO nanoparticles (NPs) and nanofibers (NFs) were synthesized by a modified sol-gel method in supercritical conditions and electrospinning technique, respectively. CO and NO2 sensing tests have demonstrated that the annealing temperature and shape of zinc oxide nanomaterials are the key factors in modulating the electrical and sensing properties. Specifically, ZnO NPs annealed at high temperature (700 °C) have been found sensitive to CO, while they displayed negligible response to NO2. The opposite behavior has been registered for the one-dimensional ZnO NFs annealed at medium temperature (400 °C). Due to their adaptable sensitivity/selectivity characteristics, the developed sensors show promising applications in dual air quality control systems for closed ambient such as automotive cabin, parking garage and tunnels. PMID:28348340
Social media as a sensor of air quality and public response in China.
Wang, Shiliang; Paul, Michael J; Dredze, Mark
2015-03-26
Recent studies have demonstrated the utility of social media data sources for a wide range of public health goals, including disease surveillance, mental health trends, and health perceptions and sentiment. Most such research has focused on English-language social media for the task of disease surveillance. We investigated the value of Chinese social media for monitoring air quality trends and related public perceptions and response. The goal was to determine if this data is suitable for learning actionable information about pollution levels and public response. We mined a collection of 93 million messages from Sina Weibo, China's largest microblogging service. We experimented with different filters to identify messages relevant to air quality, based on keyword matching and topic modeling. We evaluated the reliability of the data filters by comparing message volume per city to air particle pollution rates obtained from the Chinese government for 74 cities. Additionally, we performed a qualitative study of the content of pollution-related messages by coding a sample of 170 messages for relevance to air quality, and whether the message included details such as a reactive behavior or a health concern. The volume of pollution-related messages is highly correlated with particle pollution levels, with Pearson correlation values up to .718 (n=74, P<.001). Our qualitative results found that 67.1% (114/170) of messages were relevant to air quality and of those, 78.9% (90/114) were a firsthand report. Of firsthand reports, 28% (32/90) indicated a reactive behavior and 19% (17/90) expressed a health concern. Additionally, 3 messages of 170 requested that action be taken to improve quality. We have found quantitatively that message volume in Sina Weibo is indicative of true particle pollution levels, and we have found qualitatively that messages contain rich details including perceptions, behaviors, and self-reported health effects. Social media data can augment existing air pollution surveillance data, especially perception and health-related data that traditionally requires expensive surveys or interviews.
Linear air-fuel sensor development
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garzon, F.; Miller, C.
1996-12-14
The electrochemical zirconia solid electrolyte oxygen sensor, is extensively used for monitoring oxygen concentrations in various fields. They are currently utilized in automobiles to monitor the exhaust gas composition and control the air-to-fuel ratio, thus reducing harmful emission components and improving fuel economy. Zirconia oxygen sensors, are divided into two classes of devices: (1) potentiometric or logarithmic air/fuel sensors; and (2) amperometric or linear air/fuel sensors. The potentiometric sensors are ideally suited to monitor the air-to-fuel ratio close to the complete combustion stoichiometry; a value of about 14.8 to 1 parts by volume. This occurs because the oxygen concentration changesmore » by many orders of magnitude as the air/fuel ratio is varied through the stoichiometric value. However, the potentiometric sensor is not very sensitive to changes in oxygen partial pressure away from the stoichiometric point due to the logarithmic dependence of the output voltage signal on the oxygen partial pressure. It is often advantageous to operate gasoline power piston engines with excess combustion air; this improves fuel economy and reduces hydrocarbon emissions. To maintain stable combustion away from stoichiometry, and enable engines to operate in the excess oxygen (lean burn) region several limiting-current amperometric sensors have been reported. These sensors are based on the electrochemical oxygen ion pumping of a zirconia electrolyte. They typically show reproducible limiting current plateaus with an applied voltage caused by the gas diffusion overpotential at the cathode.« less
Single Walled Carbon Nanotube Based Air Pocket Encapsulated Ultraviolet Sensor.
Kim, Sun Jin; Han, Jin-Woo; Kim, Beomseok; Meyyappan, M
2017-11-22
Carbon nanotube (CNT) is a promising candidate as a sensor material for the sensitive detection of gases/vapors, biomarkers, and even some radiation, as all these external variables affect the resistance and other properties of nanotubes, which forms the basis for sensing. Ultraviolet (UV) radiation does not impact the nanotube properties given the substantial mismatch of bandgaps and therefore, CNTs have never been considered for UV sensing, unlike the popular ZnO and other oxide nanwires. It is well-known that UV assists the adsorption/desorption characteristics of oxygen on carbon nanotubes, which changes the nanotube resistance. Here, we demonstrate a novel sensor structure encapsulated with an air pocket, where the confined air is responsible for the UV sensing mechanism and assures sensor stability and repeatability over time. In addition to the protection from any contamination, the air pocket encapsulated sensor offers negligible baseline drift and fast recovery compared to previously reported sensors. The air pocket isolated from the outside environment can act as a stationary oxygen reservoir, resulting in consistent sensor characteristics. Furthermore, this sensor can be used even in liquid environments.
The Citizen Science Toolbox: A One-Stop Resource for Air Sensor Technology
The air sensor technology market is exploding with new sensors in all kinds of forms. Developers are putting sensors in wristbands, headphones, and cell phone add-ons. Small, portable and lower-cost measurement devices using sensors are coming on the market with a wide variety of...
NASA Astrophysics Data System (ADS)
Juang, J. Y.; Sun, C. H.; Jiang, J. A.; Wen, T. H.
2017-12-01
The urban heat island effect (UHI) caused by the regional-to-global environmental changes, dramatic urbanization, and shifting in land-use compositions has becoming an important environmental issue in recent years. In the past century, the coverage of urban area in Taipei Basin has dramatically increasing by ten folds. The strengthen of UHI effect significantly enhances the frequency of warm-night effect, and strongly influences the thermal environment of the residents in the Greater Taipei Metropolitan. In addition, the urban expansions due to dramatic increasing in urban populations and traffic loading significantly impacts the air quality and causes health issue in Taipei. In this study, the main objective is to quantify and characterize the temporal and spatial distributions of thermal environmental and air quality in the Greater Taipei Metropolitan Area by using monitoring data from Central Weather Bureau, Environmental Protection Administration. In addition, in this study, we conduct the analysis on the distribution of physiological equivalent temperature in the micro scale in the metropolitan area by using the observation data and quantitative simulation to investigate how the thermal environment is influenced under different conditions. Furthermore, we establish a real-time mobile monitoring system by using wireless sensor network to investigate the correlation between the thermal environment, air quality and other environmental factors, and propose to develop the early warning system for heat stress and air quality in the metropolitan area. The results from this study can be integrated into the management and planning system, and provide sufficient and important background information for the development of smart city in the metropolitan area in the future.
CAIRSENSE Study: Real-world evaluation of low cost sensors in Denver, Colorado
Low-cost air pollution sensors are a rapidly developing field in air monitoring. In recent years, numerous sensors have been developed that can provide real-time concentration data for different air pollutants at costs accessible to individuals and non-regulatory groups. Addition...
NASA Astrophysics Data System (ADS)
Stewart, G.; Popoola, O. A.; Mead, M. I.; McKeating, S. J.; Calleja, M.; Hayes, M.; Baron, R. P.; Saffell, J.; Jones, R.
2012-12-01
In this paper we describe how low-cost, lightweight devices, which incorporate GPS and GPRS facilities and contain electrochemical sensors for carbon monoxide (CO), nitrogen monoxide (NO) and nitrogen dioxide (NO2), have been used to collect data representative of personal exposure to these important urban air pollutants. E.U. legislation has set target levels for gases thought to have adverse impacts on human health, and consequently led to a need for a more informed air pollution control policy. With many sites in the U.K. and in the rest of the E.U. still failing to meet annual targets for NO2, a need to better understand pollutant sources and behaviour has arisen. Moreover, while traditional chemiluminescence techniques provide precise measurements, the instruments are sparsely populated around urban centres and are thus limited in their ability to account for true personal exposure. Through a series of laboratory and field studies, it has been shown that electrochemical sensor nodes, when configured suitably and after post-processing of data, can provide selective, reproducible measurements, and that the devices have appropriate detection limits (at the low parts-per-billion level), as well as fast enough response times, for urban air quality studies. Both mobile nodes and their static analogues have been deployed with different aims. Static nodes have been used in dense networks in both the urban environment and in the grounds of a major international airport, as described in the partner papers of Mead et al and Bright et al. Mobile units are easily deployed in scalable networks for short-term studies on personal exposure; these studies have been carried out in a wide range of locations including Lagos, Kuala-Lumpur, London and Valencia. Data collected by both mobile and static sensor nodes illustrate the insufficiency of the existing infrastructure in accounting for both the spatial and temporal variability in air pollutants due to road traffic emissions, and thus also the potential insufficiency at quantifying the risks to health in the surrounding area. Recent campaigns with mobile sensor nodes have included attempts to probe the differences in personal exposure to gas-phase air pollutants at different heights of breathing zone and between different methods of transport.
Tao, Hua; Veetil, Suhas P; Pan, Xingchen; Liu, Cheng; Zhu, Jianqiang
2015-08-01
Air conditioning systems can lead to dynamic phase change in the laser beams of high-power laser facilities for the inertial confinement fusion, and this kind of phase change cannot be measured by most of the commonly employed Hartmann wavefront sensor or interferometry due to some uncontrollable factors, such as too large laser beam diameters and the limited space of the facility. It is demonstrated that this problem can be solved using a scheme based on modulation coherent imaging, and thus the influence of the air conditioning system on the performance of the high-power facility can be evaluated directly.
Development of a flight data acquisition system for small unmanned aircraft
NASA Astrophysics Data System (ADS)
Hood, Scott
Current developments surrounding the use of unmanned aerial vehicles have produced a need for a high quality data acquisition platform developed specifically a research environment. This work was undertaken to produce such a system that is low cost, extensible, and better supports fixed wing research through the inclusion of a custom vane based air data probe capable of measuring airspeed, angle of attack, and angle of sideslip. This was accomplished by starting with the open source Pixhawk system as the core and then modifying the device firmware and adding sensors to suit the needs of current aerospace research at OSU. An overview of each component of the system is presented, as well as a description of various firmware modifications to the stock Pixhawk system. Tests were then performed on all of the major sensors using bench testing, wind tunnel analysis, and flight maneuvers to determine the final performance of each part of the system. This research shows that all of the critical sensors on the data acquisition platform produce data acceptable for flight research. The accelerometer has been shown to have an overall tolerance of +/-0.0545 m/s², with +/-0.223 deg/s for the gyroscopic sensor, +/-1.32 hPa for the barometric sensor, +/-0.318 m/s for the airspeed sensor, +/-1.65 °C for the outside air temperature sensor, and +/-0.00115 V for the analog to digital converter. The stock calibration curve for the airspeed sensor was determined to be correct to within +/-0.5 in H2O through wind tunnel testing, and an experimental step input analysis on the flow direction vanes showed that worst case steady state error and time to damp are acceptable for the system. Power spectral density and spectral coherence analysis of flight data was used to show that the custom air data probe is capable of following the flight dynamics of a given aircraft to within a 10 percent tolerance across a range of frequencies. Finally, general performance of the system was proven using basic aircraft system identification data collection as a test case.
OpenAQ: A Platform to Aggregate and Freely Share Global Air Quality Data
NASA Astrophysics Data System (ADS)
Hasenkopf, C. A.; Flasher, J. C.; Veerman, O.; DeWitt, H. L.
2015-12-01
Thousands of ground-based air quality monitors around the world publicly publish real-time air quality data; however, researchers and the public do not have access to this information in the ways most useful to them. Often, air quality data are posted on obscure websites showing only current values, are programmatically inaccessible, and/or are in inconsistent data formats across sites. Yet, historical and programmatic access to such a global dataset would be transformative to several scientific fields, from epidemiology to low-cost sensor technologies to estimates of ground-level aerosol by satellite retrievals. To increase accessibility and standardize this disparate dataset, we have built OpenAQ, an innovative, open platform created by a group of scientists and open data programmers. The source code for the platform is viewable at github.com/openaq. Currently, we are aggregating, storing, and making publicly available real-time air quality data (PM2.5, PM10, SO2, NO2, and O3) via an Application Program Interface (API). We will present the OpenAQ platform, which currently has the following specific capabilities: A continuous ingest mechanism for some of the most polluted cities, generalizable to more sources An API providing data-querying, including ability to filter by location, measurement type and value and date, as well as custom sort options A generalized, chart-based visualization tool to explore data accessible via the API At this stage, we are seeking wider participation and input from multiple research communities in expanding our data retrieval sites, standardizing our protocols, receiving feedback on quality issues, and creating tools that can be built on top of this open platform.
Maruo, Yasuko Yamada; Nakamura, Jiro
2011-09-30
We have developed a portable device for formaldehyde monitoring with both high sensitivity and high temporal resolution, and carried out indoor air formaldehyde concentration analysis. The absorbance difference of the sensor element was measured in the monitoring device at regular intervals of, for example, one hour or 30 min, and the result was converted into the formaldehyde concentration. This was possible because we found that the lutidine derivative that was formed as a yellow product of the reaction between 1-phenyl-1,3-butandione and formaldehyde was stable in porous glass for at least six months. We estimated the reaction rate and to be 0.049 min(-1) and the reaction occurred quickly enough for us to monitor hourly changes in the formaldehyde concentration. The detection limit was 5 μg m(-3) h. We achieved hourly formaldehyde monitoring using the developed device under several indoor conditions, and estimated the air exchange rate and formaldehyde adsorption rate, which we adopted as a new term in the mass balance equation for formaldehyde, in one office. Copyright © 2011 Elsevier B.V. All rights reserved.
An expert system/ion trap mass spectrometry approach for life support systems monitoring
NASA Technical Reports Server (NTRS)
Palmer, Peter T.; Wong, Carla M.; Yost, Richard A.; Johnson, Jodie V.; Yates, Nathan A.; Story, Michael
1992-01-01
Efforts to develop sensor and control system technology to monitor air quality for life support have resulted in the development and preliminary testing of a concept based on expert systems and ion trap mass spectrometry (ITMS). An ITMS instrument provides the capability to identify and quantitate a large number of suspected contaminants at trace levels through the use of a variety of multidimensional experiments. An expert system provides specialized knowledge for control, analysis, and decision making. The system is intended for real-time, on-line, autonomous monitoring of air quality. The key characteristics of the system, performance data and analytical capabilities of the ITMS instrument, the design and operation of the expert system, and results from preliminary testing of the system for trace contaminant monitoring are described.
Groß, Andrea; Beulertz, Gregor; Marr, Isabella; Kubinski, David J.; Visser, Jaco H.; Moos, Ralf
2012-01-01
The accumulating-type (or integrating-type) NOx sensor principle offers two operation modes to measure low levels of NOx: The direct signal gives the total amount dosed over a time interval and its derivative the instantaneous concentration. With a linear sensor response, no baseline drift, and both response times and recovery times in the range of the gas exchange time of the test bench (5 to 7 s), the integrating sensor is well suited to reliably detect low levels of NOx. Experimental results are presented demonstrating the sensor’s integrating properties for the total amount detection and its sensitivity to both NO and to NO2. We also show the correlation between the derivative of the sensor signal and the known gas concentration. The long-term detection of NOx in the sub-ppm range (e.g., for air quality measurements) is discussed. Additionally, a self-adaption of the measurement range taking advantage of the temperature dependency of the sensitivity is addressed. PMID:22736980
NASA Astrophysics Data System (ADS)
Michel, A. P.; Liu, P. Q.; Yeung, J. K.; Zhang, Y.; Baeck, M. L.; Pan, X.; Dong, H.; Wang, Z.; Smith, J. A.; Gmachl, C. F.
2009-05-01
The 2008 Olympic Games focused attention on the air quality of Beijing, China and served as an important test-bed for developing, deploying, and testing new technologies for analysis of air quality and regional climate in urban environments. Poor air quality in urban locations has a significant detrimental effect on the health of residents while also impacting both regional and global climate change. As a result, there exists a great need for highly sensitive trace gas sensors for studying the atmosphere of the urban environment. Open-path remote sensors are of particular interest as they can obtain data on spatial scales similar to those used in regional climate models. Quantum cascade lasers (QCLs) can be designed for operation in the mid-infrared (mid-IR) with a central wavelength anywhere between 3 to 24 μm and made tunable over a wavelength interval of over 0.1 μm. The Quantum Cascade Laser Open-Path System (QCLOPS) is a mid-infrared laser absorption spectrometer that uses a tunable, thermoelectrically cooled, pulsed Daylight Solutions Inc. QCL for measurement of trace gases. The system is aimed at applications with path lengths ranging from approximately 0.1 to 1.0 km. The system is designed to continuously monitor multiple trace gases [water vapor (H2O), ozone (O3), ammonia (NH3), and carbon dioxide (CO2)] in the lower atmosphere. A field campaign from July to September 2008 in Beijing used QCLOPS to study trace gas concentrations before, during, and after the Olympic Games in an effort to capture changes induced by emissions reduction methods. QCLOPS was deployed at the Institute of Atmospheric Physics - Chinese Academy of Sciences on the roof of a two-story building, at an approximate distance of 2 miles from the Olympic National Stadium ("The Bird's Nest.") QCLOPS operated with an open-path round trip distance of approximately 75 m. The system ran with minimal human interference, twenty-four hours per day for the full campaign period. In order to collect data over numerous absorption peaks belonging to the target gases of H2O, NH3, O3, and CO2, measurements were made at 317 different wavelengths within the full tuning range of the laser (1020 - 1070 cm-1). We present the design of this novel sensor which was successfully built, deployed, and operated with minimal operator intervention for the three month field campaign period. Furthermore, we present the results of the field campaign and the capabilities of the QCLOPS system to measure fluctuations of the trace gases at parts-per-billion levels. The time series data illustrate the changing levels of the trace gases over the campaign period. In addition, data from commercial sensors simultaneously deployed at the field site are presented as a validation of the capabilities of the QCLOPS system. This work was supported by MIRTHE (NSF-ERC #EEC-0540832).
Using Arduinos and 3D-printers to Build Research-grade Weather Stations and Environmental Sensors
NASA Astrophysics Data System (ADS)
Ham, J. M.
2013-12-01
Many plant, soil, and surface-boundary-layer processes in the geosphere are governed by the microclimate at the land-air interface. Environmental monitoring is needed at smaller scales and higher frequencies than provided by existing weather monitoring networks. The objective of this project was to design, prototype, and test a research-grade weather station that is based on open-source hardware/software and off-the-shelf components. The idea is that anyone could make these systems with only elementary skills in fabrication and electronics. The first prototypes included measurements of air temperature, humidity, pressure, global irradiance, wind speed, and wind direction. The best approach for measuring precipitation is still being investigated. The data acquisition system was deigned around the Arduino microcontroller and included an LCD-based user interface, SD card data storage, and solar power. Sensors were sampled at 5 s intervals and means, standard deviations, and maximum/minimums were stored at user-defined intervals (5, 30, or 60 min). Several of the sensor components were printed in plastic using a hobby-grade 3D printer (e.g., RepRap Project). Both passive and aspirated radiation shields for measuring air temperature were printed in white Acrylonitrile Butadiene Styrene (ABS). A housing for measuring solar irradiance using a photodiode-based pyranometer was printed in opaque ABS. The prototype weather station was co-deployed with commercial research-grade instruments at an agriculture research unit near Fort Collins, Colorado, USA. Excellent agreement was found between Arduino-based system and commercial weather instruments. The technology was also used to support air quality research and automated air sampling. The next step is to incorporate remote access and station-to-station networking using Wi-Fi, cellular phone, and radio communications (e.g., Xbee).
NASA Technical Reports Server (NTRS)
Gregory, G. L.; Beck, S. M.; Mathis, J. J., Jr.
1981-01-01
In situ correlative measurements were obtained with a NASA aircraft in support of two NASA airborne remote sensors participating in the Environmental Protection Agency's 1980persistent elevated pollution episode (PEPE) and Northeast regional oxidant study (NEROS) field program in order to provide data for evaluating the capability of two remote sensors for measuring mixing layer height, and ozone and aerosol concentrations in the troposphere during the 1980 PEPE/NEROS program. The in situ aircraft was instrumented to measure temperature, dewpoint temperature, ozone concentrations, and light scattering coefficient. In situ measurements for ten correlative missions are given and discussed. Each data set is presented in graphical and tabular format aircraft flight plans are included.
77 FR 11789 - Airworthiness Directives; The Boeing Company Airplanes
Federal Register 2010, 2011, 2012, 2013, 2014
2012-02-28
...-icing system for the angle of attack sensor, the total air temperature, and the pitot probes. We are proposing this AD to prevent ice from forming on air data system sensors and consequent loss of or... receive about this proposed AD. Discussion The air data sensor heating system, when ON, heats the pitot...
77 FR 73282 - Airworthiness Directives; The Boeing Company Airplanes
Federal Register 2010, 2011, 2012, 2013, 2014
2012-12-10
... system for the angle of attack sensor, the total air temperature, and the pitot probes. We are issuing this AD to prevent ice from forming on air data system sensors and consequent loss of or misleading... angle of attack sensor, the total air temperature, and the pitot probes. Actions Since Issuance of NPRM...
Low-Cost Fiber Optic Pressure Sensor
Sheem, Sang K.
2004-05-18
The size and cost of fabricating fiber optic pressure sensors is reduced by fabricating the membrane of the sensor in a non-planar shape. The design of the sensors may be made in such a way that the non-planar membrane becomes a part of an air-tight cavity, so as to make the membrane resilient due to the air-cushion effect of the air-tight cavity. Such non-planar membranes are easier to make and attach.
Low-Cost Fiber Optic Pressure Sensor
Sheem, Sang K.
2003-07-22
The size and cost of fabricating fiber optic pressure sensors is reduced by fabricating the membrane of the sensor in a non-planar shape. The design of the sensors may be made in such a way that the non-planar membrane becomes a part of an air-tight cavity, so as to make the membrane resilient due to the air-cushion effect of the air-tight cavity. Such non-planar membranes are easier to make and attach.
NASA Astrophysics Data System (ADS)
Nowlan, Caroline R.; Liu, Xiong; Leitch, James W.; Chance, Kelly; González Abad, Gonzalo; Liu, Cheng; Zoogman, Peter; Cole, Joshua; Delker, Thomas; Good, William; Murcray, Frank; Ruppert, Lyle; Soo, Daniel; Follette-Cook, Melanie B.; Janz, Scott J.; Kowalewski, Matthew G.; Loughner, Christopher P.; Pickering, Kenneth E.; Herman, Jay R.; Beaver, Melinda R.; Long, Russell W.; Szykman, James J.; Judd, Laura M.; Kelley, Paul; Luke, Winston T.; Ren, Xinrong; Al-Saadi, Jassim A.
2016-06-01
The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 molecules
Indrehus, Oddny; Aralt, Tor Tybring
2005-04-01
Aerosol, NO and CO concentration, temperature, air humidity, air flow and number of running ventilation fans were measured by continuous analysers every minute for a whole week for six different one-week periods spread over ten months in 2001 and 2002 at measuring stations in the 7860 m long tunnel. The ventilation control system was mainly based on aerosol measurements taken by optical scatter sensors. The ventilation turned out to be satisfactory according to Norwegian air quality standards for road tunnels; however, there was some uncertainty concerning the NO2 levels. The air humidity and temperature inside the tunnel were highly influenced by the outside metrological conditions. Statistical models for NO concentration were developed and tested; correlations between predicted and measured NO were 0.81 for a partial least squares regression (PLS1) model based on CO and aerosol, and 0.77 for a linear regression model based only on aerosol. Hence, the ventilation control system should not solely be based on aerosol measurements. Since NO2 is the hazardous polluter, modelling NO2 concentration rather than NO should be preferred in any further optimising of the ventilation control.
Laser-Based and Ultra-Portable Gas Sensor for Indoor and Outdoor Formaldehyde (HCHO) Monitoring
NASA Astrophysics Data System (ADS)
Shutter, J. D.; Allen, N.; Paul, J.; Thiebaud, J.; So, S.; Scherer, J. J.; Keutsch, F. N.
2017-12-01
While used as a key tracer of oxidative chemistry in the atmosphere, formaldehyde (HCHO) is also a known human carcinogen and is listed and regulated by the United States EPA as a hazardous air pollutant. Combustion processes and photochemical oxidation of volatile organic compounds (VOCs) are the major outdoor sources of HCHO, and building materials and household products are ubiquitous sources of indoor HCHO. Due to the ease with which humans can be exposed to HCHO, it is imperative to monitor levels of both indoor and outdoor HCHO exposure in both short and long-term studies.High-quality direct and indirect methods of quantifying HCHO mixing ratios exist, but instrument size and user-friendliness can make them cumbersome or impractical for certain types of indoor and long-term outdoor measurements. In this study, we present urban HCHO measurements by using a new, commercially-available, ppbv-level accurate HCHO gas sensor (Aeris Technologies' MIRA Pico VOC Laser-Based Gas Analyzer) that is highly portable (29 cm x 20 cm x 10 cm), lightweight (3 kg), easy-to-use, and has low power (15 W) consumption. Using an ultra-compact multipass cell, an absorption path length of 13 m is achieved, resulting in a sensor capable of achieving ppbv/s sensitivity levels with no significant spectral interferences.To demonstrate the utility of the gas sensor for emissions measurements, a GPS was attached to the sensor's housing in order to map mobile HCHO measurements in real-time around the Boston, Massachusetts, metro area. Furthermore, the sensor was placed in residential and industrial environments to show its usefulness for indoor and outdoor pollution measurements. Lastly, we show the feasibility of using the HCHO sensor (or a network of them) in long-term monitoring stations for hazardous air pollutants.
Extrinsic fiber optic displacement sensors and displacement sensing systems
Murphy, K.A.; Gunther, M.F.; Vengsarkar, A.M.; Claus, R.O.
1994-04-05
An extrinsic Fizeau fiber optic sensor comprises a single-mode fiber, used as an input/output fiber, and a multimode fiber, used purely as a reflector, to form an air gap within a silica tube that acts as a Fizeau cavity. The Fresnel reflection from the glass/air interface at the front of the air gap (reference reflection) and the reflection from the air/glass interface at the far end of the air gap (sensing reflection) interfere in the input/output fiber. The two fibers are allowed to move in the silica tube, and changes in the air gap length cause changes in the phase difference between the reference reflection and the sensing reflection. This phase difference is observed as changes in intensity of the light monitored at the output arm of a fused biconical tapered coupler. The extrinsic Fizeau fiber optic sensor behaves identically whether it is surface mounted or embedded, which is unique to the extrinsic sensor in contrast to intrinsic Fabry-Perot sensors. The sensor may be modified to provide a quadrature phase shift extrinsic Fizeau fiber optic sensor for the detection of both the amplitude and the relative polarity of dynamically varying strain. The quadrature light signals may be generated by either mechanical or optical means. A plurality of the extrinsic sensors may connected in cascade and multiplexed to allow monitoring by a single analyzer. 14 figures.
Extrinsic fiber optic displacement sensors and displacement sensing systems
Murphy, Kent A.; Gunther, Michael F.; Vengsarkar, Ashish M.; Claus, Richard O.
1994-01-01
An extrinsic Fizeau fiber optic sensor comprises a single-mode fiber, used as an input/output fiber, and a multimode fiber, used purely as a reflector, to form an air gap within a silica tube that acts as a Fizeau cavity. The Fresnel reflection from the glass/air interface at the front of the air gap (reference reflection) and the reflection from the air/glass interface at the far end of the air gap (sensing reflection) interfere in the input/output fiber. The two fibers are allowed to move in the silica tube, and changes in the air gap length cause changes in the phase difference between the reference reflection and the sensing reflection. This phase difference is observed as changes in intensity of the light monitored at the output arm of a fused biconical tapered coupler. The extrinsic Fizeau fiber optic sensor behaves identically whether it is surface mounted or embedded, which is unique to the extrinsic sensor in contrast to intrinsic Fabry-Perot sensors. The sensor may be modified to provide a quadrature phase shift extrinsic Fizeau fiber optic sensor for the detection of both the amplitude and the relative polarity of dynamically varying strain. The quadrature light signals may be generated by either mechanical or optical means. A plurality of the extrinsic sensors may connected in cascade and multiplexed to allow monitoring by a single analyzer.
The deployment of carbon monoxide wireless sensor network (CO-WSN) for ambient air monitoring.
Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C; Khang, Soon-Jai
2014-06-16
Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011-2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1-1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring.
NASA Astrophysics Data System (ADS)
Ryerson, T. B.
2009-12-01
CalNex is a major field study planned for May and June of 2010. The study, led by NOAA and the California Air Resources Board, coordinates many interagency partners with independent but complementary capabilities and goals. Observations from surface-, aircraft-, ship-, and space-based sensors, along with Lagrangian and Eulerian modeling studies, will be used to extend previous studies and contribute new data and understanding to issues relevant to climate change and air quality in California. This overview will present the integrated approach that will be taken in CalNex, utilizing long-term surface observations, instrumented tall towers, several major intensive ground sites, a network of daily ozonesonde launches, a radar profiling network, multiple instrumented research aircraft, a research vessel, and retrievals from several satellites. The primary CalNex science questions and experimental strategies to address them will be presented, with illustrations and data examples taken from recent field projects in California to provide context for the upcoming study.
This article summarizes the findings from the EPA's Apps and Sensors for Air Pollution Workshop that was held March 26-27 of 2012. The workshop brought together researchers, developers, and community-based groups who have been working with sensors and apps in a variety of settin...
Assessing the Value of Enhancing AirNow Data with NASA Satellite Data
NASA Astrophysics Data System (ADS)
Pasch, A. N.; Burke, B.; Huang, S.; Dye, T.; Dawes, S. S.; DeWinter, J. L.; Zahn, P. H.; Haderman, M.; Szykman, J.; White, J. E.; Dickerson, P.; van Donkelaar, A.; Martin, R.
2013-12-01
We will describe the methodology and findings from a study that addressed how satellite-enhanced air quality information provided through the U.S. Environmental Protection Agency's (EPA) AirNow Satellite Data Processor (ASDP) program could contribute to greater socioeconomic benefits. This study was funded by the National Aeronautics and Space Administration (NASA) and conducted, in partnership with the EPA, by the Center for Technology in Government at the University at Albany (CTG) and Sonoma Technology, Inc. (STI). AirNow is the national repository of real-time air quality data and forecasts for the United States. While mainly a public outreach and awareness tool, AirNow relies on the same network of ground-based air quality monitors that is used by federal, state, local, and tribal governments throughout the United States. Extensive as the monitoring network is, considerable gaps exist in certain parts of the United States. Even areas with monitors considered adequate for regulatory purposes can lack information needed to resolve localized air quality issues or give forecasters sufficient confidence about the potential air quality impact of specific events. Monitors are expensive to deploy and maintain; thus, EPA is seeking other ways to improve coverage and detail. Satellite-estimated data can provide information for many places where ground monitors do not exist, and supplement ground monitors, providing additional information for use in analysis and forecasting. ASDP uses satellite-derived estimates for fine-particle pollution (PM2.5) and provides coverage for a small window of time during the day. As satellite capabilities improve in terms of different types of sensors and increased coverage throughout the day, the ASDP program is prepared to extend its scope to additional pollutants and provide greater enhancements to the ground-based networks. In this study, CTG assessed the socioeconomic benefits of air quality data at a community level through three case studies in the Denver, Atlanta, and Kansas City regions by interviewing people at EPA regional offices, state environmental and public health agencies, local public health authorities, regional planning and non-profit outreach organizations, and universities. The interviews focused on the existing uses of air quality information and the potential value of incorporating NASA satellite-enhanced AirNow data to support and enhance the missions of the organizations interviewed. STI analyzed the economic benefit of using satellite data to fill in gaps in the current air quality monitoring network used to provide information to the public. This presentation will discuss how the findings can be used to improve estimation of the socioeconomic benefits derived from Earth observation science in policy and management decisions.
Overview of Emerging Air Sensors
These slides will be presented at the 2014 National Ambient Air Monitoring Conference in Atlanta, GA during August 11-15, 2014. The goal is to provide an overview of air sensor technology and the audience will be primarily state air monitoring agencies and EPA Regions.
NASA Astrophysics Data System (ADS)
Land, Phillip; Majumdar, Arun K.
2016-05-01
This paper describes a new concept of mitigating signal distortions caused by random air-water interface using an adaptive optics (AO) system. This is the first time the concept of using an AO for mitigating the effects of distortions caused mainly by a random air-water interface is presented. We have demonstrated the feasibility of correcting the distortions using AO in a laboratory water tank for investigating the propagation effects of a laser beam through an airwater interface. The AO system consisting of a fast steering mirror, deformable mirror, and a Shack-Hartmann Wavefront Sensor for mitigating surface water distortions has a unique way of stabilizing and aiming a laser onto an object underneath the water. Essentially the AO system mathematically takes the complex conjugate of the random phase caused by air-water interface allowing the laser beam to penetrate through the water by cancelling with the complex conjugates. The results show the improvement of a number of metrics including Strehl ratio, a measure of the quality of optical image formation for diffraction limited optical system. These are the first results demonstrating the feasibility of developing a new sensor system such as Laser Doppler Vibrometer (LDV) utilizing AO for mitigating surface water distortions.
Guide to Camouflage for DARCOM Equipment Developers
1978-04-29
the trails by dragging devices, etc., can delay recognition of a tracked- veicle trail. A missile system, having fixed physical characteristics which...systems applicable to surface-to-air, air-to-air, and air-to-surface missiles. Sensors in the 0.2 to 0.4 and 1.0 to 5.0 micron bands are hybrid ...a wide variety of ultra- violet, visible and near infrared sensor systems. Actual sensors are hybrid computer controlled in six degrees-of-freedom
High-performance optical projection controllable ZnO nanorod arrays for microweighing sensors.
Wang, Hongbo; Jiang, Shulan; Zhang, Lei; Yu, Bingjun; Chen, Duoli; Yang, Weiqing; Qian, Linmao
2018-03-08
Optical microweighing sensors are an essential component of micro-force measurements in physical, chemical, and biological detection fields, although, their limited detection range (less than 15°) severely hinders their wide application. Such a limitation is mainly attributed to the essential restrictions of traditional light reflection and optical waveguide modes. Here, we report a high-performance optical microweighing sensor based on the synergistic effects of both a new optical projection mode and a ZnO nanorod array sensor. Ascribed to the unique configuration design of this sensing method, this optical microweighing sensor has a wide detection range (more than 80°) and a high sensitivity of 90 nA deg -1 , which is much larger than that of conventional microcantilever-based optical microweighing sensors. Furthermore, the location of the UV light source can be adjusted within a few millimeters, meaning that the microweighing sensor does not need repetitive optical calibration. More importantly, for low height and small incident angles of the UV light source, we can obtain highly sensitive microweighing properties on account of the highly sensitive ZnO nanorod array-based UV sensor. Therefore, this kind of large detection range, non-contact, and non-destructive microweighing sensor has potential applications in air quality monitoring and chemical and biological detection.
Ozone, ozone production rates and NO observations on the outskirts of Quito, Ecuador
NASA Astrophysics Data System (ADS)
Cazorla, M.
2014-12-01
Air quality measurements of ambient ozone, ozone production rates and nitrogen oxides, in addition to baseline meterology observations, are being taken at a recently built roof-top facility on the campus of Universidad San Francisco de Quito, in Ecuador. The measurement site is located in Cumbayá, a densely populated valley adjacent to the city of Quito. Time series of ozone and NO are being obtained with commercial air quality monitors. Rush-hour peaks of NO, above 100 ppb, have been observed, while daytime ozone levels are low. In addition, ozone production rates are being measured with the Ecuadorian version of the MOPS, Measurement of Ozone Production Sensor, originally built at Penn State University in 2010. NO and ozone observations and test results of measured ozone production rates will be presented.
Optimization of Sensor Monitoring Strategies for Emissions
NASA Astrophysics Data System (ADS)
Klise, K. A.; Laird, C. D.; Downey, N.; Baker Hebert, L.; Blewitt, D.; Smith, G. R.
2016-12-01
Continuous or regularly scheduled monitoring has the potential to quickly identify changes in air quality. However, even with low-cost sensors, only a limited number of sensors can be placed to monitor airborne pollutants. The physical placement of these sensors and the sensor technology used can have a large impact on the performance of a monitoring strategy. Furthermore, sensors can be placed for different objectives, including maximum coverage, minimum time to detection or exposure, or to quantify emissions. Different objectives may require different monitoring strategies, which need to be evaluated by stakeholders before sensors are placed in the field. In this presentation, we outline methods to enhance ambient detection programs through optimal design of the monitoring strategy. These methods integrate atmospheric transport models with sensor characteristics, including fixed and mobile sensors, sensor cost and failure rate. The methods use site specific pre-computed scenarios which capture differences in meteorology, terrain, concentration averaging times, gas concentration, and emission characteristics. The pre-computed scenarios become input to a mixed-integer, stochastic programming problem that solves for sensor locations and types that maximize the effectiveness of the detection program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Patel, Sameer; Li, Jiayu; Pandey, Apoorva; Pervez, Shamsh; Chakrabarty, Rajan K; Biswas, Pratim
2017-01-01
Many households use solid fuels for cooking and heating purposes. There is currently a knowledge gap in our understanding of the variations in indoor air quality throughout the household as most of the studies focus on the areas in the close proximity of the cookstove. A low-cost wireless particulate matter (PM) sensor network was developed and deployed in households in Raipur, India to establish the spatio-temporal variation of PM concentrations. The data from multiple sensors were acquired in real-time with a wireless system. Data collected from the sensors agreed well (R 2 =0.713) with the reference data collected from a commercially available instrument. Low spatial variability was observed within the kitchen due to its small size and poor ventilation - a common feature of most rural Indian kitchens. Due to insufficient ventilation from open doors and windows, high PM concentrations similar to those found in the kitchen were also found in the adjoining rooms. The same household showed significantly different post-extinguished cookstove PM concentration decay rates (0.26mg/m 3 -min and 0.87mg/m 3 -min) on different days, owing to varying natural air exchange rates (7.68m 3 /min and 37.40m 3 /min). Copyright © 2016 Elsevier Inc. All rights reserved.
Airborne mapping of Seoul's atmosphere: Trace gas measurements from GeoTASO during KORUS-AQ
NASA Astrophysics Data System (ADS)
Nowlan, C. R.; Al-Saadi, J. A.; Castellanos, P.; Chance, K.; Gonzalez Abad, G.; Janz, S. J.; Judd, L.; Kowalewski, M. G.; Liu, X.
2017-12-01
The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) instrument is a pushbroom airborne remote sensing instrument capable of making measurements of air quality and ocean color using backscattered UV and visible light. GeoTASO is an airborne test-bed for the upcoming Tropospheric Emissions: Monitoring of Pollution (TEMPO) and Geostationary Environment Monitoring Spectrometer (GEMS) geostationary satellite missions, which will measure air quality over North America and Asia, respectively. GeoTASO also acts as a satellite analogue during field campaigns. GeoTASO flew on the NASA Langley Research Center UC-12 aircraft during the Korea-United States Air Quality Study in May-June 2016, collecting spectra over South Korea during 30 flights over 19 flight days. These observations can be used to derive 2-D maps of tropospheric trace gases including ozone, nitrogen dioxide, sulfur dioxide, formaldehyde, nitrous acid and glyoxal below the aircraft at spatial resolutions between 250 m x 250 m and 1 km x 1 km, depending on the gas. We present spatially resolved trace gas retrievals over Seoul and its surrounding industrial regions, and comparisons with correlative satellite and campaign data.
The expanding scope of air pollution monitoring can facilitate sustainable development.
Knox, Andrew; Mykhaylova, Natalia; Evans, Greg J; Lee, Colin J; Karney, Bryan; Brook, Jeffrey R
2013-03-15
This paper explores technologies currently expanding the physical scope of air pollution monitoring and their potential contributions to the assessment of sustainable development. This potential lies largely in the ability of these technologies to address issues typically on the fringe of the air pollution agenda. Air pollution monitoring tends to be primarily focused on human health, and largely neglects other aspects of sustainable development. Sensor networks, with their relatively inexpensive monitoring nodes, allow for monitoring with finer spatiotemporal resolution. This resolution can support more conclusive studies of air pollution's effect on socio-ecological justice and human quality of life. Satellite observation of air pollution allows for wider geographical scope, and in doing so can facilitate studies of air pollution's effects on natural capital and ecosystem resilience. Many air pollution-related aspects of the sustainability of development in human systems are not being given their due attention. Opportunities exist for air pollution monitoring to attend more to these issues. Improvements to the resolution and scale of monitoring make these opportunities realizable. Copyright © 2012 Elsevier B.V. All rights reserved.
The CEOS Atmospheric Composition Constellation: Enhancing the Value of Space-Based Observations
NASA Technical Reports Server (NTRS)
Eckman, Richard; Zehner, Claus; Al-Saadi, Jay
2015-01-01
The Committee on Earth Observation Satellites (CEOS) coordinates civil space-borne observations of the Earth. Participating agencies strive to enhance international coordination and data exchange and to optimize societal benefit. In recent years, CEOS has collaborated closely with the Group on Earth Observations (GEO) in implementing the Global Earth Observing System of Systems (GEOSS) space-based objectives. The goal of the CEOS Atmospheric Composition Constellation (ACC) is to collect and deliver data to improve monitoring, assessment and predictive capabilities for changes in the ozone layer, air quality and climate forcing associated with changes in the environment through coordination of existing and future international space assets. A project to coordinate and enhance the science value of a future constellation of geostationary sensors measuring parameters relevant to air quality supports the forthcoming European Sentinel-4, Korean GEMS, and US TEMPO missions. Recommendations have been developed for harmonization to mutually improve data quality and facilitate widespread use of the data products.
On Target: Organizing and Executing the Strategic Air Campaign Against Iraq
2002-01-01
possession, use, sale, creation or display of any porno graphic photograph, videotape, movie, drawing, book, or magazine or similar represen- tations. This...forward-looking infrared (FLIR) sensor to create daylight-quality video images of terrain and utilized terrain-following radar to enable the aircraft to...The Black Hole Planners had pleaded with CENTAF Intel to provide them with photos of targets, provide additional personnel to analyze PGM video
1 million-Q optomechanical microdisk resonators for sensing with very large scale integration
NASA Astrophysics Data System (ADS)
Hermouet, M.; Sansa, M.; Banniard, L.; Fafin, A.; Gely, M.; Allain, P. E.; Santos, E. Gil; Favero, I.; Alava, T.; Jourdan, G.; Hentz, S.
2018-02-01
Cavity optomechanics have become a promising route towards the development of ultrasensitive sensors for a wide range of applications including mass, chemical and biological sensing. In this study, we demonstrate the potential of Very Large Scale Integration (VLSI) with state-of-the-art low-loss performance silicon optomechanical microdisks for sensing applications. We report microdisks exhibiting optical Whispering Gallery Modes (WGM) with 1 million quality factors, yielding high displacement sensitivity and strong coupling between optical WGMs and in-plane mechanical Radial Breathing Modes (RBM). Such high-Q microdisks with mechanical resonance frequencies in the 102 MHz range were fabricated on 200 mm wafers with Variable Shape Electron Beam lithography. Benefiting from ultrasensitive readout, their Brownian motion could be resolved with good Signal-to-Noise ratio at ambient pressure, as well as in liquid, despite high frequency operation and large fluidic damping: the mechanical quality factor reduced from few 103 in air to 10's in liquid, and the mechanical resonance frequency shifted down by a few percent. Proceeding one step further, we performed an all-optical operation of the resonators in air using a pump-probe scheme. Our results show our VLSI process is a viable approach for the next generation of sensors operating in vacuum, gas or liquid phase.
Mapping Atmospheric Ammonia Emissions Using a Mobile Quantum Cascade Laser-based Open-path Sensor
NASA Astrophysics Data System (ADS)
Sun, K.; Tao, L.; Miller, D. J.; Khan, M. A.; Zondlo, M. A.
2012-12-01
Ammonia (NH3) is a key precursor to atmospheric fine particulate matter, with strong implications for regional air quality and global climate change. Despite the importance of atmospheric ammonia, its spatial/temporal variation is poorly characterized, and the knowledge of its sources, sinks, and transport is severely limited. Existing measurements suggest that traffic exhaust may provide significant amounts of ammonia in urban areas, which cause greater impacts on particulate matter formation and urban air quality. To capture the spatial and temporal variation of ammonia emissions, a portable, low power sensor with high time resolution is necessary. We have developed a portable open-path ammonia sensor with a detection limit of 0.5 ppbv ammonia for 1 s measurements. The sensor has a power consumption of about 60 W and is capable of running on a car battery continuously for 24 hours. An additional laser has been coupled to the sensor to yield concurrent N2O and CO measurements as tracers for determining various sources. The overall sensor prototype fits on a 60 cm × 20 cm aluminum breadboard. Roadside measurements indicated NH3/CO emission ratios of 4.1±5.4 ppbv/ppmv from a fleet of 320 vehicles, which agree with existing on-ramp measurements. Urban measurements in the Baltimore and Washington, DC metropolitan areas have shown significant ammonia mixing ratios concurrent with carbon monoxide levels from the morning and evening rush hours. On-road measurements of our open-path sensor have also been performed continuously from the Midwest to Princeton, NJ including urban areas such as Pittsburgh, tunnels, and relatively clean conditions. The emission ratios of ammonia against CO and/or CO2 help identify the sources and amounts of both urban and agricultural ammonia emissions. Preliminary data from both spatial mapping, monitoring, and vehicle exhaust measurements suggest that urban ammonia emissions from fossil fuel combustion are significant and may provide an unrecognized source in the atmospheric ammonia budget. Ongoing efforts include spatial mapping of ammonia and other tracers in the New York City and Philadelphia metropolitan areas. Further comparison with TES satellite ammonia retrieval will help to put the measurements into a larger geographical and temporal context.
The effect of ego-motion on environmental monitoring.
Lerner, Uri; Yacobi, Tamar; Levy, Ilan; Moltchanov, Sharon A; Cole-Hunter, Tom; Fishbain, Barak
2015-11-15
Air pollution has a proven impact on public health. Currently, pollutant levels are obtained by high-priced, sizeable, stationary Air Quality Monitoring (AQM) stations. Recent developments in sensory and communication technologies have made relatively low-cost, micro-sensing units (MSUs) feasible. Their lower power consumption and small size enable mobile sensing, deploying single or multiple units simultaneously. Recent studies have reported on measurements acquired by mobile MSUs, mounted on cars, bicycles and pedestrians. While these modes of transportation inherently present different velocity and acceleration regimes, the effect of the sensors' varying movement characteristics have not been previously accounted for. This research assesses the impact of sensor's motion on its functionality through laboratory measurements and a field campaign. The laboratory setup consists of a wind tunnel to assess the effect of air flow on the measurements of nitrogen dioxide and ozone at different velocities in a controlled environment, while the field campaign is based on three cars mounted with MSUs, measuring pollutants and environmental variables at different traveling speeds. In both experimental designs we can regard the MSUs as a moving object in the environment, i.e. having a distinct ego-motion. The results show that MSU's behavior is highly affected by variation in speed and sensor placement with respect to direction of movement, mainly due to the physical properties of installed sensors. This strongly suggests that any future design of MSU must account for the speed effect from the design stage all the way through deployment and results analysis. This is the first report examining the influence of airflow variations on MSU's ability to accurately measure pollutant levels. Copyright © 2015 Elsevier B.V. All rights reserved.
The paper give results of a characterization of ozone emissions from air cleaners equipped with ozone generators and sensor and feedback control circuitry. Ozone emission rates of several consumer appliances, marketed as indoor air treatment or air purification systems, were det...
Enabling Smart Air Conditioning by Sensor Development: A Review
Cheng, Chin-Chi; Lee, Dasheng
2016-01-01
The study investigates the development of sensors, in particular the use of thermo-fluidic sensors and occupancy detectors, to achieve smart operation of air conditioning systems. Smart operation refers to the operation of air conditioners by the reinforcement of interaction to achieve both thermal comfort and energy efficiency. Sensors related to thermal comfort include those of temperature, humidity, and pressure and wind velocity anemometers. Improvements in their performance in the past years have been studied by a literature survey. Traditional occupancy detection using passive infra-red (PIR) sensors and novel methodologies using smartphones and wearable sensors are both discussed. Referring to the case studies summarized in this study, air conditioning energy savings are evaluated quantitatively. Results show that energy savings of air conditioners before 2000 was 11%, and 30% after 2000 by the integration of thermo-fluidic sensors and occupancy detectors. By utilizing wearable sensing to detect the human motions, metabolic rates and related information, the energy savings can reach up to 46.3% and keep the minimum change of predicted mean vote (∆PMV→0), which means there is no compromise in thermal comfort. This enables smart air conditioning to compensate for the large variations from person to person in terms of physiological and psychological satisfaction, and find an optimal temperature for everyone in a given space. However, this tendency should be evidenced by more experimental results in the future. PMID:27916906
NASA Astrophysics Data System (ADS)
Jung, J.; Choi, Y.; Souri, A.; Jeon, W.
2017-12-01
Particle matter(PM) has played a significantly deleterious role in affecting human health and climate. Recently, continuous high concentrations of PM in Korea attracted public attention to this critical issue, and the Korea-United States Air Quality Study(KORUS-AQ) campaign in 2016 was conducted to investigate the causes. For this study, we adjusted the initial conditions in the chemical transport model(CTM) to improve its performance over Korean Peninsula during KORUS-AQ period, using the campaign data to evaluate our model performance. We used the Optimal Interpolation(OI) approach and used hourly surface air quality measurement data from the Air Quality Monitoring Station(AQMS) by NIER and the aerosol optical depth(AOD) measured by a GOCI sensor from the geostationary orbit onboard the Communication Ocean and Meteorological Satellite(COMS). The AOD at 550nm has a 6km spatial resolution and broad coverage over East Asia. After assimilating the surface air quality observation data, the model accuracy significantly improved compared to base model result (without assimilation). It reported very high correlation value (0.98) and considerably decreased mean bias. Especially, it well captured some high peaks which was underpredicted by the base model. To assimilate satellite data, we applied AOD scaling factors to quantify each specie's contribution to total PM concentration and find-mode fraction(FMF) to define vertical distribution. Finally, the improvement showed fairly good agreement.
An Investigation of Air Quality Surrounding Lake Merritt in Oakland, California
NASA Astrophysics Data System (ADS)
Ararso, I.; Casino, N.; Chen, B.; Johnson, J.; Koerber, K. W.; Lau, S.; Truisi, V.; Yanez, M.; Yeung, A.; Unigarro, M.; Vue, G.; Garduno, L.; Cuff, K.
2005-12-01
Lake Merritt is a naturally occurring inlet from the San Francisco Bay that was converted into an urban lake near downtown Oakland in 1860. The Lake itself is located within the Lake Merritt Park and Wildlife Refuge, home to over 90 species of migrating waterfowl, as well as a variety of aquatic wildlife. Its close proximity to downtown, several busy roads, and two major highways makes Lake Merritt a popular destination that is easily accessible to Oakland residents, but also puts it at risk for impaired air quality due to automobile exhaust. In an effort to assess air quality near Lake Merritt, we measured percent oxygen and carbon dioxide (CO2) concentrations in ambient air. These two gases can be used to assess air quality because the significant build up of CO2, which primarily results from the incomplete combustion of personal automobile engines, can result in the reduction of oxygen to concentration levels that are hazardous to human and other life. During the Summer of 2005, air samples from over 90 different locations were collected and used to make these measurements. Measurements were made with PASCO data-loggers attached to sensors that use infrared detectors to measure the amount of energy absorbed by carbon dioxide and oxygen molecules. Results were statistically analyzed, mapped, and used to assess the overall quality of air surrounding the Lake. Preliminary analysis of oxygen data indicates that higher concentration levels occur near sections of the Lake that are furthest removed from major roads, as well as in areas that have significant amounts of vegetation. In fact, the highest value recorded in this study was measured in a sample obtained near a grove of trees in a portion of the park that has the most vegetation, and that is furthest removed from major roads. Air quality here is high primarily due to the absence of CO2 build up associated with automobile traffic. The lowest values recorded were measured in samples collected along a stretch of the lakeshore that is very close to one of the busiest streets in the general area. The general trend of carbon dioxide concentration levels was also observed to decrease with distance from major roads and nearby highways. In the future, we plan to investigate possible relationships between oxygen and carbon dioxide concentrations in air surrounding the Lake and dissolved oxygen concentration of its waters. To the best of our knowledge, the air quality surrounding Lake Merritt has not been investigated before. Therefore results obtained during this study provide the foundation upon which future research may be built.
Particulate matter sensor with a heater
Hall, Matthew [Austin, TX
2011-08-16
An apparatus to detect particulate matter. The apparatus includes a sensor electrode, a shroud, and a heater. The electrode measures a chemical composition within an exhaust stream. The shroud surrounds at least a portion of the sensor electrode, exclusive of a distal end of the sensor electrode exposed to the exhaust stream. The shroud defines an air gap between the sensor electrode and the shroud and an opening toward the distal end of the sensor electrode. The heater is mounted relative to the sensor electrode. The heater burns off particulate matter in the air gap between the sensor electrode and the shroud.
Development of optical MEMS CO2 sensors
NASA Astrophysics Data System (ADS)
McNeal, Mark P.; Moelders, Nicholas; Pralle, Martin U.; Puscasu, Irina; Last, Lisa; Ho, William; Greenwald, Anton C.; Daly, James T.; Johnson, Edward A.; George, Thomas
2002-09-01
Inexpensive optical MEMS gas and chemical sensors offer chip-level solutions to environmental monitoring, industrial health and safety, indoor air quality, and automobile exhaust emissions monitoring. Previously, Ion Optics, Inc. reported on a new design concept exploiting Si-based suspended micro-bridge structures. The devices are fabricated using conventional CMOS compatible processes. The use of photonic bandgap (PBG) crystals enables narrow band IR emission for high chemical selectivity and sensitivity. Spectral tuning was accomplished by controlling symmetry and lattice spacing of the PBG structures. IR spectroscopic studies were used to characterize transmission, absorption and emission spectra in the 2 to 20 micrometers wavelength range. Prototype designs explored suspension architectures and filament geometries. Device characterization studies measured drive and emission power, temperature uniformity, and black body detectivity. Gas detection was achieved using non-dispersive infrared (NDIR) spectroscopic techniques, whereby target gas species were determined from comparison to referenced spectra. A sensor system employing the emitter/detector sensor-chip with gas cell and reflective optics is demonstrated and CO2 gas sensitivity limits are reported.
2012-07-01
AFRL /RYH) Sensors Directorate Air Force Research Laboratory Wright-Patterson Air Force ...Lossless Acoustic Monopoles, Electric Dipoles, and Magnetodielectric Spheres, Air Force Research Laboratory in-house report AFRL -SN-HS-TR-2006-0039... FORCE RESEARCH LABORATORY SENSORS DIRECTORATE WRIGHT-PATTERSON AIR FORCE BASE, OH 45433-7320 AIR FORCE MATERIEL COMMAND UNITED
Semiconducter Optical Amplifier as a Phase Modulator for Coherent Laser Radar (Preprint)
2012-01-01
AIR FORCE RESEARCH LABORATORY SENSORS DIRECTORATE WRIGHT-PATTERSON AIR FORCE BASE, OH 45433-7320 AIR FORCE MATERIEL COMMAND UNITED STATES... AIR FORCE NOTICE AND SIGNATURE PAGE Using Government drawings, specifications, or other data included in this document for any purpose other...NUMBER Multispectral Sensing and Detection Division LADAR Technology Branch (AFRL/RYMM) Air Force Research Laboratory, Sensors Directorate Wright
CALIOP-based Biomass Burning Smoke Plume Injection Height
NASA Astrophysics Data System (ADS)
Soja, A. J.; Choi, H. D.; Fairlie, T. D.; Pouliot, G.; Baker, K. R.; Winker, D. M.; Trepte, C. R.; Szykman, J.
2017-12-01
Carbon and aerosols are cycled between terrestrial and atmosphere environments during fire events, and these emissions have strong feedbacks to near-field weather, air quality, and longer-term climate systems. Fire severity and burned area are under the control of weather and climate, and fire emissions have the potential to alter numerous land and atmospheric processes that, in turn, feedback to and interact with climate systems (e.g., changes in patterns of precipitation, black/brown carbon deposition on ice/snow, alteration in landscape and atmospheric/cloud albedo). If plume injection height is incorrectly estimated, then the transport and deposition of those emissions will also be incorrect. The heights to which smoke is injected governs short- or long-range transport, which influences surface pollution, cloud interaction (altered albedo), and modifies patterns of precipitation (cloud condensation nuclei). We are working with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) science team and other stakeholder agencies, primarily the Environmental Protection Agency and regional partners, to generate a biomass burning (BB) plume injection height database using multiple platforms, sensors and models (CALIOP, MODIS, NOAA HMS, Langley Trajectory Model). These data have the capacity to provide enhanced smoke plume injection height parameterization in regional, national and international scientific and air quality models. Statistics that link fire behavior and weather to plume rise are crucial for verifying and enhancing plume rise parameterization in local-, regional- and global-scale models used for air quality, chemical transport and climate. Specifically, we will present: (1) a methodology that links BB injection height and CALIOP air parcels to specific fires; (2) the daily evolution of smoke plumes for specific fires; (3) plumes transport and deposited on the Greenland Ice Sheet; and (4) compare CALIOP-derived smoke plume injection to CMAQ modeled smoke plume injection. These results have the potential to provide value to national and international modeling communities (scientific and air quality) and to public land, fire, and air quality management and regulations communities.
Kids Making Sense of Air Quality Around Them Through a Hands-On, STEM-Based Program
NASA Astrophysics Data System (ADS)
Dye, T.
2015-12-01
Air pollution in many parts of the world is harming millions of people, shortening lives, and taking a toll on our ecosystem. Cities in India, China, and even the United States frequently exceed air quality standards. The use of localized data is a powerful enhancement to regulatory monitoring site data. Learning about air quality at a local level is a powerful driver for change. The Kids Making Sense program unites Science, Technology, Engineering, and Mathematics (STEM) education with a complete measurement and environmental education system that teaches youth about air pollution and empowers them to drive positive change in their communities. With this program, youth learn about particle pollution, its sources, and health effects. A half-day lecture is followed by hands-on activity using handheld air sensors paired with an app on smartphones. Students make measurements around schools to discover pollution sources and cleaner areas. Next, the data they collect are crowdsourced on a website for guided discussion and data interpretation. This program meets Next Generation Science Standards, encourages project-based learning and deep understanding of applied science, and allows students to practice science like real scientists. The program has been successfully implemented in several schools in the United States and Asia, including New York City, San Francisco, Los Angeles, and Sacramento in the United States, and Taipei and Taichung in Taiwan. During this talk, we'll provide an overview of the program, discuss some of the challenges, and lay out the next steps for Kids Making Sense.
A Comparison of Wind Speed Data from Mechanical and Ultrasonic Anemometers
NASA Technical Reports Server (NTRS)
Short, D.; Wells, L.; Merceret, F.; Roeder, W. P.
2006-01-01
This study compared the performance of mechanical and ultrasonic anemometers at the Eastern Range (ER; Kennedy Space Center and Cape Canaveral Air Force Station on Florida's Atlantic coast) and the Western Range (WR; Vandenberg Air Force Base on California's Pacific coast). Launch Weather Officers, forecasters, and Range Safety analysts need to understand the performance of wind sensors at the ER and WR for weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The current ER and WR weather tower wind instruments are being changed from the current propeller-and-vane (ER) and cup-and-vane (WR) sensors to ultrasonic sensors through the Range Standardization and Automation (RSA) program. The differences between mechanical and ultrasonic techniques have been found to cause differences in the statistics of peak wind speed in previous studies. The 45th Weather Squadron (45 WS) and the 30th Weather Squadron (30 WS) requested the Applied Meteorology Unit (AMU) to compare data between RSA and current sensors to determine if there are significant differences. Approximately 3 weeks of Legacy and RSA wind data from each range were used in the study, archived during May and June 2005. The ER data spanned the full diurnal cycle, while the WR data was confined to 1000-1600 local time. The sample of 1-minute data from numerous levels on 5 different towers on each range totaled more than 500,000 minutes of data (482,979 minutes of data after quality control). The 10 towers were instrumented at several levels, ranging from 12 ft to 492 ft above ground level. The RSA sensors were collocated at the same vertical levels as the present sensors and typically within 15 ft horizontally of each another. Data from a total of 53 RSA ultrasonic sensors, collocated with present sensors were compared. The 1-minute average wind speed/direction and the 1-second peak wind speed/direction were compared.
The Deployment of Carbon Monoxide Wireless Sensor Network (CO-WSN) for Ambient Air Monitoring
Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C.; Khang, Soon-Jai
2014-01-01
Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011–2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1–1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring. PMID:24937527
DOE Office of Scientific and Technical Information (OSTI.GOV)
None
A system according to the principles of the present disclosure includes an air/fuel ratio determination module and an emission level determination module. The air/fuel ratio determination module determines an air/fuel ratio based on input from an air/fuel ratio sensor positioned downstream from a three-way catalyst that is positioned upstream from a selective catalytic reduction (SCR) catalyst. The emission level determination module selects one of a predetermined value and an input based on the air/fuel ratio. The input is received from a nitrogen oxide sensor positioned downstream from the three-way catalyst. The emission level determination module determines an ammonia level basedmore » on the one of the predetermined value and the input received from the nitrogen oxide sensor.« less
NASA Astrophysics Data System (ADS)
Shim, Hayeong; Roh, Yongrae
2018-07-01
Ultrasonic sensors in air are used to measure distances from obstacles in household appliances, automobiles, and other areas. Among these ultrasonic sensors in air, sensors using disk-shaped piezoelectric ceramics are composed of a multilayered structure having a vibrational plate, a piezoelectric ceramic disk, and a backing layer. In this study, we derived theoretical equations that can accurately analyze the acoustic characteristics of the piezoelectric multilayered structure, and then analyzed the performance of the ultrasonic sensor according to the geometrical change of the multilayered structure. The characteristics analyzed were the resonant frequency and the radiated sound pressure at a far field of the sensor. The validity of the theoretical analysis was verified by comparing the results with those obtained from the finite element analysis of the same structure. The exact functional forms of the resonant frequency of and the radiated sound pressure from the piezoelectric multilayered structure derived in this study can be directly utilized to maximize the performance of various ultrasonic sensors in air.
Applications of MODIS satellite data and products for monitoring air quality in the state of Texas
NASA Astrophysics Data System (ADS)
Hutchison, Keith D.
The Center for Space Research (CSR), in conjunction with the Monitoring Operations Division (MOD) of the Texas Commission on Environmental Quality (TCEQ), is evaluating the use of remotely sensed satellite data to assist in monitoring and predicting air quality in Texas. The challenges of meeting air quality standards established by the US Environmental Protection Agency (US EPA) are impacted by the transport of pollution into Texas that originates from outside our borders and are cumulative with those generated by local sources. In an attempt to quantify the concentrations of all pollution sources, MOD has installed ground-based monitoring stations in rural regions along the Texas geographic boundaries including the Gulf coast, as well as urban regions that are the predominant sources of domestic pollution. However, analysis of time-lapse GOES satellite imagery at MOD, clearly demonstrates the shortcomings of using only ground-based observations for monitoring air quality across Texas. These shortcomings include the vastness of State borders, that can only be monitored with a large number of ground-based sensors, and gradients in pollution concentration that depend upon the location of the point source, the meteorology governing its transport to Texas, and its diffusion across the region. With the launch of NASA's MODerate resolution Imaging Spectroradiometer (MODIS), the transport of aerosol-borne pollutants can now be monitored over land and ocean surfaces. Thus, CSR and MOD personnel have applied MODIS data to several classes of pollution that routinely impact Texas air quality. Results demonstrate MODIS data and products can detect and track the migration of pollutants. This paper presents one case study in which continental haze from the northeast moved into the region and subsequently required health advisories to be issued for 150 counties in Texas. It is concluded that MODIS provides the basis for developing advanced data products that will, when used in conjunction with ground-based observations, create a cost-effective and accurate pollution monitoring system for the entire state of Texas.
NASA Astrophysics Data System (ADS)
Wysokiński, Karol; Filipowicz, Marta; Stańczyk, Tomasz; Lipiński, Stanisław; Napierała, Marek; Murawski, Michał; Nasiłowski, Tomasz
2017-10-01
A matrix of optical fiber sensors eligible for remote measurements is reported in this paper. The aim of work was to monitor the air quality with a device, which does not need any electricity on site of the measurement. The matrix consists of several sensors detecting carbon dioxide concentration, relative humidity and temperature. Sensors utilize active optical materials, which change their color when exposed to varied conditions. All the sensors are powered with standard light emitting diodes. Light is transmitted by an optical fiber from the light source and then it reaches the active layer which changes its color, when the conditions change. This results in a change of attenuation of light passing through the active layer. Modified light is then transmitted by another optical fiber to the detector, where simple photoresistor is used. It is powered by a stabilized DC power supply and the current is measured. Since no expensive elements are needed to manufacture such a matrix of sensors, its price may be competitive to the price of the devices already available on the market, while the matrix also exhibits other valuable properties.
Jerrett, Michael; Donaire-Gonzalez, David; Popoola, Olalekan; Jones, Roderic; Cohen, Ronald C; Almanza, Estela; de Nazelle, Audrey; Mead, Iq; Carrasco-Turigas, Glòria; Cole-Hunter, Tom; Triguero-Mas, Margarita; Seto, Edmund; Nieuwenhuijsen, Mark
2017-10-01
Low cost, personal air pollution sensors may reduce exposure measurement errors in epidemiological investigations and contribute to citizen science initiatives. Here we assess the validity of a low cost personal air pollution sensor. Study participants were drawn from two ongoing epidemiological projects in Barcelona, Spain. Participants repeatedly wore the pollution sensor - which measured carbon monoxide (CO), nitric oxide (NO), and nitrogen dioxide (NO 2 ). We also compared personal sensor measurements to those from more expensive instruments. Our personal sensors had moderate to high correlations with government monitors with averaging times of 1-h and 30-min epochs (r ~ 0.38-0.8) for NO and CO, but had low to moderate correlations with NO 2 (~0.04-0.67). Correlations between the personal sensors and more expensive research instruments were higher than with the government monitors. The sensors were able to detect high and low air pollution levels in agreement with expectations (e.g., high levels on or near busy roadways and lower levels in background residential areas and parks). Our findings suggest that the low cost, personal sensors have potential to reduce exposure measurement error in epidemiological studies and provide valid data for citizen science studies. Copyright © 2017 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Holzrichter, John F
2015-05-05
An implanted stimulation device or air control device are activated by an external radar-like sensor for controlling apnea. The radar-like sensor senses the closure of the air flow cavity, and associated control circuitry signals (1) a stimulator to cause muscles to open the air passage way that is closing or closed or (2) an air control device to open the air passage way that is closing or closed.
Monitoring space shuttle air quality using the Jet Propulsion Laboratory electronic nose
NASA Technical Reports Server (NTRS)
Ryan, Margaret Amy; Zhou, Hanying; Buehler, Martin G.; Manatt, Kenneth S.; Mowrey, Victoria S.; Jackson, Shannon P.; Kisor, Adam K.; Shevade, Abhijit V.; Homer, Margie L.
2004-01-01
A miniature electronic nose (ENose) has been designed and built at the Jet Propulsion Laboratory (JPL), Pasadena, CA, and was designed to detect, identify, and quantify ten common contaminants and relative humidity changes. The sensing array includes 32 sensing films made from polymer carbon-black composites. Event identification and quantification were done using the Levenberg-Marquart nonlinear least squares method. After successful ground training, this ENose was used in a demonstration experiment aboard STS-95 (October-November, 1998), in which the ENose was operated continuously for six days and recorded the sensors' response to the air in the mid-deck. Air samples were collected daily and analyzed independently after the flight. Changes in shuttle-cabin humidity were detected and quantified by the JPL ENose; neither the ENose nor the air samples detected any of the contaminants on the target list. The device is microgravity insensitive.
Next Generation Air Measurements for Fugitive, Area Source, and Fence Line Applications
Next generation air measurements (NGAM) is an EPA term for the advancing field of air pollutant sensor technologies, data integration concepts, and geospatial modeling strategies. Ranging from personal sensors to satellite remote sensing, NGAM systems may provide revolutionary n...
Hofman, Jelle; Maher, Barbara A; Muxworthy, Adrian R; Wuyts, Karen; Castanheiro, Ana; Samson, Roeland
2017-06-20
Biomagnetic monitoring of atmospheric pollution is a growing application in the field of environmental magnetism. Particulate matter (PM) in atmospheric pollution contains readily measurable concentrations of magnetic minerals. Biological surfaces, exposed to atmospheric pollution, accumulate magnetic particles over time, providing a record of location-specific, time-integrated air quality information. This review summarizes current knowledge of biological material ("sensors") used for biomagnetic monitoring purposes. Our work addresses the following: the range of magnetic properties reported for lichens, mosses, leaves, bark, trunk wood, insects, crustaceans, mammal and human tissues; their associations with atmospheric pollutant species (PM, NO x , trace elements, PAHs); the pros and cons of biomagnetic monitoring of atmospheric pollution; current challenges for large-scale implementation of biomagnetic monitoring; and future perspectives. A summary table is presented, with the aim of aiding researchers and policy makers in selecting the most suitable biological sensor for their intended biomagnetic monitoring purpose.
Sensor Technologies for Particulate Detection and Characterization
NASA Technical Reports Server (NTRS)
Greenberg, Paul S.
2008-01-01
Planned Lunar missions have resulted in renewed attention to problems attributable to fine particulates. While the difficulties experienced during the sequence of Apollo missions did not prove critical in all cases, the comparatively long duration of impending missions may present a different situation. This situation creates the need for a spectrum of particulate sensing technologies. From a fundamental perspective, an improved understanding of the properties of the dust fraction is required. Described here is laboratory-based reference instrumentation for the measurement of fundamental particle size distribution (PSD) functions from 2.5 nanometers to 20 micrometers. Concomitant efforts for separating samples into fractional size bins are also presented. A requirement also exists for developing mission compatible sensors. Examples include provisions for air quality monitoring in spacecraft and remote habitation modules. Required sensor attributes such as low mass, volume, and power consumption, autonomy of operation, and extended reliability cannot be accommodated by existing technologies.
NASA Astrophysics Data System (ADS)
Mousavi, Monireh Sadat; Ashrafi, Khosro; Motlagh, Majid Shafie Pour; Niksokhan, Mohhamad Hosein; Vosoughifar, HamidReza
2018-02-01
In this study, coupled method for simulation of flow pattern based on computational methods for fluid dynamics with optimization technique using genetic algorithms is presented to determine the optimal location and number of sensors in an enclosed residential complex parking in Tehran. The main objective of this research is costs reduction and maximum coverage with regard to distribution of existing concentrations in different scenarios. In this study, considering all the different scenarios for simulation of pollution distribution using CFD simulations has been challenging due to extent of parking and number of cars available. To solve this problem, some scenarios have been selected based on random method. Then, maximum concentrations of scenarios are chosen for performing optimization. CFD simulation outputs are inserted as input in the optimization model using genetic algorithm. The obtained results stated optimal number and location of sensors.
Choi, Subin; Park, Kyeonghwan; Lee, Seungwook; Lim, Yeongjin; Oh, Byungjoo; Chae, Hee Young; Park, Chan Sam; Shin, Heugjoo; Kim, Jae Joon
2018-03-02
This paper presents a resolution-reconfigurable wide-range resistive sensor readout interface for wireless multi-gas monitoring applications that displays results on a smartphone. Three types of sensing resolutions were selected to minimize processing power consumption, and a dual-mode front-end structure was proposed to support the detection of a variety of hazardous gases with wide range of characteristic resistance. The readout integrated circuit (ROIC) was fabricated in a 0.18 μm CMOS process to provide three reconfigurable data conversions that correspond to a low-power resistance-to-digital converter (RDC), a 12-bit successive approximation register (SAR) analog-to-digital converter (ADC), and a 16-bit delta-sigma modulator. For functional feasibility, a wireless sensor system prototype that included in-house microelectromechanical (MEMS) sensing devices and commercial device products was manufactured and experimentally verified to detect a variety of hazardous gases.
Zhou, Lihong; Yuan, Liming; Thomas, Rick; Iannacchione, Anthony
2017-12-01
When there are installations of air velocity sensors in the mining industry for real-time airflow monitoring, a problem exists with how the monitored air velocity at a fixed location corresponds to the average air velocity, which is used to determine the volume flow rate of air in an entry with the cross-sectional area. Correction factors have been practically employed to convert a measured centerline air velocity to the average air velocity. However, studies on the recommended correction factors of the sensor-measured air velocity to the average air velocity at cross sections are still lacking. A comprehensive airflow measurement was made at the Safety Research Coal Mine, Bruceton, PA, using three measuring methods including single-point reading, moving traverse, and fixed-point traverse. The air velocity distribution at each measuring station was analyzed using an air velocity contour map generated with Surfer ® . The correction factors at each measuring station for both the centerline and the sensor location were calculated and are discussed.
Yuan, Liming; Thomas, Rick; Iannacchione, Anthony
2017-01-01
When there are installations of air velocity sensors in the mining industry for real-time airflow monitoring, a problem exists with how the monitored air velocity at a fixed location corresponds to the average air velocity, which is used to determine the volume flow rate of air in an entry with the cross-sectional area. Correction factors have been practically employed to convert a measured centerline air velocity to the average air velocity. However, studies on the recommended correction factors of the sensor-measured air velocity to the average air velocity at cross sections are still lacking. A comprehensive airflow measurement was made at the Safety Research Coal Mine, Bruceton, PA, using three measuring methods including single-point reading, moving traverse, and fixed-point traverse. The air velocity distribution at each measuring station was analyzed using an air velocity contour map generated with Surfer®. The correction factors at each measuring station for both the centerline and the sensor location were calculated and are discussed. PMID:29201495
We present the design and fabrication of a micro electro mechanical systems (MEMS) air-microfluidic particulate matter (PM) sensor, and show experimental results obtained from exposing the sensor to concentrations of tobacco smoke and diesel exhaust, two commonly occurring P...
CitySpace Air Sensor Network Project Conducted to Test New Monitoring Capabilities
The CitySpace project is a new research effort by EPA to field test new, lower-cost air pollution sensors in a mid-sized city to understand how this emerging technology can add valuable information on air pollution patterns in neighboorhoods.
South Philadelphia Passive Sampler and Sensor Study - Interim Report
Starting in the June 2013, the U.S. EPA and the City of Philadelphia Air Measurements Services (AMS) began a collaborative research project to investigate how sensor-based, stand-alone air measurements (SAMs) and passive samplers (PSs) can help improve information on air pollutan...
The Challenge of Handling Big Data Sets in the Sensor Web
NASA Astrophysics Data System (ADS)
Autermann, Christian; Stasch, Christoph; Jirka, Simon
2016-04-01
More and more Sensor Web components are deployed in different domains such as hydrology, oceanography or air quality in order to make observation data accessible via the Web. However, besides variability of data formats and protocols in environmental applications, the fast growing volume of data with high temporal and spatial resolution is imposing new challenges for Sensor Web technologies when sharing observation data and metadata about sensors. Variability, volume and velocity are the core issues that are addressed by Big Data concepts and technologies. Most solutions in the geospatial sector focus on remote sensing and raster data, whereas big in-situ observation data sets relying on vector features require novel approaches. Hence, in order to deal with big data sets in infrastructures for observational data, the following questions need to be answered: 1. How can big heterogeneous spatio-temporal datasets be organized, managed, and provided to Sensor Web applications? 2. How can views on big data sets and derived information products be made accessible in the Sensor Web? 3. How can big observation data sets be processed efficiently? We illustrate these challenges with examples from the marine domain and outline how we address these challenges. We therefore show how big data approaches from mainstream IT can be re-used and applied to Sensor Web application scenarios.
The measurement of carbon dioxide levels in a city canyon
NASA Astrophysics Data System (ADS)
Boyd, Jenny; Budinov, Daniel; Robinson, Iain; Jack, James
2016-10-01
Cities today have two major environmental concerns - carbon emissions and air quality. Global carbon levels are increasing and cities require to show plans to tackle and reduce the amount of carbon which they are emitting. At present carbon emissions in urban areas are calculated rather than measured. In some cities where industrial activity is not carbon intensive, the major contributors are the burning of fuel for heating and the emissions from vehicles. Air quality levels have a direct impact on human health and cities are under increased pressure to demonstrate plans to control and reduce levels of air pollution. Of great importance is the way in which emissions, both carbon rich emissions and pollutants, disperse in a city environment. Little work has been reported on the movement of CO2 in the urban environment and the effect the structure of the environment exerts on the movement and dispersion. This paper describes an investigation into the dispersion of CO2 within an urban environment in the Old Town of the City of Edinburgh, using a hand carried low cost portable CO2 sensor.
Acoustic Sensors for Air and Surface Navigation Applications
Kapoor, Rohan; Ramasamy, Subramanian; Schyndel, Ron Van
2018-01-01
This paper presents the state-of-the-art and reviews the state-of-research of acoustic sensors used for a variety of navigation and guidance applications on air and surface vehicles. In particular, this paper focuses on echolocation, which is widely utilized in nature by certain mammals (e.g., cetaceans and bats). Although acoustic sensors have been extensively adopted in various engineering applications, their use in navigation and guidance systems is yet to be fully exploited. This technology has clear potential for applications in air and surface navigation/guidance for intelligent transport systems (ITS), especially considering air and surface operations indoors and in other environments where satellite positioning is not available. Propagation of sound in the atmosphere is discussed in detail, with all potential attenuation sources taken into account. The errors introduced in echolocation measurements due to Doppler, multipath and atmospheric effects are discussed, and an uncertainty analysis method is presented for ranging error budget prediction in acoustic navigation applications. Considering the design challenges associated with monostatic and multi-static sensor implementations and looking at the performance predictions for different possible configurations, acoustic sensors show clear promises in navigation, proximity sensing, as well as obstacle detection and tracking. The integration of acoustic sensors in multi-sensor navigation systems is also considered towards the end of the paper and a low Size, Weight and Power, and Cost (SWaP-C) sensor integration architecture is presented for possible introduction in air and surface navigation systems. PMID:29414894
Itoh, Toshio; Akamatsu, Takafumi; Tsuruta, Akihiro; Shin, Woosuck
2017-01-01
We investigated selective detection of the target volatile organic compounds (VOCs) nonanal, n-decane, and acetoin for lung cancer-related VOCs, and acetone and methyl i-butyl ketone for diabetes-related VOCs, in humid air with simulated VOC contamination (total concentration: 300 μg/m3). We used six “grain boundary-response type” sensors, including four commercially available sensors (TGS 2600, 2610, 2610, and 2620) and two Pt, Pd, and Au-loaded SnO2 sensors (Pt, Pd, Au/SnO2), and two “bulk-response type” sensors, including Zr-doped CeO2 (CeZr10), i.e., eight sensors in total. We then analyzed their sensor signals using principal component analysis (PCA). Although the six “grain boundary-response type” sensors were found to be insufficient for selective detection of the target gases in humid air, the addition of two “bulk-response type” sensors improved the selectivity, even with simulated VOC contamination. To further improve the discrimination, we selected appropriate sensors from the eight sensors based on the PCA results. The selectivity to each target gas was maintained and was not affected by contamination. PMID:28753948
Fu, Long; Huda, Quamrul; Yang, Zheng; Zhang, Lucas; Hashisho, Zaher
2017-11-01
Significant amounts of volatile organic compounds and greenhouse gases are generated from wastewater lagoons and tailings ponds in Alberta, Canada. Accurate measurements of these air pollutants and greenhouse gases are needed to support management and regulatory decisions. A mobile platform was developed to measure air emissions from tailings pond in the oil sands region of Alberta. The mobile platform was tested in 2015 in a municipal wastewater treatment lagoon. With a flux chamber and a CO 2 /CH 4 sensor on board, the mobile platform was able to measure CO 2 and CH 4 emissions over two days at two different locations in the pond. Flux emission rates of CO 2 and CH 4 that were measured over the study period suggest the presence of aerobic and anaerobic zones in the wastewater treatment lagoon. The study demonstrated the capabilities of the mobile platform in measuring fugitive air emissions and identified the potential for the applications in air and water quality monitoring programs. The Mobile Platform demonstrated in this study has the ability to measure greenhouse gas (GHG) emissions from fugitive sources such as municipal wastewater lagoons. This technology can be used to measure emission fluxes from tailings ponds with better detection of spatial and temporal variations of fugitive emissions. Additional air and water sampling equipment could be added to the mobile platform for a broad range of air and water quality studies in the oil sands region of Alberta.
Air Conditioning Overflow Sensor
NASA Technical Reports Server (NTRS)
1996-01-01
The Technology Transfer Office at Stennis Space Center helped a local inventor develop a prototype of an attachment for central air conditioners and heat pumps that helps monitor water levels to prevent condensation overflow. The sensor will indicate a need for drain line maintenance and prevent possible damage caused by drain pan water spillover. An engineer in the Stennis Space Center prototype Development Laboratory used SSC sensor technology in the development of the sensor.
Development of Micro Air Reconnaissance Vehicle as a Test Bed for Advanced Sensors and Electronics
NASA Technical Reports Server (NTRS)
Shams, Qamar A.; Vranas, Thomas L.; Fox, Robert L.; Kuhn, Theodore R.; Ingham, John; Logan, Michael J.; Barnes, Kevin N.; Guenther, Benjamin F.
2002-01-01
This paper describes the development of a Micro/Mini Air Reconnaissance Vehicle for advanced sensors and electronics at NASA Langley Research Center over the last year. This vehicle is expected to have a total weight of less than four pounds, a design velocity of 40 mph, an endurance of 15-20 minutes, and a maximum range of 5km. The vehicle has wings that are simple to detach yet retain the correct alignment. The upper fuselage surface has a quick release hatch used to access the interior and also to mount the varying propulsion systems. The sensor suite developed for this vehicle consists of a Pitot-static measurement system for determining air speed, an absolute pressure measurement for determining altitude, magnetic direction measurement, and three orthogonal gyros to determine body angular rates. Swarming GPS-guidance and in-flight maneuvering is discussed, as well as design and installation of some other advance sensors like MEMS microphones, infrared cameras, GPS, humidity sensors, and an ultrasonic sonar sensor. Also low cost, small size, high performance control and navigation system for the Micro Air Vehicle is discussed. At the end, laboratory characterization of different sensors, motors, propellers, and batteries will be discussed.
A Pneumatic Tactile Sensor for Co-Operative Robots
He, Rui; Yu, Jianjun; Zuo, Guoyu
2017-01-01
Tactile sensors of comprehensive functions are urgently needed for the advanced robot to co-exist and co-operate with human beings. Pneumatic tactile sensors based on air bladder possess some noticeable advantages for human-robot interaction application. In this paper, we construct a pneumatic tactile sensor and apply it on the fingertip of robot hand to realize the sensing of force, vibration and slippage via the change of the pressure of the air bladder, and we utilize the sensor to perceive the object’s features such as softness and roughness. The pneumatic tactile sensor has good linearity, repeatability and low hysteresis and both its size and sensing range can be customized by using different material as well as different thicknesses of the air bladder. It is also simple and cheap to fabricate. Therefore, the pneumatic tactile sensor is suitable for the application of co-operative robots and can be widely utilized to improve the performance of service robots. We can apply it to the fingertip of the robot to endow the robotic hand with the ability to co-operate with humans and handle the fragile objects because of the inherent compliance of the air bladder. PMID:29125565
NASA Astrophysics Data System (ADS)
Alston, E. J.; Sokolik, I. N.
2011-12-01
This study examines how aerosols measured from the ground and space over the U. S. Southeast change temporally over a regional scale and their radiative impacts. PM2.5 data consist of two datasets that represent the measurements that are used for regulatory purposes by the U.S. EPA and continuous measurements used for quickly disseminating air quality information. Aerosol optical depth (AOD) data come from three NASA sensors: the MODIS sensors onboard Terra and Aqua satellites and the MISR sensor onboard the Terra satellite. We analyze all available aerosol data over the state of Georgia from 2000 - 2009. In additional to aerosol data, we examine the surface albedo and cloud cover products from MODIS Terra over the same time period. Strong seasonality is detected in both the AOD and PM2.5 datasets; as evidenced by a threefold increase of AOD from mean winter values to mean summer values, and the increase in PM2.5 concentrations is almost twofold from over the same period. We found good agreement between MODIS and MISR onboard the Terra satellite during the spring and summer having correlation coefficients of 0.64 in spring and 0.71 in summer. Monthly anomalies were used to determine the presence of a trend in the both AODs and PM2.5 aerosol datasets. In addition, radiative transfer modeling was performed to assess the aerosol radiative forcing in the region over the past decade. The results of this analysis suggest that the Southeastern U.S. is experiencing solar brightening likely due to better air quality control policies. Our results also hint that if the brightening continues, the radiative forcing from these aerosols will become less negative, which could have potential impacts on climate for the region.
Plug-in Sensors for Air Pollution Monitoring.
ERIC Educational Resources Information Center
Shaw, Manny
Faristors, a type of plug-in sensors used in analyzing equipment, are described in this technical report presented at the 12th Conference on Methods in Air Pollution and Industrial Hygiene Studies, University of Southern California, April, 1971. Their principles of operation, interchangeability, and versatility for measuring air pollution at…
Air condition sensor on KNX network
NASA Astrophysics Data System (ADS)
Gecova, Katerina; Vala, David; Slanina, Zdenek; Walendziuk, Wojciech
2017-08-01
One of the main goals of modern buildings in addition to the management environment is also attempt to save energy. For this reason, increased demands on the prevention of energy loss, which can be expressed for example as an inefficient use of the available functions as a building or heat leakage. Reducing heat loss as a perfect tightness of doors and windows in the building, however, restricts the natural ventilation, which leads to a gradual deterioration of the quality of the internal environment. This state then has a very significant impact on human health. In the closed, poorly ventilated area, the person staying at increasing the carbon dioxide concentration, temperature and humidity, which impacts the human thermoregulation system, increases fatigue and causes restlessness. It is therefore necessary to monitor these parameters and then control so as to ensure stable and optimal human values. The aim is to design and implementation Module sensors that will be able to measure different parameters, allowing the subsequent regulation of indoor environmental quality.
Kim, Daehee; Kim, Dongwan; An, Sunshin
2016-07-09
Code dissemination in wireless sensor networks (WSNs) is a procedure for distributing a new code image over the air in order to update programs. Due to the fact that WSNs are mostly deployed in unattended and hostile environments, secure code dissemination ensuring authenticity and integrity is essential. Recent works on dynamic packet size control in WSNs allow enhancing the energy efficiency of code dissemination by dynamically changing the packet size on the basis of link quality. However, the authentication tokens attached by the base station become useless in the next hop where the packet size can vary according to the link quality of the next hop. In this paper, we propose three source authentication schemes for code dissemination supporting dynamic packet size. Compared to traditional source authentication schemes such as μTESLA and digital signatures, our schemes provide secure source authentication under the environment, where the packet size changes in each hop, with smaller energy consumption.
Kim, Daehee; Kim, Dongwan; An, Sunshin
2016-01-01
Code dissemination in wireless sensor networks (WSNs) is a procedure for distributing a new code image over the air in order to update programs. Due to the fact that WSNs are mostly deployed in unattended and hostile environments, secure code dissemination ensuring authenticity and integrity is essential. Recent works on dynamic packet size control in WSNs allow enhancing the energy efficiency of code dissemination by dynamically changing the packet size on the basis of link quality. However, the authentication tokens attached by the base station become useless in the next hop where the packet size can vary according to the link quality of the next hop. In this paper, we propose three source authentication schemes for code dissemination supporting dynamic packet size. Compared to traditional source authentication schemes such as μTESLA and digital signatures, our schemes provide secure source authentication under the environment, where the packet size changes in each hop, with smaller energy consumption. PMID:27409616
NASA Technical Reports Server (NTRS)
Limero, Thomas; Beck, Steve; James, John T.
2004-01-01
A combustion products analyzer (CPA) was built for use on Shuttle in response to several thermodegradation incidents that had occurred during early flights. The CPA contained sensors that measured carbon monoxide, hydrogen chloride, hydrogen cyanide, and hydrogen fluoride. These marker compounds, monitored by the CPA, were selected based upon the likely products to be released in a spacecraft fire. When the Toxicology Laboratory group at Johnson Space Center (JSC) began to assess the air quality monitoring needs for the International Space Station (ISS), the CPA was the starting point for design of an instrument to monitor the atmosphere following a thermodegradation event. The final product was significantly different from the CPA and was named the compound specific analyzer-combustion products (CSA-CP). The major change from the CPA that will be the focus of this paper was the replacement of an unreliable hydrogen fluoride (HF) sensor with an oxygen sensor. A reliable HF sensor was not commercially available, but as the toxicology group reviewed the overall monitoring strategy for ISS, it appeared that a portable oxygen sensor to backup the major constituent analyzer was needed. Therefore, an oxygen sensor replaced the HF sensor in the new instrument. This paper will describe the development, deployment, and performance of the CSA-CP oxygen sensor on both Shuttle and ISS. Also, data for CSA-CP oxygen sensor accuracy at nominal and reduced pressures will be presented.
Fiber Optic Sensors for Structural Health Monitoring of Air Platforms
Guo, Honglei; Xiao, Gaozhi; Mrad, Nezih; Yao, Jianping
2011-01-01
Aircraft operators are faced with increasing requirements to extend the service life of air platforms beyond their designed life cycles, resulting in heavy maintenance and inspection burdens as well as economic pressure. Structural health monitoring (SHM) based on advanced sensor technology is potentially a cost-effective approach to meet operational requirements, and to reduce maintenance costs. Fiber optic sensor technology is being developed to provide existing and future aircrafts with SHM capability due to its unique superior characteristics. This review paper covers the aerospace SHM requirements and an overview of the fiber optic sensor technologies. In particular, fiber Bragg grating (FBG) sensor technology is evaluated as the most promising tool for load monitoring and damage detection, the two critical SHM aspects of air platforms. At last, recommendations on the implementation and integration of FBG sensors into an SHM system are provided. PMID:22163816
NASA Astrophysics Data System (ADS)
Gan, Chuen-Meei
Air quality model forecasts from Weather Research and Forecast (WRF) and Community Multiscale Air Quality (CMAQ) are often used to support air quality applications such as regulatory issues and scientific inquiries on atmospheric science processes. In urban environments, these models become more complex due to the inherent complexity of the land surface coupling and the enhanced pollutants emissions. This makes it very difficult to diagnose the model, if the surface parameter forecasts such as PM2.5 (particulate matter with aerodynamic diameter less than 2.5 microm) are not accurate. For this reason, getting accurate boundary layer dynamic forecasts is as essential as quantifying realistic pollutants emissions. In this thesis, we explore the usefulness of vertical sounding measurements on assessing meteorological and air quality forecast models. In particular, we focus on assessing the WRF model (12km x 12km) coupled with the CMAQ model for the urban New York City (NYC) area using multiple vertical profiling and column integrated remote sensing measurements. This assessment is helpful in probing the root causes for WRF-CMAQ overestimates of surface PM2.5 occurring both predawn and post-sunset in the NYC area during the summer. In particular, we find that the significant underestimates in the WRF PBL height forecast is a key factor in explaining this anomaly. On the other hand, the model predictions of the PBL height during daytime when convective heating dominates were found to be highly correlated to lidar derived PBL height with minimal bias. Additional topics covered in this thesis include mathematical method using direct Mie scattering approach to convert aerosol microphysical properties from CMAQ into optical parameters making direct comparisons with lidar and multispectral radiometers feasible. Finally, we explore some tentative ideas on combining visible (VIS) and mid-infrared (MIR) sensors to better separate aerosols into fine and coarse modes.
1980-09-01
Air Vehicles as Sensor Platforms" (see inset) and would seek to determine the operational capability of advanced high altitude air vehicles as...Unmanned Air Vehicles as Sensor Platforms Determine the operational capability of advanced high-altitude air vehicles as platforms for surveillance...m) IT ala (1) a freccia ES sensacion (r) artificial ES indicador (m) tipo A NE pillvleugel FR I sensation MI artificielle FR indicateur (m) type A
Air Pollution Measurements by Citizen Scientists and NASA Satellites: Data Integration and Analysis
NASA Astrophysics Data System (ADS)
Gupta, P.; Maibach, J.; Levy, R. C.; Doraiswamy, P.; Pikelnaya, O.; Feenstra, B.; Polidori, A.
2017-12-01
PM2.5, or fine particulate matter, is a category of air pollutant consisting of solid particles with effective aerodynamic diameter of less than 2.5 microns. These particles are hazardous to human health, as their small size allows them to penetrate deep into the lungs. Since the late 1990's, the US Environmental Protection Agency has been monitoring PM2.5 using a network of ground-level sensors. Due to cost and space restrictions, the EPA monitoring network remains spatially sparse. That is, while the network spans the extent of the US, the distance between sensors is large enough that significant spatial variation in PM concentration can go undetected. To increase the spatial resolution of monitoring, previous studies have used satellite data to estimate ground-level PM concentrations. From imagery, one can create a measure of haziness due to aerosols, called aerosol optical depth (AOD), which then can be used to estimate PM concentrations using statistical and physical modeling. Additionally, previous research has identified a number of meteorological variables, such as relative humidity and mixing height, which aide in estimating PM concentrations from AOD. Although the high spatial resolution of satellite data is valuable alone for forecasting air quality, higher resolution ground-level data is needed to effectively study the relationship between PM2.5 concentrations and AOD. To this end, we discuss a citizen-science PM monitoring network deployed in California. Using low-cost PM sensors, this network achieves higher spatial resolution. We additionally discuss a software pipeline for integrating resulting PM measurements with satellite data, as well as initial data analysis.
Wetherbee, Gregory A.; Rhodes, Mark F.
2013-01-01
The U.S. Geological Survey Branch of Quality Systems operates the Precipitation Chemistry Quality Assurance project (PCQA) to provide independent, external quality-assurance for the National Atmospheric Deposition Program (NADP). NADP is composed of five monitoring networks that measure the chemical composition of precipitation and ambient air. PCQA and the NADP Program Office completed five short-term studies to investigate the effects of equipment performance with respect to the National Trends Network (NTN) and Mercury Deposition Network (MDN) data quality: sample evaporation from NTN collectors; sample volume and mercury loss from MDN collectors; mercury adsorption to MDN collector glassware, grid-type precipitation sensors for precipitation collectors, and the effects of an NTN collector wind shield on sample catch efficiency. Sample-volume evaporation from an NTN Aerochem Metrics (ACM) collector ranged between 1.1–33 percent with a median of 4.7 percent. The results suggest that weekly NTN sample evaporation is small relative to sample volume. MDN sample evaporation occurs predominantly in western and southern regions of the United States (U.S.) and more frequently with modified ACM collectors than with N-CON Systems Inc. collectors due to differences in airflow through the collectors. Variations in mercury concentrations, measured to be as high as 47.5 percent per week with a median of 5 percent, are associated with MDN sample-volume loss. Small amounts of mercury are also lost from MDN samples by adsorption to collector glassware irrespective of collector type. MDN 11-grid sensors were found to open collectors sooner, keep them open longer, and cause fewer lid cycles than NTN 7-grid sensors. Wind shielding an NTN ACM collector resulted in collection of larger quantities of precipitation while also preserving sample integrity.
Novel Fabry-Perot fiber optic sensor with multiple applications
NASA Astrophysics Data System (ADS)
Chen, Xiaopei; Shen, Fabin; Wang, Anbo; Wang, Zhuang; Zhang, Yan
2004-12-01
A novel Intrinsic Fabry-Perot fiber-optic sensor is presented in this paper. The sensors were made through two simple steps: wet chemical etch and fusion splice. Micro air-gaps were generated inside the fibers and functioned as reflective mirrors. This procedure not only provides a simple and cost effective technology for fabricating intrinsic Fabry-Perot Interferometric (IFPI) fiber sensors, but also provides two possible IFPI structures. Both of the fiber cavity between the air-gaps or the air-gap and cleaved fiber end can be used as sensing elements. With these two structures, this sensor can be used to measure the temperature, strain, pressure, refractive index of chemicals and the thin film thickness by itself. Multi-point measurements can also be achieved by multiplexing. Furthermore, it also can be multiplexed with other sensors such as Long Period Gratings (LPG) to provide compensations for other perturbation sensing. Theoretical and experimental studies of two sensor structures are described. Experimental results show that high resolution and high sensitivity can be obtained with appropriate signal processing.
NASA Astrophysics Data System (ADS)
Petculescu, Andi G.; Sabatier, James M.
2004-04-01
The paper addresses several sensitive issues concerning the use of air-coupled ultrasound to probe small vibrations of surfaces covered with low-lying vegetation such as grass. The operation of the ultrasonic sensor is compared to that of a laser Doppler vibrometer, in various contexts. It is shown that ambient air motion affects either system, albeit differently. As air speed increases, the acoustic sensor detects a progressively richer turbulent spectrum, which reduces its sensitivity. In turn, optical sensors are prone to tremendous signal losses when probing moving vegetation, due to randomly varying speckle patterns. The work was supported by the Office of Naval Research.
NASA Astrophysics Data System (ADS)
Kochuparampil, Roshan Joseph
The advent of an era of abundant natural gas is making it an increasingly economical fuel source against incumbents such as crude oil and coal, in end-use sectors such as power generation, transportation and industrial chemical production, while also offering significant environmental benefits over these incumbents. Equipment manufacturers, in turn, are responding to widespread demand for power plants optimized for operation with natural gas. In several applications such as distributed power generation, gas transmission, and water pumping, stationary, spark-ignited, natural gas fueled internal combustion engines (ICEs) are the power plant of choice (over turbines) owing to their lower equipment and operational costs, higher thermal efficiencies across a wide load range, and the flexibility afforded to end-users when building fine-resolution horsepower topologies: modular size increments ranging from 100 kW -- 2 MW per ICE power plant compared to 2 -- 5 MW per turbine power plant. Under the U.S. Environment Protection Agency's (EPA) New Source Performance Standards (NSPS) and Reciprocating Internal Combustion Engine National Emission Standards for Hazardous Air Pollutants (RICE NESHAP) air quality regulations, these natural gas power plants are required to comply with stringent emission limits, with several states mandating even stricter emissions norms. In the case of rich-burn or stoichiometric natural gas ICEs, very high levels of sustained emissions reduction can be achieved through exhaust after-treatment that utilizes Non Selective Catalyst Reduction (NSCR) systems. The primary operational constraint with these systems is the tight air-fuel ratio (AFR) window of operation that needs to be maintained if the NSCR system is to achieve simultaneous reduction of carbon monoxide (CO), nitrogen oxides (NOx), total hydrocarbons (THC), volatile organic compounds (VOCs), and formaldehyde (CH 2O). Most commercially available AFR controllers utilizing lambda (oxygen) sensor feedback are unable to maintain engine AFR within the required range owing to drift in sensor output over time. In this thesis, the emissions compliance performance of an AFR controller is evaluated over a 6-month period on an engine driving a gas compressor in an active natural gas production field. This AFR controller differentiates itself from other commercially available products by employing a lambda sensor that has been engineered against sensor drift, making it better suited for natural gas engine applications. Also included in this study are the controller's responses to transient loads, diurnal performance, adaptability to seasonal variations in ambient temperature, fuel quality variations (in wellhead gas), engine health considerations for proper AFR control, and controller calibration sensitivity when replacing lambda sensors. During the first three months of operation and subsequent diurnal tests, the controller's performance as a multi-point AFR control system was consistent, demonstrating appropriate AFR adjustments to variation in engine operation, over a wide range of ambient conditions, despite high consumption rate of engine lubrication oil. For the remainder the test, the high levels of lubrication oil consumption, compromised the ability to verify controller performance.
NASA Technical Reports Server (NTRS)
Knowlton, Kelly; Andrews, Jane C.
2006-01-01
Every year, more than 280 million visitors tour our Nation s most treasured parks and wilderness areas. Unfortunately, many visitors are unable to see the spectacular vistas they expect because of white or brown haze in the air. Most of this haze is not natural; it is air pollution, carried by the wind often hundreds of miles from its origin. Some of the pollutants have been linked to serious health problems, such as asthma and other lung disorders, and even premature death. In addition, nitrates and sulfates contribute to acid rain formation, which contaminates rivers and lakes and erodes buildings and historical monuments. The U.S. Environmental Protection Agency RPOs (Regional Planning Organizations) have been tasked with monitoring and determining the nature and origin of haze in Class I scenic areas, and finding ways to reduce haze in order to improve visibility in these areas. The RPOs have developed an Internet-based air quality DST (Decision Support Tool) called FASTNET (Fast Aerosol Sensing Tools for Natural Event Tracking). While FASTNET incorporates a few satellite datasets, most of the data utilized by this DST comes from ground-based instrument networks. The problem is that in many areas the sensors are sparsely located, with long distances between them, causing difficulties in tracking haze over the United States, determining its source, and analyzing its content. Satellite data could help to fill in the data gaps and to supplement and verify ground-recorded air quality data. Although satellite data are now being used for air quality research applications, such data are not routinely used for environmental decision support, in part because of limited resources, difficulties with interdisciplinary data interpretation, and the need for advanced inter-agency partnerships. As a result, the validation and verification of satellite data for air quality operational system applications has been limited This candidate solution evaluates the usefulness of OMI (Ozone Monitoring Instrument) and TES (Tropospheric Emission Spectrometer) air quality data for the RPOs by comparing OMI and TES data with ground-based data that are acquired during identified episodes of air pollution. The air quality data from OMI and TES are of different spectral ranges than data from satellites currently included in FASTNET, giving them potential advantages over the existing satellites. If the OMI and TES data are shown to be useful to the RPOs, they would then be integrated into the FASTNET DST for use on an operational basis.
Village Green Project and Air Sensor Kits
This is a presentation for the OAQPS Teachers Workshop. Will provide a background overview on the Village Green Project and our air sensor kit for outreach, then have the teachers try putting it together.
Development of on package indicator sensor for real-time monitoring of meat quality
Shukla, Vivek; Kandeepan, G.; Vishnuraj, M. R.
2015-01-01
Aim: The aim was to develop an indicator sensor for real-time monitoring of meat quality and to compare the response of indicator sensor with meat quality parameters at ambient temperature. Materials and Methods: Indicator sensor was prepared using bromophenol blue (1% w/v) as indicator solution and filter paper as indicator carrier. Indicator sensor was fabricated by coating indicator solution onto carrier by centrifugation. To observe the response of indicator sensor buffalo meat was packed in polystyrene foam trays covered with PVC film and indicator sensor was attached to the inner side of packaging film. The pattern of color change in indicator sensor was monitored and compared with meat quality parameters viz. total volatile basic nitrogen, D-glucose, standard plate count and tyrosine value to correlate ability of indicator sensor for its suitability to predict the meat quality and storage life. Results: The indicator sensor changed its color from yellow to blue starting from margins during the storage period of 24 h at ambient temperature and this correlated well with changes in meat quality parameters. Conclusions: The indicator sensor can be used for real-time monitoring of meat quality as the color of indicator sensor changed from yellow to blue starting from margins when meat deteriorates with advancement of the storage period. Thus by observing the color of indicator sensor quality of meat and shelf life can be predicted. PMID:27047103
Yi, Wei-Ying; Leung, Kwong-Sak; Leung, Yee
2017-12-22
Urban air pollution has caused public concern globally because it seriously affects human life. Modern monitoring systems providing pollution information with high spatio-temporal resolution have been developed to identify personal exposures. However, these systems' hardware specifications and configurations are usually fixed according to the applications. They can be inconvenient to maintain, and difficult to reconfigure and expand with respect to sensing capabilities. This paper aims at tackling these issues by adopting the proposed Modular Sensor System (MSS) architecture and Universal Sensor Interface (USI), and modular design in a sensor node. A compact MSS sensor node is implemented and evaluated. It has expandable sensor modules with plug-and-play feature and supports multiple Wireless Sensor Networks (WSNs). Evaluation results show that MSS sensor nodes can easily fit in different scenarios, adapt to reconfigurations dynamically, and detect low concentration air pollution with high energy efficiency and good data accuracy. We anticipate that the efforts on system maintenance, adaptation, and evolution can be significantly reduced when deploying the system in the field.
2017-01-01
Urban air pollution has caused public concern globally because it seriously affects human life. Modern monitoring systems providing pollution information with high spatio-temporal resolution have been developed to identify personal exposures. However, these systems’ hardware specifications and configurations are usually fixed according to the applications. They can be inconvenient to maintain, and difficult to reconfigure and expand with respect to sensing capabilities. This paper aims at tackling these issues by adopting the proposed Modular Sensor System (MSS) architecture and Universal Sensor Interface (USI), and modular design in a sensor node. A compact MSS sensor node is implemented and evaluated. It has expandable sensor modules with plug-and-play feature and supports multiple Wireless Sensor Networks (WSNs). Evaluation results show that MSS sensor nodes can easily fit in different scenarios, adapt to reconfigurations dynamically, and detect low concentration air pollution with high energy efficiency and good data accuracy. We anticipate that the efforts on system maintenance, adaptation, and evolution can be significantly reduced when deploying the system in the field. PMID:29271952
NASA Astrophysics Data System (ADS)
Mieloszyk, M.; Opoka, S.; Ostachowicz, W.
2015-07-01
This paper presents an application of Fibre Bragg Grating (FBG) sensors for Structural Health Monitoring (SHM) of offshore wind energy support structure model. The analysed structure is a tripod equipped with 16 FBG sensors. From a wide variety of Operational Modal Analysis (OMA) methods Frequency Domain Decomposition (FDD) technique is used in this paper under assumption that the input loading is similar to a white noise excitation. The FDD method can be applied using different sets of sensors, i.e. the one which contains all FBG sensors and the other set of sensors localised only on a particular tripod's leg. The cases considered during investigation were as follows: damaged and undamaged scenarios, different support conditions. The damage was simulated as an dismantled flange on an upper brace in one of the tripod legs. First the model was fixed to an antishaker table and investigated in the air under impulse excitations. Next the tripod was submerged into water basin in order to check the quality of the measurement set-up in different environmental condition. In this case the model was excited by regular waves.
Electrochemical Measurement of Atmospheric Corrosion
NASA Technical Reports Server (NTRS)
DeArmond, Anna H.; Davis, Dennis D.; Beeson, Harold D.
1999-01-01
Corrosion of Shuttle thruster components in atmospheres containing high concentrations of nitrogen tetroxide (NTO) and water is an important issue in ground operations of bipropellant systems in humid locations. Measurements of the corrosivities of NTO-containing atmospheres and the responses of different materials to these atmospheres have been accomplished using an electrochemical sensor. The sensor is composed of alternating aluminum/titanium strips separated by thin insulating layers. Under high humidity conditions a thin film of water covers the surface of the sensor. Added NTO vapor reacts with the water film to form a conductive medium and establishes a galvanic cell. The current from this cell can be integrated with respect to time and related to the corrosion activity. The surface layer formed from humid air/NTO reacts in the same way as an aqueous solution of nitric acid. Nitric acid is generally considered an important agent in NTO corrosion situations. The aluminum/titanium sensor is unresponsive to dry air, responds slightly to humid air (> 75% RH), and responds strongly to the combination of humid air and NTO. The sensor response is a power function (n = 2) of the NTO concentration. The sensor does not respond to NTO in dry air. The response of other materials in this type of sensor is related to position of the material in a galvanic series in aqueous nitric acid. The concept and operation of this electrochemical corrosion measurement is being applied to other corrosive atmospheric contaminants such as hydrogen chloride, hydrogen fluoride, sulfur dioxide, and acidic aerosols.
NASA Astrophysics Data System (ADS)
Gaïor, R.; Al Samarai, I.; Berat, C.; Blanco Otano, M.; David, J.; Deligny, O.; Lebbolo, H.; Lecoz, S.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Mariş, I. C.; Montanet, F.; Repain, P.; Salamida, F.; Settimo, M.; Stassi, P.; Stutz, A.
2018-04-01
We present the GIGAS (Gigahertz Identification of Giant Air Shower) microwave radio sensor arrays of the EASIER project (Extensive Air Shower Identification with Electron Radiometers), deployed at the site of the Pierre Auger cosmic ray observatory. The aim of these novel arrays is to probe the intensity of the molecular bremsstrahlung radiation expected from the development of the extensive air showers produced by the interaction of ultra high energy cosmic rays in the atmosphere. In the designed setup, the sensors are embedded within the surface detector array of the Pierre Auger observatory allowing us to use the particle signals at ground level to trigger the radio system. A series of seven, then 61 sensors have been deployed in the C-band, followed by a new series of 14 higher sensitivity ones in the C-band and the L-band. The design, the operation, the calibration and the sensitivity to extensive air showers of these arrays are described in this paper.
Shimada, Youichi; Terayama, Yukio
2006-01-01
This report represents the development of the prototype transtibial prosthesis to assist a smooth and comfortable walking for an unilateral amputee. This prosthesis is composed of two air cylinders, solenoid valves, portable and small air tank for compressed air storage, a multiple sensor system and a microprocessor. Two air cylinders are located around the rods to act as antagonistic and agonistic muscles. The system causes flexion and extension of the foot plate jointed at the ankle with compressed air, injected -or discharged via a solenoid or electromagnetic valves. The valves or solenoids are controlled with a microprocessor (Microchip Technology Inc., PIC16F876), the microprocessor generates control signals to the interface circuits for valve opening and closing consistent with the foot position during the walking phase. The control patterns generated in the microprocessor are modified with feedback from the touch sensor, ankle joint angle sensor and the two dimensional acceleration sensor. The primary walking pattern for an individual amputee should be developed through the gait analysis with video.
2015-12-01
AFRL-RY-WP-TR-2015-0144 COGNITIVE RADIO LOW-ENERGY SIGNAL ANALYSIS SENSOR INTEGRATED CIRCUITS (CLASIC) A Broadband Mixed-Signal Iterative Down...See additional restrictions described on inside pages STINFO COPY AIR FORCE RESEARCH LABORATORY SENSORS DIRECTORATE WRIGHT-PATTERSON AIR FORCE...Signature// TODD KASTLE, Chief Spectrum Warfare Division Sensors Directorate This report is published in the interest of scientific and technical
2009-04-01
noses”, High Frequency Quartz Crystal Microbalance (HF- QCM ), and fluorescent polymer based sensors . The combination of the chemical binding of molecules...nose and uses HF- QCM technology. The hand-held product consists of a sampling unit and analyzer and contains an array of sensors and coatings which...i AU/ACSC/2763/2008-09 AIR COMMAND AND STAFF COLLEGE AIR UNIVERSITY THE NOSE KNOWS: DEVELOPING ADVANCED CHEMICAL SENSORS FOR THE REMOTE
NASA Astrophysics Data System (ADS)
Widodo, Slamet; Miftakul, Amin M.; Sutrisman, Adi
2018-02-01
There are many phenomena that human are exposed to toxins from certain types such as of CO2, CO2 and CH4 gases. The device used to detect large amounts of CO, CO2, and CH4 gas in air in enclosed spaces using MQ 135 gas sensors of different types based on the three sensitivity of the Gas. The results of testing the use of sensors MQ 135 on the gas content of CO, CO2 and CH4 received by the sensor is still in the form of ppm based on the maximum ppm detection range of each sensor. Active sensor detects CO 120 ppm gas, CO2 1600 ppm and CH4 1ppm "standby 1" air condition with intermediate rotary fan. Active sensor detects CO 30 ppm gas, CO2 490 ppm and CH4 7 ppm "Standby 2" with low rotating fan output. Fuzzy rulebase logic for motor speed when gas detection sensor CO, CO2, and CH4 output controls the motion speed of the fan blower. Active sensors detect CO 15 ppm, CO2 320 ppm and CH4 45 ppm "Danger" air condition with high fan spin fan. At the gas level of CO 15 ppm, CO2 390 ppm and CH4 3 ppm detect "normal" AC sensor with fan output stop spinning.
A One ppm NDIR Methane Gas Sensor with Single Frequency Filter Denoising Algorithm
Zhu, Zipeng; Xu, Yuhui; Jiang, Binqing
2012-01-01
A non-dispersive infrared (NDIR) methane gas sensor prototype has achieved a minimum detection limit of 1 parts per million by volume (ppm). The central idea of the design of the sensor is to decrease the detection limit by increasing the signal to noise ratio (SNR) of the system. In order to decrease the noise level, a single frequency filter algorithm based on fast Fourier transform (FFT) is adopted for signal processing. Through simulation and experiment, it is found that the full width at half maximum (FWHM) of the filter narrows with the extension of sampling period and the increase of lamp modulation frequency, and at some optimum sampling period and modulation frequency, the filtered signal maintains a noise to signal ratio of below 1/10,000. The sensor prototype provides the key techniques for a hand-held methane detector that has a low cost and a high resolution. Such a detector may facilitate the detection of leakage of city natural gas pipelines buried underground, the monitoring of landfill gas, the monitoring of air quality and so on.
Participatory measurements of individual exposure to air pollution in urban areas
NASA Astrophysics Data System (ADS)
Madelin, Malika; Duché, Sarah; Dupuis, Vincent
2016-04-01
Air pollution is a major environmental issue in urban areas. Chronic and high concentration exposure presents a health risk with cardiovascular and respiratory problems and longer term nervous, carcinogenic and endocrine problems. In addition to the estimations based on simulations of both background and regional pollution and of the pollution induced by the traffic, knowing exposure of each individual is a key issue. This exposure reflects the high variability of pollution at fine spatial and time scales, according to the proximity of emission sources and the urban morphology outside. The emergence of citizen science and the progress of miniaturized electronics, low-cost and accessible to (almost) everyone, offers new opportunities for the monitoring of air pollution, but also for the citizens' awareness of their individual exposure to air pollution. In this communication, we propose to present a participatory research project 'What is your air?' (project funded by the Île-de-France region), which aims at raising awareness on the theme of air quality, its monitoring with sensors assembled in a FabLab workshop and an online participatory mapping. Beyond the discussion on technical choices, the stages of manufacture or the sensor calibration procedures, we discuss the measurements made, in this case the fine particle concentration measurements, which are dated and georeferenced (communication via a mobile phone). They show high variability between the measurements (in part linked to the substrates, land use, traffic) and low daily contrasts. In addition to the analysis of the measurements and their comparison with the official data, we also discuss the choice of representation of information, including mapping, and therefore the message about pollution to communicate.
Field, M.E.; Sullivan, W.H.
A precision liquid level sensor utilizes a balanced bridge, each arm including an air dielectric line. Changes in liquid level along one air dielectric line imbalance the bridge and create a voltage which is directly measurable across the bridge.
Evaluating lateral boundary conditions in MATCH using retrieved observations from satellites
NASA Astrophysics Data System (ADS)
Andersson, Emma; Kahnert, Michael; Simpson, David; Devasthale, Abhay
2015-04-01
The role of hemispheric transport has gained large attention in regional chemical transport models due to its impact on both climate, air quality and visibility. The hemispheric transport in regional models are represented by the lateral boundary conditions (LBCs), where the inflow boundary specifies the domain beyond the model region and the outflow region will impact the stability of the advective transport solution. This study focuses on evaluating and implement LBCs from global chemical transport models for two important atmospheric tracers: carbon monoxide (CO) and ozone (O3). LBCs are derived from the hemispheric European Monitoring and Evaluation Programme (EMEP) model and the Model for Ozone and Related chemical Tracers (MOZART-4) over the time periods 2006-2012 and 2011-2012 respectively. Evaluation is done with observational data retrieved from the satellite sensors Measurements Of the Pollution In The Troposphere (MOPITT) and the Ozone Monitoring Instrument (OMI). The implementation of the LBCs is done in the regional chemical transport model Multiple scale atmospheric transport and chemistry (MATCH), developed by the Swedish Meteorological and Hydrological Institute (SMHI). The MATCH model is mostly used in simulations of the air quality over Europe on both on regional and local scales. In this study the model the domain is set over Europe. The LBC evaluation is done for the tropospheric column by smoothing the LBCs using satellite averaging kernels and a priori information. By retrieving the average profile for each month and lateral boundary, possible biases and also what global model that might be better suited for the LBCs in MATCH. The implementation will show how these biases proliferate through the MATCH model, and it will possibly be compared to satellite retrieved data from the sensor Atmospheric InfraRed Sounder (AIRS) inboard the satellite Aqua.
NASA Astrophysics Data System (ADS)
Drosoglou, Theano; Kouremeti, Natalia; Bais, Alkis; Zyrichidou, Irene; Li, Shu; Balis, Dimitris; Huang, Zhonghui
2016-04-01
A miniature MAX-DOAS system, Phaethon, has been developed at the Laboratory of Atmospheric Physics of the Aristotle University of Thessaloniki, Greece, for ground-based monitoring of column densities of atmospheric gases. Simultaneous measurements with two Phaethon systems at the city centre of Thessaloniki and at a rural location about 30 km away have shown that Phaethon provides NO2 and HCHO tropospheric column measurements of acceptable accuracy under both low and high air-pollution levels. Currently three systems have been deployed in areas with different pollution patterns to support air quality and satellite validation studies. In the framework of the EU FP7 Monitoring and Assessment of Regional air quality in China using space Observations, Project Of Long-term sino-european co-Operation, MarcoPolo project, one of the Phaethon systems has been installed since April 2015 in the Guangzhou region in China. Tropospheric NO2 and HCHO columns derived at Guangzhou during the first 10 months of operation are compared with corresponding retrievals from OMI/Aura and GOME-2/Metop-A and /Metop-B satellite sensors. The area is characterized by humid subtropical monsoon climate and cloud-free conditions are rather rare from early March to mid-October. Despite this limitation and the short period of operation of Phaethon in Guangzhou, the agreement between ground-based and satellite observations is generally good for both NO2 and HCHO. It appears that GOME-2 sensors seem to underestimate the tropospheric NO2, possibly due to their large pixel size, whereas the comparison with OMI data is better, especially when a small cloud fraction (< 0.2) is used for cloud screening.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Oliveira, Jorge Luiz Goes; Passos, Julio Cesar; Verschaeren, Ruud
Two-phase flow measurements were carried out using a resistive void fraction meter coupled to a venturi or orifice plate. The measurement system used to estimate the liquid and gas mass flow rates was evaluated using an air-water experimental facility. Experiments included upward vertical and horizontal flow, annular, bubbly, churn and slug patterns, void fraction ranging from 2% to 85%, water flow rate up to 4000 kg/h, air flow rate up to 50 kg/h, and quality up to almost 10%. The fractional root mean square (RMS) deviation of the two-phase mass flow rate in upward vertical flow through a venturi platemore » is 6.8% using the correlation of Chisholm (D. Chisholm, Pressure gradients during the flow of incompressible two-phase mixtures through pipes, venturis and orifice plates, British Chemical Engineering 12 (9) (1967) 454-457). For the orifice plate, the RMS deviation of the vertical flow is 5.5% using the correlation of Zhang et al. (H.J. Zhang, W.T. Yue, Z.Y. Huang, Investigation of oil-air two-phase mass flow rate measurement using venturi and void fraction sensor, Journal of Zhejiang University Science 6A (6) (2005) 601-606). The results show that the flow direction has no significant influence on the meters in relation to the pressure drop in the experimental operation range. Quality and slip ratio analyses were also performed. The results show a mean slip ratio lower than 1.1, when bubbly and slug flow patterns are encountered for mean void fractions lower than 70%. (author)« less
Radar coordination and resource management in a distributed sensor network using emergent control
NASA Astrophysics Data System (ADS)
Weir, B. S.; Sokol, T. M.
2009-05-01
As the list of anti-air warfare and ballistic missile defense missions grows, there is an increasing need to coordinate and optimize usage of radar resources across the netted force. Early attempts at this optimization involved top-down control mechanisms whereby sensors accept resource tasking orders from networked tracking elements. These approaches rely heavily on uncertain knowledge of sensor constraints and capabilities. Furthermore, advanced sensor systems may support self-defense missions of the host platform and are therefore unable to relinquish control to an external function. To surmount these issues, the use of bottom-up emergent control techniques is proposed. The information necessary to make quality, network-wide resource allocations is readily available to sensor nodes with access to a netted track picture. By assessing resource priorities relative to the network (versus local) track picture, sensors can understand the contribution of their resources to the netted force. This allows the sensors to apply resources where most needed and remove waste. Furthermore, simple local rules for resource usage, when properly constructed, allow sensors to obtain a globally optimal resource allocation without direct coordination (emergence). These results are robust to partial implementation (i.e., not all nodes upgraded at once) and failures on individual nodes (whether from casualty or reallocation to other sensor missions), and they leave resource control decisions in the hands of the sensor systems instead of an external function. This paper presents independent research and development work on emergent control of sensor resources and the impact to resource allocation and tracking performance.
NASA Astrophysics Data System (ADS)
Wang, Anbo; Miller, Mark S.; Gunther, Michael F.; Murphy, Kent A.; Claus, Richard O.
1993-03-01
A self-referencing technique compensating for fiber losses and source fluctuations in air-gap intensity-based optical fiber sensors is described and demonstrated. A resolution of 0.007 micron has been obtained over a measurement range of 0-250 microns for an intensity-based displacement sensor using this referencing technique. The sensor is shown to have minimal sensitivity to fiber bending losses and variations in the LED input power. A theoretical model for evaluation of step-index multimode optical fiber splice is proposed. The performance of the sensor as a displacement sensor agrees well with the theoretical analysis.
Teich, Sorin; Al-Rawi, Wisam; Heima, Masahiro; Faddoul, Fady F; Goldzweig, Gil; Gutmacher, Zvi; Aizenbud, Dror
2016-10-01
To evaluate the image quality generated by eight commercially available intraoral sensors. Eighteen clinicians ranked the quality of a bitewing acquired from one subject using eight different intraoral sensors. Analytical methods used to evaluate clinical image quality included the Visual Grading Characteristics method, which helps to quantify subjective opinions to make them suitable for analysis. The Dexis sensor was ranked significantly better than Sirona and Carestream-Kodak sensors; and the image captured using the Carestream-Kodak sensor was ranked significantly worse than those captured using Dexis, Schick and Cyber Medical Imaging sensors. The Image Works sensor image was rated the lowest by all clinicians. Other comparisons resulted in non-significant results. None of the sensors was considered to generate images of significantly better quality than the other sensors tested. Further research should be directed towards determining the clinical significance of the differences in image quality reported in this study. © 2016 FDI World Dental Federation.
Air Pollution Monitoring and Mining Based on Sensor Grid in London
Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John
2008-01-01
In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a two-layer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm. PMID:27879895
Air Pollution Monitoring and Mining Based on Sensor Grid in London.
Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John
2008-06-01
In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a twolayer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm.
A theoretical/experimental program to develop active optical pollution sensors
NASA Technical Reports Server (NTRS)
Mills, F. S.; Blais, R. N.; Kindle, E. C.
1977-01-01
Light detection and ranging (LIDAR) technology was applied to the assessment of air quality, and its usefulness was evaluated by actual field tests. Necessary hardware was successfully constructed and operated in the field. Measurements of necessary physical parameters, such as SO2 absorption coefficients were successfully completed and theoretical predictions of differential absorption performance were reported. Plume modeling improvements were proposed. A full scale field test of equipment, data analysis and auxiliary data support was conducted in Maryland during September 1976.
1981-04-01
pitch attitude (rad) Perturbation lateral path angle (rad) Mass density of air (slug-ft^) Time delay (sec) Perturbation bank angle (rad...terms of the sixth, say 6^. The solutions for u and 6 are Immediate from the constraints, and the system of equa- tions may be reduced by...These Idealized expressions neglect lags and -i 1 time delays due to sensor, computation and actuator dynamics (see Appen- "v :{ dix D for the
Integrated optics ring-resonator chemical sensor for detection of air contamination
NASA Technical Reports Server (NTRS)
Manfreda, A. M.; Homer, M. L.; Ksendzov, A.
2004-01-01
We report a silicon nitride-based ring resonator chemical sensor with sensing polymer coating. Its sensitivity to isopropanol in air is at least 50 ppm - well under the permissible exposure level of 400 ppm.
Intregrated optics ring-resonator chemical sensor for detection of air contamination
NASA Technical Reports Server (NTRS)
Ksendzov, Alexander; Homer, Margie L.; Manfreda, Allison M.
2004-01-01
We report a silicon nitride-based ring resonator chemical sensor with sensing polymer coating. Its sensitivity to isopropanol in air is at least 50 ppm - well under the permissible exposure level of 400 ppm.
Field, Michael E.; Sullivan, William H.
1985-01-01
A precision liquid level sensor utilizes a balanced R. F. bridge, each arm including an air dielectric line. Changes in liquid level along one air dielectric line imbalance the bridge and create a voltage which is directly measurable across the bridge.
Respirable particulate monitoring with remote sensors. (Public health ecology: Air pollution)
NASA Technical Reports Server (NTRS)
Severs, R. K.
1974-01-01
The feasibility of monitoring atmospheric aerosols in the respirable range from air or space platforms was studied. Secondary reflectance targets were located in the industrial area and near Galveston Bay. Multichannel remote sensor data were utilized to calculate the aerosol extinction coefficient and thus determine the aerosol size distribution. Houston Texas air sampling network high volume data were utilized to generate computer isopleth maps of suspended particulates and to establish the mass loading of the atmosphere. In addition, a five channel nephelometer and a multistage particulate air sampler were used to collect data. The extinction coefficient determined from remote sensor data proved more representative of wide areal phenomena than that calculated from on site measurements. It was also demonstrated that a significant reduction in the standard deviation of the extinction coefficient could be achieved by reducing the bandwidths used in remote sensor.
An Analysis of Peak Wind Speed Data from Collocated Mechanical and Ultrasonic Anemometers
NASA Technical Reports Server (NTRS)
Short, David A.; Wells, Leonard; Merceret, Francis J.; Roeder, William P.
2007-01-01
This study compared peak wind speeds reported by mechanical and ultrasonic anemometers at Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC) on the east central coast of Florida and Vandenberg Air Force Base (VAFB) on the central coast of California. Launch Weather Officers, forecasters, and Range Safety analysts need to understand the performance of wind sensors at CCAFS/KSC and VAFB for weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The legacy CCAFS/KSC and VAFB weather tower wind instruments are being changed from propeller-and-vane (CCAFS/KSC) and cup-and-vane (VAFB) sensors to ultrasonic sensors under the Range Standardization and Automation (RSA) program. Mechanical and ultrasonic wind measuring techniques are known to cause differences in the statistics of peak wind speed as shown in previous studies. The 45th Weather Squadron (45 WS) and the 30th Weather Squadron (30 WS) requested the Applied Meteorology Unit (AMU) to compare data between the RSA ultrasonic and legacy mechanical sensors to determine if there are significant differences. Note that the instruments were sited outdoors under naturally varying conditions and that this comparison was not designed to verify either technology. Approximately 3 weeks of mechanical and ultrasonic wind data from each range from May and June 2005 were used in this study. The CCAFS/KSC data spanned the full diurnal cycle, while the VAFB data were confined to 1000-1600 local time. The sample of 1-minute data from numerous levels on five different towers on each range totaled more than 500,000 minutes of data (482,979 minutes of data after quality control). The ten towers were instrumented at several levels, ranging from 12 ft to 492 ft above ground level. The ultrasonic sensors were collocated at the same vertical levels as the mechanical sensors and typically within 15 ft horizontally of each another. Data from a total of 53 RSA ultrasonic sensors, collocated with mechanical sensors were compared. The 1- minute average wind speed/direction and the 1-second peak wind speed/direction were compared.
NASA Astrophysics Data System (ADS)
Swadley, S. D.; Baker, N.; Derber, J.; Collard, A.; Hilton, F.; Ruston, B.; Bell, W.; Candy, B.; Kleespies, T. J.
2009-12-01
The NPOESS atmospheric sounding functionality will be accomplished using two separate sensor suites, the combined infrared (IR) and microwave (MW) sensor suite (CrIMSS), and the Microwave Imager/Sounder (MIS) instrument. CrIMSS consists of the Cross Track Infrared Sounder (CrIS) and the cross track Advanced Technology Microwave Sounder (ATMS), and is scheduled to fly on the NPOESS Preparatory Project (NPP), and NPOESS operational flight units C1 and C3. The MIS is a conical scanning polarimetric imager and sounder patterned after the heritage WindSat, and DMSP Special Sensor Microwave Imagers and Sounders (SSMI and SSMIS), and is scheduled for flight units C2, C3 and C4. ATMS combines the current operational Advanced Microwave Sounding Unit (AMSU) and the Microwave Humidity Sounder (MHS), but with an additional channel in the 51.76 GHz oxygen absorption region and 3 additional channels in the 165.5 and 183 GHz water vapor absorption band. CrIS is a Fourier Transform Spectrometer and will provide 159 shortwave IR channels, 433 mid-range IR channels, and 713 longwave IR channels. The heritage sensors for CrIS are the NASA Advanced Infrared Sounder (AIRS) and the MetOp-A Infrared Atmospheric Sounding Interferometer (IASI). Both AIRS and IASI are high quality, high spectral resolution sounders which represent a significant improvement in the effective vertical resolution over previous IR sounders. This presentation will give an overview of preparations underway for day-1 monitoring of NPP/NPOESS radiances, and subsequent operational radiance assimilation. These preparations capitalize on experience gained during the pre-launch preparations, sensor calibration/validation and operational assimilation for the heritage sensors. One important step is to use pre-flight sensor channel specifications, noise estimates and knowledge of the antenna patterns, to generate and test proxy NPP/NPOESS sensor observations in existing assimilation systems. Other critical factors for successful radiance assimilation include low noise measurements, channel sets that span the vertical space defined within the NWP model, a fast and accurate radiative transfer model, and bias correction schemes designed to remove systematic biases in the departures between the observed versus calculated radiances.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Humayun, Md Tanim; Divan, Ralu; Liu, Yuzi
Chemoresistive sensors based on multiwalled carbon nanotubes (MWCNTs) functionalized with SnO 2 nanocrystals (NCs) have great potential for detecting trace gases at low concentrations (single ppm levels) at room temperature, because the SnO 2 nanocrystals act as active sites for the chemisorption of gas molecules, and carbon nanotubes (CNTs) act as an excellent current carrying platform, allowing the adsorption of gas on SnO 2 to modulate the resistance of the CNTs. However, uniform conjugation of SnO 2 NCs with MWCNTs is challenging. An effective atomic layer deposition based approach to functionalize the surface of MWCNTs with SnO 2 NCs, resultingmore » in a novel CH 4 sensor with 10 ppm sensitivity, is presented in this paper. Scanning electron microscopy, transmission electron microscopy (TEM), energy dispersive x-ray spectroscopy, and Raman spectroscopy were implemented to study the morphology, elemental composition, and the crystal quality of SnO 2 functionalized MWCNTs. High resolution TEM images showed that the crystal quality of the functionalizing SnO 2 NCs was of high quality with clear lattice fringes and the dimension almost three times smaller than shown thus far in literature. A lift-off based photolithography technique comprising bilayer photoresists was optimized to fabricate SnO 2 functionalized MWCNTs-based chemoresistor sensor, which at room temperature can reliably sense below 10 ppm of CH4 in air. Such low level gas sensitivity, with significant reversible relative resistance change, is believed to be the direct result of the successful functionalization of the MWCNT surface by SnO 2 NCs.« less
Micromechanical Sensor for the Spectral Decomposition of Acoustic Signals
2012-02-01
8 Figure 2.2: Reverse Ballistic Air Gun ................................................................................. 9 Figure 2.3: A MEMS...Schematic of the Sensor including Sensor-to-Sensor Parasitic .................... 177 Figure 5.9: Schematic of Laser Machined Sensor...178 Figure 5.10: Laser Machined Sensor Mode 1
NASA Technical Reports Server (NTRS)
Hilderman, Don R.
2006-01-01
The purpose of the NASA Glenn Research Center Weather Information Communications (WINCOMM) project was to develop advanced communications and information technologies to enable the high-quality and timely dissemination of strategic weather information between the flight deck and ground users as well as tactical turbulence hazard information between relevant aircraft and to the ground. This report will document and reference accomplishments on the dissemination of weather information during the en route phase of flight from ground-based weather information providers to the flight deck (ground-to-air), from airborne meteorological sensors to ground users (air-to-ground), and weather turbulence and icing hazard information between relevant aircraft (air-to-air). In addition, references in this report will demonstrate the architecture necessary to implement and perform successful transmission and reception of weather information to the cockpit, show that weather information flow does not impact "normal" traffic, demonstrate the feasibility of operational implementation, and lay foundation for future data link development.
2004-03-06
NASA's DC-8 flying laboratory seen at sunset after a flight supporting the AirSAR 2004 Mesoamerica campaign. AirSAR 2004 Mesoamerica is a three-week expedition by an international team of scientists that uses an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR) which is located onboard NASA's DC-8 airborne laboratory. Scientists from many parts of the world including NASA's Jet Propulsion Laboratory are combining ground research done in several areas in Central America with NASA's AirSAR technology to improve and expand on the quality of research they are able to conduct. The radar, developed by NASA's Jet Propulsion Laboratory, can penetrate clouds and also collect data at night. Its high-resolution sensors operate at multiple wavelengths and modes, allowing AirSAR to see beneath treetops, through thin sand, and dry snow pack. AirSAR's 2004 campaign is a collaboration of many U.S. and Central American institutions and scientists, including NASA; the National Science Foundation; the Smithsonian Institution; National Geographic; Conservation International; the Organization of Tropical Studies; the Central American Commission for Environment and Development; and the Inter-American Development Bank.
2004-03-04
A spider photographed during NASA's AirSAR 2004 Mesoamerica campaign in the La Selva region of the Costa Rican rain forest. AirSAR 2004 Mesoamerica is a three-week expedition by an international team of scientists that uses an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR) which is located onboard NASA's DC-8 airborne laboratory. Scientists from many parts of the world including NASA's Jet Propulsion Laboratory are combining ground research done in several areas in Central America with NASA's AirSAR technology to improve and expand on the quality of research they are able to conduct. The radar, developed by NASA's Jet Propulsion Laboratory, can penetrate clouds and also collect data at night. Its high-resolution sensors operate at multiple wavelengths and modes, allowing AirSAR to see beneath treetops, through thin sand, and dry snow pack. AirSAR's 2004 campaign is a collaboration of many U.S. and Central American institutions and scientists, including NASA; the National Science Foundation; the Smithsonian Institution; National Geographic; Conservation International; the Organization of Tropical Studies; the Central American Commission for Environment and Development; and the Inter-American Development Bank.
Field, M.E.; Sullivan, W.H.
1985-01-29
A precision liquid level sensor utilizes a balanced R. F. bridge, each arm including an air dielectric line. Changes in liquid level along one air dielectric line imbalance the bridge and create a voltage which is directly measurable across the bridge. 2 figs.
Embedded Triboelectric Active Sensors for Real-Time Pneumatic Monitoring.
Fu, Xian Peng; Bu, Tian Zhao; Xi, Feng Ben; Cheng, Ting Hai; Zhang, Chi; Wang, Zhong Lin
2017-09-20
Pneumatic monitoring sensors have great demands for power supply in cylinder systems. Here, we present an embedded sliding triboelectric nanogenerator (TENG) in air cylinder as active sensors for position and velocity monitoring. The embedded TENG is composed of a circular poly(tetrafluoroethylene) polymer and a triangular copper electrode. The working mechanism as triboelectric active sensors and electric output performance are systematically investigated. By integrating into the pneumatic system, the embedded triboelectric active sensors have been used for real-time air pressure/flow monitoring and energy storage. Air pressures are measured from 0.04 to 0.12 MPa at a step of 0.02 MPa with a sensitivity of 49.235 V/MPa, as well as airflow from 50 to 250 L/min at a step of 50 L/min with a sensitivity of 0.002 μA·min/L. This work has first demonstrated triboelectric active sensors for pneumatic monitoring and may promote the development of TENG in intelligent pneumatic system.
NASA Technical Reports Server (NTRS)
Knowlton, Kelly; Andrews, Jane C.; Ryan, Robert E.
2007-01-01
Studies have shown that vegetation is directly sensitive to changes in the diffuse-to-global irradiance ratio and that increased percentage of diffuse irradiation can accelerate photosynthesis. Therefore, measurements of diffuse versus global irradiance could be useful for monitoring crop productivity and overall vegetative health as they relate to the total amount of particulates in the air that result from natural disasters or anthropogenic (manmade) causes. While the components of solar irradiance are measured by satellite and surface sensors and calculated with atmospheric models, disagreement exists between the results, creating a need for more accurate and comprehensive retrievals of atmospheric aerosol parameters. Two satellite sensors--APS and VIIRS--show promise for retrieving aerosol properties at an unprecedented level of accuracy. APS is expected to be launched in December 2008. The planned launch date for VIIRS onboard NPP is September 2009. Identified partners include the USDA s ARS, North Carolina State University, Purdue Climate Change Research Center, and the Cooperative Institute for Research in the Atmosphere at Colorado State University. Although at present no formal DSSs (decision support systems) require accurate values of diffuse-to-global irradiance, this parameter is sufficiently important that models are being developed that will incorporate these measurements. This candidate solution is aligned with the Agricultural Efficiency and Air Quality National Applications.
Andrews, Jr., William H.; Thompson, Cyril V [Knoxville, TN; Vass, Arpad A [Oak Ridge, TN; Smith, Rob R [Knoxville, TN
2011-12-13
An apparatus and a method for detecting a burial site of human remains are disclosed. An air stream is drawn through an air intake conduit from locations near potential burial sites of human remains. The air stream is monitored by one or more chemical sensors to determine whether the air stream includes one or more indicator compounds selected from halogenated compounds, hydrocarbons, nitrogen-containing compounds, sulfur-containing compounds, acid/ester compounds, oxygen-containing compounds, and naphthalene-containing compounds. When it is determined that an indicator compound is present in the air stream, this indicates that a burial site of human remains is below or nearby. Each sensor may be in electrical communication with an indicator that signals when the sensor has detected the presence of the indicator compound in the air stream. In one form, the indicator compound is a halogenated compound and/or a hydrocarbon, and the presence of the halogenated compound and/or the hydrocarbon in the air stream indicates that a burial site of human remains is below or nearby.
NASA Astrophysics Data System (ADS)
Tom, Michael; Trujillo, Edward
1994-06-01
Integrated infrared (IR) sensors which exploit modular avionics concepts can provide features such as operational flexibility, enhanced stealthiness, and ease of maintenance to meet the demands of tactical, airborne sensor systems. On-board, tactical airborne sensor systems perform target acquisition, tracking, identification, threat warning, missile launch detection, and ground mapping in support of situation awareness, self-defense, navigation, target attack, weapon support, and reconnaissance activities. The use of sensor suites for future tactical aircraft such as US Air Force's multirole fighter require a blend of sensor inputs and outputs that may vary over time. It is expected that special-role units of these tactical aircraft will be formed to conduct tasks and missions such as anti-shipping, reconnaissance, or suppression of enemy air defenses.
Szulczyński, Bartosz; Wasilewski, Tomasz; Wojnowski, Wojciech; Majchrzak, Tomasz; Dymerski, Tomasz; Namieśnik, Jacek; Gębicki, Jacek
2017-01-01
This review paper presents different ways to apply a measurement instrument of e-nose type to evaluate ambient air with respect to detection of the odorants characterized by unpleasant odour in a vicinity of municipal processing plants. An emphasis was put on the following applications of the electronic nose instruments: monitoring networks, remote controlled robots and drones as well as portable devices. Moreover, this paper presents commercially available sensors utilized in the electronic noses and characterized by the limit of quantification below 1 ppm v/v, which is close to the odour threshold of some odorants. Additionally, information about bioelectronic noses being a possible alternative to electronic noses and their principle of operation and application potential in the field of air evaluation with respect to detection of the odorants characterized by unpleasant odour was provided. PMID:29156597
Szulczyński, Bartosz; Wasilewski, Tomasz; Wojnowski, Wojciech; Majchrzak, Tomasz; Dymerski, Tomasz; Namieśnik, Jacek; Gębicki, Jacek
2017-11-19
This review paper presents different ways to apply a measurement instrument of e-nose type to evaluate ambient air with respect to detection of the odorants characterized by unpleasant odour in a vicinity of municipal processing plants. An emphasis was put on the following applications of the electronic nose instruments: monitoring networks, remote controlled robots and drones as well as portable devices. Moreover, this paper presents commercially available sensors utilized in the electronic noses and characterized by the limit of quantification below 1 ppm v / v , which is close to the odour threshold of some odorants. Additionally, information about bioelectronic noses being a possible alternative to electronic noses and their principle of operation and application potential in the field of air evaluation with respect to detection of the odorants characterized by unpleasant odour was provided.
A Wireless, Passive Sensor for Quantifying Packaged Food Quality
Tan, Ee Lim; Ng, Wen Ni; Shao, Ranyuan; Pereles, Brandon D.; Ong, Keat Ghee
2007-01-01
This paper describes the fabrication of a wireless, passive sensor based on an inductive-capacitive resonant circuit, and its application for in situ monitoring of the quality of dry, packaged food such as cereals, and fried and baked snacks. The sensor is made of a planar inductor and capacitor printed on a paper substrate. To monitor food quality, the sensor is embedded inside the food package by adhering it to the package's inner wall; its response is remotely detected through a coil connected to a sensor reader. As food quality degrades due to increasing humidity inside the package, the paper substrate absorbs water vapor, changing the capacitor's capacitance and the sensor's resonant frequency. Therefore, the taste quality of the packaged food can be indirectly determined by measuring the change in the sensor's resonant frequency. The novelty of this sensor technology is its wireless and passive nature, which allows in situ determination of food quality. In addition, the simple fabrication process and inexpensive sensor material ensure a low sensor cost, thus making this technology economically viable. PMID:28903195
Roopa Manjunatha, G; Rajanna, K; Mahapatra, D Roy; Nayak, M M; Krishnaswamy, Uma Maheswari; Srinivasa, R
2013-12-01
Design and development of a piezoelectric polyvinylidene fluoride (PVDF) thin film based nasal sensor to monitor human respiration pattern (RP) from each nostril simultaneously is presented in this paper. Thin film based PVDF nasal sensor is designed in a cantilever beam configuration. Two cantilevers are mounted on a spectacle frame in such a way that the air flow from each nostril impinges on this sensor causing bending of the cantilever beams. Voltage signal produced due to air flow induced dynamic piezoelectric effect produce a respective RP. A group of 23 healthy awake human subjects are studied. The RP in terms of respiratory rate (RR) and Respiratory air-flow changes/alterations obtained from the developed PVDF nasal sensor are compared with RP obtained from respiratory inductance plethysmograph (RIP) device. The mean RR of the developed nasal sensor (19.65 ± 4.1) and the RIP (19.57 ± 4.1) are found to be almost same (difference not significant, p > 0.05) with the correlation coefficient 0.96, p < 0.0001. It was observed that any change/alterations in the pattern of RIP is followed by same amount of change/alterations in the pattern of PVDF nasal sensor with k = 0.815 indicating strong agreement between the PVDF nasal sensor and RIP respiratory air-flow pattern. The developed sensor is simple in design, non-invasive, patient friendly and hence shows promising routine clinical usage. The preliminary result shows that this new method can have various applications in respiratory monitoring and diagnosis.
NASA Astrophysics Data System (ADS)
Hübert, T.; Lang, C.
2012-09-01
An online monitoring of environmental and inherent product parameters is required during transportation and storage of fruit and vegetables to avoid quality degradation and spoilage. The control of transpiration losses is suggested as an indicator for fruit freshness by humidity measurements. For that purpose, an electronic sensor is surrounded by a wet porous fiber material which is in contact with the outer atmosphere. Transpiration reduces the water content of the porous material and thus also the internal water activity. The sensor system, known as "artificial fruit," measures the relative humidity and temperature inside the wet material. Humidity and temperature data are collected and transmitted on demand by a miniaturized radio communication unit. The decrease in the measured relative humidity has been calibrated against the mass loss of tomatoes under different external influencing parameters such as temperature, humidity, and air flow. Current battery life allows the sensor system, embedded in a fruit crate, to transmit data on transpiration losses via radio transmission for up to two weeks.
Characterization and dynamics of air pollutants in the Lower Rio Grande Valley
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mejia-Velazquez, G.M.; Sheya, S.A.; Dworzanski, J.
1999-07-01
The Lower Rio Grande Valley (LRGV) has become a region of increasing interest because of its rapid economic development and the increased international border crossing traffic, as well as for its extensive agricultural activities. Over the past few years air pollution problems in the region have been reported by the population. However, very few air quality studies have been performed in the area. In this paper some results of a study to demonstrate the feasibility of a comprehensive (criteria pollutant + VOC/SVOC + PM{sub FINE}) air pollutant dynamics characterization and modeling study in the LRGV are presented and discussed. Themore » study involved both sides of the US/Mexican border and used. A highly mobile monitoring station equipped with a broad array of physical and chemical samplers and sensors was used in the study in two periods in December, 1995 and March,1998. PM10/PM2.5 and NO{sub x} (the latter only in the March 1998 study) concentrations were measured in Reynosa, Rio Bravo and Matamoros, Mexico, as well as Hidalgo, Brownsville and along the Freeway between Brownsville and McAllen on Texas. The photochemical model predicted peak ozone concentrations that reached, and on some days exceeded, air quality standards. The concurrent PM10/PM2.5 study involved both physical (size distributed counting) and time-resolved (2-hourly) organic chemical (VOC/SVOC type PM{sub FINE} adsorbates) characterization methods. Recently completed multivariate data analysis results from a December 1995 study at one of the sites (Hidalgo international bridge) are being presented to illustrate the capabilities of the time-resolved PM{sub FINE} characterization approach. The results of this work show that the LRGV region does not appear to have grave air pollution problems yet. However, with the increase in traffic activities over the next few years, air quality is likely to deteriorate.« less
NASA Astrophysics Data System (ADS)
Tubío-Pardavila, R.; Vigil, S. A.; Puig-Suari, J.; Aguado Agelet, F.
2014-12-01
There is a requirement for low cost in-situ measurements of environmental parameters such as air quality, meteorological data, and water quality in remote areas. Currently available solutions for such measurements include remote sensing from satellite and aircraft platforms, and in-situ measurements from mobile and aircraft platforms. Fixed systems such as eddy covariance networks, tall towers, and the Total Carbon Column Observing Network (TCCON) are providing precision greenhouse gas measurements. Within this context, the HUMSAT system designed by the University of Vigo (Spain) will complement existing high-precision measurement systems with low cost in-situ ground based sensors in remote locations using a constellation of CubeSats as a communications relay. The HUMSAT system standardizes radio communications in between deployed sensors and the CubeSats of the constellation, which act as store and forward satellites to ground stations for uploading to the internet. Current ground stations have been established at the University of Vigo (Spain) and California Polytechnic State University (Cal Poly). Users of the system may deploy their own environmental sensors to meet local requirements. The sensors will be linked to a low-cost satellite data transceiver using a standard HUMSAT protocol. The transceiver is capable of receiving data from the HUMSAT constellation to remotely reconfigure sensors without the need of physically going to the sensor location. This transceiver uses a UHF channel around 437 MHz to exchange short data messages with the sensors. These data messages can contain up to 32 bytes of useful information and are transmitted at a speed around 300 bps. The protocol designed for this system handles the access to the channel by all these elements and guarantees a correct transmission of the information in such an scenario. The University of Vigo has launched the first satellite of the constellation, the HUMSAT-D CubeSat in November 2013 and has deployed sensors in Spain and Brazil. Sensors will be also deployed by Cal Poly in the near future. In the following months, the SERPENS CubeSAT Mission, a joint project of the University of Brasilia and the University of Vigo will launch the second CubeSat of the constellation.
Battista, L; Sciuto, S A; Scorza, A
2013-03-01
In this work, a simple and low-cost air flow sensor, based on a novel fiber-optic sensing technique has been developed for monitoring air flows rates supplied by a neonatal ventilator to support infants in intensive care units. The device is based on a fiber optic sensing technique allowing (a) the immunity to light intensity variations independent by measurand and (b) the reduction of typical shortcomings affecting all biomedical fields (electromagnetic interference and patient electrical safety). The sensing principle is based on the measurement of transversal displacement of an emitting fiber-optic cantilever due to action of air flow acting on it; the fiber tip displacement is measured by means of a photodiode linear array, placed in front of the entrance face of the emitting optical fiber in order to detect its light intensity profile. As the measurement system is based on a detection of the illumination pattern, and not on an intensity modulation technique, it results less sensitive to light intensity fluctuation independent by measurand than intensity-based sensors. The considered technique is here adopted in order to develop two different configurations for an air flow sensor suitable for the measurement of air flow rates typically occurring during mechanical ventilation of newborns: a mono-directional and a bi-directional transducer have been proposed. A mathematical model for the air flow sensor is here proposed and a static calibration of two different arrangements has been performed: a measurement range up to 3.00 × 10(-4) m(3)∕s (18.0 l∕min) for the mono-directional sensor and a measurement range of ±3.00 × 10(-4) m(3)∕s (±18.0 l∕min) for the bi-directional sensor are experimentally evaluated, according to the air flow rates normally encountered during tidal breathing of infants with a mass lower than 10 kg. Experimental data of static calibration result in accordance with the proposed theoretical model: for the mono-directional configuration, the coefficient of determination r(2) is equal to 0.997; for the bi-directional configuration, the coefficient of determination r(2) is equal to 0.990 for positive flows (inspiration) and 0.988 for negative flows (expiration). Measurement uncertainty δQ of air flow rate has been evaluated by means of the propagation of distributions and the percentage error in the arrangement of bi-directional sensor ranges from a minimum of about 0.5% at -18.0 l∕min to a maximum of about 9% at -12.0 l∕min.
NASA Astrophysics Data System (ADS)
Battista, L.; Sciuto, S. A.; Scorza, A.
2013-03-01
In this work, a simple and low-cost air flow sensor, based on a novel fiber-optic sensing technique has been developed for monitoring air flows rates supplied by a neonatal ventilator to support infants in intensive care units. The device is based on a fiber optic sensing technique allowing (a) the immunity to light intensity variations independent by measurand and (b) the reduction of typical shortcomings affecting all biomedical fields (electromagnetic interference and patient electrical safety). The sensing principle is based on the measurement of transversal displacement of an emitting fiber-optic cantilever due to action of air flow acting on it; the fiber tip displacement is measured by means of a photodiode linear array, placed in front of the entrance face of the emitting optical fiber in order to detect its light intensity profile. As the measurement system is based on a detection of the illumination pattern, and not on an intensity modulation technique, it results less sensitive to light intensity fluctuation independent by measurand than intensity-based sensors. The considered technique is here adopted in order to develop two different configurations for an air flow sensor suitable for the measurement of air flow rates typically occurring during mechanical ventilation of newborns: a mono-directional and a bi-directional transducer have been proposed. A mathematical model for the air flow sensor is here proposed and a static calibration of two different arrangements has been performed: a measurement range up to 3.00 × 10-4 m3/s (18.0 l/min) for the mono-directional sensor and a measurement range of ±3.00 × 10-4 m3/s (±18.0 l/min) for the bi-directional sensor are experimentally evaluated, according to the air flow rates normally encountered during tidal breathing of infants with a mass lower than 10 kg. Experimental data of static calibration result in accordance with the proposed theoretical model: for the mono-directional configuration, the coefficient of determination r2 is equal to 0.997; for the bi-directional configuration, the coefficient of determination r2 is equal to 0.990 for positive flows (inspiration) and 0.988 for negative flows (expiration). Measurement uncertainty δQ of air flow rate has been evaluated by means of the propagation of distributions and the percentage error in the arrangement of bi-directional sensor ranges from a minimum of about 0.5% at -18.0 l/min to a maximum of about 9% at -12.0 l/min.
Krawczyk, M.; Namiesnik, J.
2003-01-01
A new technique is presented for continuous measurements of hydrogen contamination by air in the upper explosive limit range. It is based on the application of a catalytic combustion sensor placed in a cell through which the tested sample passes. The air content is the function of the quantity of formed heat during catalytic combustion of hydrogen inside the sensor. There is the possibility of using the method in industrial installations by using hydrogen for cooling electric current generators. PMID:18924620
Dense rain forest in the La Selva region of Costa Rica
2004-03-05
Dense rain forest in the La Selva region of Costa Rica. AirSAR 2004 Mesoamerica is a three-week expedition by an international team of scientists that uses an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR) which is located onboard NASA's DC-8 airborne laboratory. Scientists from many parts of the world including NASA's Jet Propulsion Laboratory are combining ground research done in several areas in Central America with NASA's AirSAR technology to improve and expand on the quality of research they are able to conduct. The radar, developed by NASA's Jet Propulsion Laboratory, can penetrate clouds and also collect data at night. Its high-resolution sensors operate at multiple wavelengths and modes, allowing AirSAR to see beneath treetops, through thin sand, and dry snow pack. AirSAR's 2004 campaign is a collaboration of many U.S. and Central American institutions and scientists, including NASA; the National Science Foundation; the Smithsonian Institution; National Geographic; Conservation International; the Organization of Tropical Studies; the Central American Commission for Environment and Development; and the Inter-American Development Bank.
The rise of low-cost sensing for managing air pollution in cities.
Kumar, Prashant; Morawska, Lidia; Martani, Claudio; Biskos, George; Neophytou, Marina; Di Sabatino, Silvana; Bell, Margaret; Norford, Leslie; Britter, Rex
2015-02-01
Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, while addressing the major challenges for their effective implementation. Copyright © 2014 Elsevier Ltd. All rights reserved.
Detecting Airborne Mercury by Use of Gold Nanowires
NASA Technical Reports Server (NTRS)
Ryan, Margaret; Shevade, Abhijit; Kisor, Adam; Homer, Margie; Soler, Jessica; Mung, Nosang; Nix, Megan
2009-01-01
Like the palladium chloride (PdCl2) films described in the immediately preceding article, gold nanowire sensors have been found to be useful for detecting airborne elemental mercury at concentrations on the order of parts per billion (ppb). Also like the PdCl2 films, gold nanowire sensors can be regenerated under conditions much milder than those necessary for regeneration of gold films that have been used as airborne-Hg sensors. The interest in nanowire sensors in general is prompted by the expectation that nanowires of a given material covering a given surface may exhibit greater sensitivity than does a film of the same material because nanowires have a greater surface area. In preparation for experiments to demonstrate this sensor concept, sensors were fabricated by depositing gold nanowires, variously, on microhotplate or microarray sensor substrates. In the experiments, the electrical resistances were measured while the sensors were exposed to air at a temperature of 25 C and relative humidity of about 30 percent containing mercury at various concentrations from 2 to 70 ppb (see figure). The results of this and other experiments have been interpreted as signifying that sensors of this type can detect mercury at ppb concentrations in room-temperature air and can be regenerated by exposure to clean flowing air at temperatures <40 C.
NASA Astrophysics Data System (ADS)
Eiriksson, D.; Jones, A. S.; Horsburgh, J. S.; Cox, C.; Dastrup, D.
2017-12-01
Over the past few decades, advances in electronic dataloggers and in situ sensor technology have revolutionized our ability to monitor air, soil, and water to address questions in the environmental sciences. The increased spatial and temporal resolution of in situ data is alluring. However, an often overlooked aspect of these advances are the challenges data managers and technicians face in performing quality control on millions of data points collected every year. While there is general agreement that high quantities of data offer little value unless the data are of high quality, it is commonly understood that despite efforts toward quality assurance, environmental data collection occasionally goes wrong. After identifying erroneous data, data managers and technicians must determine whether to flag, delete, leave unaltered, or retroactively correct suspect data. While individual instrumentation networks often develop their own QA/QC procedures, there is a scarcity of consensus and literature regarding specific solutions and methods for correcting data. This may be because back correction efforts are time consuming, so suspect data are often simply abandoned. Correction techniques are also rarely reported in the literature, likely because corrections are often performed by technicians rather than the researchers who write the scientific papers. Details of correction procedures are often glossed over as a minor component of data collection and processing. To help address this disconnect, we present case studies of quality control challenges, solutions, and lessons learned from a large scale, multi-watershed environmental observatory in Northern Utah that monitors Gradients Along Mountain to Urban Transitions (GAMUT). The GAMUT network consists of over 40 individual climate, water quality, and storm drain monitoring stations that have collected more than 200 million unique data points in four years of operation. In all of our examples, we emphasize that scientists should remain skeptical and seek independent verification of sensor data, even for sensors purchased from trusted manufacturers.
NASA Technical Reports Server (NTRS)
2014-01-01
Topics covered include: Innovative Software Tools Measure Behavioral Alertness; Miniaturized, Portable Sensors Monitor Metabolic Health; Patient Simulators Train Emergency Caregivers; Solar Refrigerators Store Life-Saving Vaccines; Monitors Enable Medication Management in Patients' Homes; Handheld Diagnostic Device Delivers Quick Medical Readings; Experiments Result in Safer, Spin-Resistant Aircraft; Interfaces Visualize Data for Airline Safety, Efficiency; Data Mining Tools Make Flights Safer, More Efficient; NASA Standards Inform Comfortable Car Seats; Heat Shield Paves the Way for Commercial Space; Air Systems Provide Life Support to Miners; Coatings Preserve Metal, Stone, Tile, and Concrete; Robots Spur Software That Lends a Hand; Cloud-Based Data Sharing Connects Emergency Managers; Catalytic Converters Maintain Air Quality in Mines; NASA-Enhanced Water Bottles Filter Water on the Go; Brainwave Monitoring Software Improves Distracted Minds; Thermal Materials Protect Priceless, Personal Keepsakes; Home Air Purifiers Eradicate Harmful Pathogens; Thermal Materials Drive Professional Apparel Line; Radiant Barriers Save Energy in Buildings; Open Source Initiative Powers Real-Time Data Streams; Shuttle Engine Designs Revolutionize Solar Power; Procedure-Authoring Tool Improves Safety on Oil Rigs; Satellite Data Aid Monitoring of Nation's Forests; Mars Technologies Spawn Durable Wind Turbines; Programs Visualize Earth and Space for Interactive Education; Processor Units Reduce Satellite Construction Costs; Software Accelerates Computing Time for Complex Math; Simulation Tools Prevent Signal Interference on Spacecraft; Software Simplifies the Sharing of Numerical Models; Virtual Machine Language Controls Remote Devices; Micro-Accelerometers Monitor Equipment Health; Reactors Save Energy, Costs for Hydrogen Production; Cameras Monitor Spacecraft Integrity to Prevent Failures; Testing Devices Garner Data on Insulation Performance; Smart Sensors Gather Information for Machine Diagnostics; Oxygen Sensors Monitor Bioreactors and Ensure Health and Safety; Vision Algorithms Catch Defects in Screen Displays; and Deformable Mirrors Capture Exoplanet Data, Reflect Lasers.
Hall effect sensors embedded within two-pole toothless stator assembly
NASA Technical Reports Server (NTRS)
Denk, Joseph (Inventor); Grant, Richard J. (Inventor)
1994-01-01
A two-pole toothless PM machine employs Hall effect sensors to indicate the position of the machine's rotor relative to power windings in the machine's stator. The Hall effect sensors are located in the main magnetic air gap underneath the power windings. The main magnetic air gap is defined by an outer magnetic surface of the rotor and an inner surface of the stator's flux collector ring.
NASA Technical Reports Server (NTRS)
Ifju, Peter
2002-01-01
Micro Air Vehicles (MAVs) will be developed for tracking individuals, locating terrorist threats, and delivering remote sensors, for surveillance and chemical/biological agent detection. The tasks are: (1) Develop robust MAV platform capable of carrying sensor payload. (2) Develop fully autonomous capabilities for delivery of sensors to remote and distant locations. The current capabilities and accomplishments are: (1) Operational electric (inaudible) 6-inch MAVs with novel flexible wing, providing superior aerodynamic efficiency and control. (2) Vision-based flight stability and control (from on-board cameras).
Satellite remote sensing of particulate matter air quality: the cloud-cover problem.
Christopher, Sundar A; Gupta, Pawan
2010-05-01
Satellite assessments of particulate matter (PM) air quality that use solar reflectance methods are dependent on availability of clear sky; in other words, mass concentrations of PM less than 2.5 microm in aerodynamic diameter (PM2.5) cannot be estimated from satellite observations under cloudy conditions or bright surfaces such as snow/ice. Whereas most ground monitors measure PM2.5 concentrations on an hourly basis regardless of cloud conditions, space-borne sensors can only estimate daytime PM2.5 in cloud-free conditions, therefore introducing a bias. In this study, an estimate of this clear-sky bias is provided from monthly to yearly time scales over the continental United States. One year of the Moderate Resolution Imaging Spectroradiometer (MODIS) 550-nm aerosol optical depth (AOD) retrievals from Terra and Aqua satellites, collocated with 371 U.S. Environmental Protection Agency (EPA) ground monitors, have been analyzed. The results indicate that the mean differences between PM2.5 reported by ground monitors and PM2.5 calculated from ground monitors during the satellite overpass times during cloud-free conditions are less than +/- 2.5 microg m(-3), although this value varies by season and location. The mean differences are not significant as calculated by t tests (alpha = 0.05). On the basis of this analysis, it is concluded that for the continental United States, cloud cover is not a major problem for inferring monthly to yearly PM2.5 from space-borne sensors.
Impact of Temperature and UV Irradiation on Dynamics of NO2 Sensors Based on ZnO Nanostructures
Pustelny, Tadeusz
2017-01-01
The main object of this study is the improvement of the dynamics of NO2 sensors based on ZnO nanostructures. Investigations presented in this paper showed that the combination of temperature and ultraviolet (UV) activation of the sensors can significantly decrease the sensor response and regeneration times. In comparison with the single activation method (elevated temperature or UV), these times for 1 ppm of NO2 decreased from about 10 min (or more) to less than 40 s. In addition, at the optimal conditions (200 °C and UV), sensors were very stable, were fully scalable (in the range on NO2 concentration of 1–20 ppm) and baseline drift was significantly reduced. Furthermore, in this paper, extensive studies of the influence of temperature and carrier gas (nitrogen and air) on NO2 sensing properties of the ZnO nanostructures were conducted. The NO2 sensing mechanisms of the sensors operating at elevated temperatures and under UV irradiation were also discussed. Our study showed that sensor responses to NO2 and response/regeneration times are comparable from sensor to sensor in air and nitrogen conditions, which suggests that the proposed simple technology connected with well-chosen operation conditions is repeatable. The estimated limit of detection of the sensors is within the level of ≈800 ppb in nitrogen and ≈700 ppb in air. PMID:29019924
Improved Airborne Gravity Results Using New Relative Gravity Sensor Technology
NASA Astrophysics Data System (ADS)
Brady, N.
2013-12-01
Airborne gravity data has contributed greatly to our knowledge of subsurface geophysics particularly in rugged and otherwise inaccessible areas such as Antarctica. Reliable high quality GPS data has renewed interest in improving the accuracy of airborne gravity systems and recent improvements in the electronic control of the sensor have increased the accuracy and ability of the classic Lacoste and Romberg zero length spring gravity meters to operate in turbulent air conditions. Lacoste and Romberg type gravity meters provide increased sensitivity over other relative gravity meters by utilizing a mass attached to a horizontal beam which is balanced by a ';zero length spring'. This type of dynamic gravity sensor is capable of measuring gravity changes on the order of 0.05 milliGals in laboratory conditions but more commonly 0.7 to 1 milliGal in survey use. The sensor may have errors induced by the electronics used to read the beam position as well as noise induced by unwanted accelerations, commonly turbulence, which moves the beam away from its ideal balance position otherwise known as the reading line. The sensor relies on a measuring screw controlled by a computer which attempts to bring the beam back to the reading line position. The beam is also heavily damped so that it does not react to most unwanted high frequency accelerations. However this heavily damped system is slow to react, particularly in turns where there are very high Eotvos effects. New sensor technology utilizes magnetic damping of the beam coupled with an active feedback system which acts to effectively keep the beam locked at the reading line position. The feedback system operates over the entire range of the system so there is now no requirement for a measuring screw. The feedback system operates at very high speed so that even large turbulent events have minimal impact on data quality and very little, if any, survey line data is lost because of large beam displacement errors. Airborne testing along with results from ground based van testing and laboratory results have shown that the new sensor provides more consistent gravity data, as measured by repeated line surveys, as well as preserving the inherent sensitivity of the Lacoste and Romberg zero length spring design. The sensor also provides reliability during survey operation as there is no mechanical counter screw. Results will be presented which show the advantages of the new sensor system over the current technology in both data quality and survey productivity. Applications include high resolution geoid mapping, crustal structure investigations and resource mapping of minerals, oil and gas.
Application of Micro-Electro-Mechanical Sensors Contactless NDT of Concrete Structures.
Ham, Suyun; Popovics, John S
2015-04-17
The utility of micro-electro-mechanical sensors (MEMS) for application in air-coupled (contactless or noncontact) sensing to concrete nondestructive testing (NDT) is studied in this paper. The fundamental operation and characteristics of MEMS are first described. Then application of MEMS sensors toward established concrete test methods, including vibration resonance, impact-echo, ultrasonic surface wave, and multi-channel analysis of surface waves (MASW), is demonstrated. In each test application, the performance of MEMS is compared with conventional contactless and contact sensing technology. Favorable performance of the MEMS sensors demonstrates the potential of the technology for applied contactless NDT efforts. To illustrate the utility of air-coupled MEMS sensors for concrete NDT, as compared with conventional sensor technology.
Song, Jiangxin; Lin, Jintian; Tang, Jialei; Liao, Yang; He, Fei; Wang, Zhaohui; Qiao, Lingling; Sugioka, Koji; Cheng, Ya
2014-06-16
We report on fabrication of a microtoroid resonator of a high-quality factor (i.e., Q-factor of ~3.24 × 10(6) measured under the critical coupling condition) integrated in a microfluidic channel using femtosecond laser three-dimensional (3D) micromachining. Coupling of light into and out of the microresonator has been realized with a fiber taper that is reliably assembled with the microtoroid. The assembly of the fiber to the microtoroid is achieved by welding the fiber taper onto the sidewall of the microtoroid using CO2 laser irradiation. The integrated microresonator maintains a high Q-factor of 3.21 × 10(5) as measured in air, which should still be sufficient for many sensing applications. We test the functionality of the integrated optofluidic sensor by performing bulk refractive index sensing of purified water doped with tiny amount of salt. It is shown that a detection limit of ~1.2 × 10(-4) refractive index unit can be achieved. Our result showcases the capability of integration of high-Q microresonators with complex microfluidic systems using femtosecond laser 3D micromachining.
NASA Astrophysics Data System (ADS)
Koutzoukis, S.; Jenerette, D.; Chandler, M.; Wang, J.; Ge, C.; Ripplinger, J.
2017-12-01
Urban air quality and climate directly affect resident health. The Los Angeles (LA) Basin is a highly populated metropolitan area, with widespread point sources of ozone (O3) precursors (NOx , Volatile Organic Compounds, CO) from fossil fuel combustion. The LA basin exists on a coast-to-mountain gradient, with increasing temperatures towards the Transverse Ranges, which rise to 1700m. Frequently not compliant with 8-hour O3 standards, the LA and South Coast Air Basins are designated as severe and extreme non-attainment areas. Summer weather in the LA basin is characterized by a persistent high pressure system, creating an inversion that traps air pollutants, including O3 precursors, coupled with physical geography that blocks prevailing upper atmosphere air flow. These interactions make neighborhood-level O3 levels more variable than common regional models. Over the summer of 2017, we investigated the importance of local meteorology, wind patterns and air temperature, in transporting and mixing ozone precursors from point sources along the coast-to-mountain gradient. We deployed a network of six EPA federal equivalent method ozone and meteorological sensors in three campaigns in the LA basin along the coast-to-mountain transect. Each campaign, we collaborated with citizen scientists to deploy three sensor stations in two, 4 km2 quadrats, for a total of six high-resolution 4 km2 pixels. O3 concentrations vary greatly along the transect. At the coastal sites, daily O3 ranges from 0ppm to 60ppm and the range increases at the inland sites, to 100ppm. At all sites, there was a positive relationship between wind speed, air temperature, and O3 concentration, with increasing correlation inland. The Pearson correlation coefficient between wind speed and O3 concentration doubles from the coast to inland, and triples between air temperature and O3. The site-specific relationships between O3 and wind direction and temperature vary, suggesting neighborhood-effects from local point sources.
Community Air Sensor Network (CAIRSENSE) Project: Lower Cost, Continuous Ambient Monitoring Methods
CAIRSENSE Project presentation was given at the 108th Annual Meeting of the Air & Waste Management Associate in June 2015. The presentation provides an overview of the CAIRSENSE Project and general info about the sensors used in the CAIRSENSE Project.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Phillips, Mark C.; Craig, Ian M.
2013-11-03
We analyze the long-term performance and stability of a trace-gas sensor based on an external cavity quantum cascade laser using data collected over a one-year period in a building air monitoring application.
EPA activities related to emerging air sensor technology
This slide set was developed through contributions of NERL and NRMRL research groups and organized to explain the diversity of ongoing research related to emerging air sensor technology for an international audience. Gayle will be walking OAQPS through the slide set in advance o...
2004-03-08
NASA Dryden Mission Manager Walter Klein poses with school children that visited the airport during AirSAR 2004. In spanish, he explained to them the mission of the DC-8 AirSAR 2004 Mesoamerican campaign in Costa Rica. AirSAR 2004 Mesoamerica is a three-week expedition by an international team of scientists that uses an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR) which is located onboard NASA's DC-8 airborne laboratory. Scientists from many parts of the world including NASA's Jet Propulsion Laboratory are combining ground research done in several areas in Central America with NASA's AirSAR technology to improve and expand on the quality of research they are able to conduct. The radar, developed by NASA's Jet Propulsion Laboratory, can penetrate clouds and also collect data at night. Its high-resolution sensors operate at multiple wavelengths and modes, allowing AirSAR to see beneath treetops, through thin sand, and dry snow pack. AirSAR's 2004 campaign is a collaboration of many U.S. and Central American institutions and scientists, including NASA; the National Science Foundation; the Smithsonian Institution; National Geographic; Conservation International; the Organization of Tropical Studies; the Central American Commission for Environment and Development; and the Inter-American Development Bank.
Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka
2017-04-09
Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.
NASA Astrophysics Data System (ADS)
Coogan, A.; Avanzi, F.; Akella, R.; Conklin, M. H.; Bales, R. C.; Glaser, S. D.
2017-12-01
Automatic meteorological and snow stations provide large amounts of information at dense temporal resolution, but data quality is often compromised by noise and missing values. We present a new gap-filling and cleaning procedure for networks of these stations based on Kalman filtering and expectation maximization. Our method utilizes a multi-sensor, regime-switching Kalman filter to learn a latent process that captures dependencies between nearby stations and handles sharp changes in snowfall rate. Since the latent process is inferred using observations across working stations in the network, it can be used to fill in large data gaps for a malfunctioning station. The procedure was tested on meteorological and snow data from Wireless Sensor Networks (WSN) in the American River basin of the Sierra Nevada. Data include air temperature, relative humidity, and snow depth from dense networks of 10 to 12 stations within 1 km2 swaths. Both wet and dry water years have similar data issues. Data with artificially created gaps was used to quantify the method's performance. Our multi-sensor approach performs better than a single-sensor one, especially with large data gaps, as it learns and exploits the dominant underlying processes in snowpack at each site.
Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka
2017-01-01
Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM2.5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM2.5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web. PMID:28397776
Singer, B C; Delp, W W
2018-04-23
The ability to inexpensively monitor PM 2.5 to identify sources and enable controls would advance residential indoor air quality (IAQ) management. Consumer IAQ monitors incorporating low-cost optical particle sensors and connections with smart home platforms could provide this service if they reliably detect PM 2.5 in homes. In this study, particles from typical residential sources were generated in a 120 m 3 laboratory and time-concentration profiles were measured with 7 consumer monitors (2-3 units each), 2 research monitors (Thermo pDR-1500, MetOne BT-645), a Grimm Mini Wide-Range Aerosol Spectrometer (GRM), and a Tapered Element Oscillating Microbalance with Filter Dynamic Measurement System (FDMS), a Federal Equivalent Method for PM 2.5 . Sources included recreational combustion (candles, cigarettes, incense), cooking activities, an unfiltered ultrasonic humidifier, and dust. FDMS measurements, filter samples, and known densities were used to adjust the GRM to obtain time-resolved mass concentrations. Data from the research monitors and 4 of the consumer monitors-AirBeam, AirVisual, Foobot, Purple Air-were time correlated and within a factor of 2 of the estimated mass concentrations for most sources. All 7 of the consumer and both research monitors substantially under-reported or missed events for which the emitted mass was comprised of particles smaller than 0.3 μm diameter. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
2004-03-06
NASA Dryden DC-8 maintenance crew members inspect the aircraft prior to take-off. L-R; Scott Silver, Paul Ristrim and Mike Lakowski. AirSAR 2004 Mesoamerica is a three-week expedition by an international team of scientists that uses an all-weather imaging tool, called the Airborne Synthetic Aperture Radar (AirSAR) which is located onboard NASA's DC-8 airborne laboratory. Scientists from many parts of the world including NASA's Jet Propulsion Laboratory are combining ground research done in several areas in Central America with NASA's AirSAR technology to improve and expand on the quality of research they are able to conduct. The radar, developed by NASA's Jet Propulsion Laboratory, can penetrate clouds and also collect data at night. Its high-resolution sensors operate at multiple wavelengths and modes, allowing AirSAR to see beneath treetops, through thin sand, and dry snow pack. AirSAR's 2004 campaign is a collaboration of many U.S. and Central American institutions and scientists, including NASA; the National Science Foundation; the Smithsonian Institution; National Geographic; Conservation International; the Organization of Tropical Studies; the Central American Commission for Environment and Development; and the Inter-American Development Bank.
Holcomb, L. Gary; Sandoval, Leo; Hutt, Bob
1998-01-01
Tilt has been the nemesis of horizontal long period seismology since its inception. Modern horizontal long period seismometers with their long natural periods are incredibly sensitive to tilt. They can sense tilts smaller than 10-11 radians. To most readers, this is just a very very small number, so we will begin with an example, which should help to illustrate just how small 10-11 radians is.Suppose we have an absolutely rigid rod which is approximately 4170 kilometers long; this just happens to be the Rand McNally map scaled crow flight distance between Los Angeles and Boston. Tilting this rod 10-11 radians corresponds to raising one end of the rod 0.0000417 meters. Alas, this is just another very very small number! However, this corresponds to slipping a little less than one third a sheet of ordinary copying paper under one end of this perfectly rigid rod. To clarify, we mean, take a sheet of paper just like the paper this report is printed on and split it a little less than one third in the thickness direction, then put it under the end of the 4170 kilometer long rod! This will tilt the rod 10-11 radians.Real world seismometers are nowhere near the length of this rod. A KS-54000 is about two meters long. Tilting a rod only two meters long 10~n radians corresponds to moving one end of this rod a mere 0.00000000002 meters or 0.02 millimicrons. As one of the authors old math teachers used to say, "That's PDS" (PDS = Pretty Damn Small). Unfortunately, the long period seismologist does not have the luxury of ignoring PDS numbers when it suits him as the mathematician frequently does. He must live in the real world in which tilts this small create severe contamination of long period seismic data.At periods longer than 20 seconds, tilt noise contaminates the long period data from all instruments installed on or near the earth's surface. Many years of experimentation revealed that installing the sensors at depth in deep mines drastically reduced the level of tilt noise in long period data. However, low levels of tilt noise persisted even at great depth; this noise was caused by air convection in the vault in which the sensors were installed. Over the years, methods were developed to control the air motion with mechanical barriers (boxes) around the sensors and by stratifying (creating a situation in which the air temperature increases with height) the air in the vault near the seismometer. These methods decreased tilt noise in deep mines to very low levels. However, deep mines, that are economically and environmentally suitable and accessible to seismology, are not plentiful and are not evenly distributed over the earth's surface. Therefore, the borehole deployable Teledyne Geotech KS-36000 and later the KS-54000 sensor systems were developed to fulfill the need for instruments that could be installed at depth wherever high quality long period data was desired. Early in the development program, it became evident to the Teledyne Geotech personnel that air convection within the borehole was going to be a significant problem in KS deployments. Experimental and theoretical investigations conducted by Teledyne Geotech (see Douze and Sherwin, 1975, and Sherwin and Cook, 1976) produced a list of recommended installation procedures for reducing the effects of air convection. These procedures consisted of wrapping the sensor in a relatively thin layer of foam insulation, filling the free space volume in the vicinity of the centralizer-bail assembly with foam insulation, and the installation of styrofoam hole plugs immediately above the cable strain relief assembly at the top of the sensor package and at the top of the borehole. This technology has performed quite satisfactorily for over 20 years but evidence of tilt noise in the system output has persisted throughout the KS deployment program (the evidence was that the horizontal components were usually noisier than the vertical components) even in deep boreholes. Some deep borehole sites have been plagued by quite high levels of horizontal noise. Therefore, there has been a definite need for a new technique for controlling low level tilt noise in deep boreholes and the use of sand has been under consideration for several years.Figure 1 contains conceptual illustrations of both the conventional holelock installed KS sensor system and the same sensor installed in sand. This figure demonstrates the major differences between the two installation methods. The curved arrows in the borehole on the left in the figure denote possible air convection cells which are believed to be the source of tilt noise in some of the conventional installations. This air motion is eliminated in a sand installation by filling most of the free air volume surrounding the seismometer with sand as shown in the right hand portion of the figure. The sand actually performs two functions; it prevents air motion and provides a remarkably ridgid clamping of the seismometer in the borehole. This report presents the results of quantitative experimental investigations into the effectiveness of controlling low level air convection in seismic borehole installations with sand. The main body of the experimental effort consisted of installing two KS-540001 sensor systems in closely spaced shallow boreholes, allowing the sensors to reach equilibrium operation, and then pouring sand into both boreholes to observe any changes caused by pouring sand into the holes. The hypothesis of the experiment was that the sand would fill up the entire free air volume between the sensor package and the borehole walls thereby preventing movement of the air in the vicinity of the sensor package. The validity of this hypothesis had been qualitatively proven by earlier experiments at ASL and by the sand installations at the IRIS/ASL stations ANMO in 1995 and COLA in 1996. This experiment documents the degree of improved noise levels to be expected if KS instruments are installed in sand instead of in the conventional manner.
NASA Astrophysics Data System (ADS)
Shikida, M.; Naito, J.; Yokota, T.; Kawabe, T.; Hayashi, Y.; Sato, K.
2009-10-01
We developed a novel catheter-type flow sensor for measuring the aspirated- and inspired-air characteristics trans-bronchially. An on-wall in-tube thermal flow sensor is mounted inside the tube, and it is used as a measurement tool in a bronchoscope. The external diameter of the tube is less than a few mm, and therefore, it can evaluate the flow characteristics in the small bronchial region. We newly developed a fabrication process to miniaturize it to less than 2.0 mm in the external diameter by using a heat shrinkable tube. A film sensor fabricated by photolithography was inserted into the tube by hand. By applying a heat shrinking process, the film was automatically mounted on the inner wall surface, and the outer size of the tube was miniaturized to almost half its original size. The final inner and outer diameters of the tube were 1.0 mm and 1.8 mm, respectively. The relationship between the input power of the sensor and the flow rate obeyed King's equation in both forward and reverse flow conditions. The sensor output dependence on ambient temperature was also studied, and the curve obtained at 39.2 °C was used as the calibration curve in animal experiments. The sensor characteristics under reciprocating flow were studied by using a ventilator, and we confirmed that the sensor was able to measure the reciprocating flow at 2.0 Hz. Finally, we successfully measured the aspirated- and inspired-air characteristics in the air passage of a rat.
Mixed-mode VLSI optic flow sensors for in-flight control of a micro air vehicle
NASA Astrophysics Data System (ADS)
Barrows, Geoffrey L.; Neely, C.
2000-11-01
NRL is developing compact optic flow sensors for use in a variety of small-scale navigation and collision avoidance tasks. These sensors are being developed for use in micro air vehicles (MAVs), which are autonomous aircraft whose maximum dimension is on the order of 15 cm. To achieve desired weight specifications of 1 - 2 grams, mixed-signal VLSI circuitry is being used to develop compact focal plane sensors that directly compute optic flow. As an interim proof of principle, we have constructed a sensor comprising a focal plane sensor head with on-chip processing and a back-end PIC microcontroller. This interim sensors weighs approximately 25 grams and is able to measure optic flow with real-world and low-contrast textures. Variations of this sensor have been used to control the flight of a glider in real-time to avoid collisions with walls.
Identification of Air Force Emerging Technologies and Militarily Significant Emerging Technologies.
1985-08-31
taking an integrated approach to avionics and EU, the various sensors and receivers on the aircraft can time-share the use of common signal processors...functions mentioned above has required, in addition to a separate sensor or antenna, a totally independent electronics suite. Many of the advanced...Classification A3. IMAGING SENSOR AUTOPROCESSOR The Air Force has contracted with Rockwell International and Honeywell in this work. Rockwell’s work is
Design and Analysis of a New Hair Sensor for Multi-Physical Signal Measurement
Yang, Bo; Hu, Di; Wu, Lei
2016-01-01
A new hair sensor for multi-physical signal measurements, including acceleration, angular velocity and air flow, is presented in this paper. The entire structure consists of a hair post, a torsional frame and a resonant signal transducer. The hair post is utilized to sense and deliver the physical signals of the acceleration and the air flow rate. The physical signals are converted into frequency signals by the resonant transducer. The structure is optimized through finite element analysis. The simulation results demonstrate that the hair sensor has a frequency of 240 Hz in the first mode for the acceleration or the air flow sense, 3115 Hz in the third and fourth modes for the resonant conversion, and 3467 Hz in the fifth and sixth modes for the angular velocity transformation, respectively. All the above frequencies present in a reasonable modal distribution and are separated from interference modes. The input-output analysis of the new hair sensor demonstrates that the scale factor of the acceleration is 12.35 Hz/g, the scale factor of the angular velocity is 0.404 nm/deg/s and the sensitivity of the air flow is 1.075 Hz/(m/s)2, which verifies the multifunction sensitive characteristics of the hair sensor. Besides, the structural optimization of the hair post is used to improve the sensitivity of the air flow rate and the acceleration. The analysis results illustrate that the hollow circular hair post can increase the sensitivity of the air flow and the II-shape hair post can increase the sensitivity of the acceleration. Moreover, the thermal analysis confirms the scheme of the frequency difference for the resonant transducer can prominently eliminate the temperature influences on the measurement accuracy. The air flow analysis indicates that the surface area increase of hair post is significantly beneficial for the efficiency improvement of the signal transmission. In summary, the structure of the new hair sensor is proved to be feasible by comprehensive simulation and analysis. PMID:27399716
Micro-controller based air pressure monitoring instrumentation system using optical fibers as sensor
NASA Astrophysics Data System (ADS)
Hazarika, D.; Pegu, D. S.
2013-03-01
This paper describes a micro-controller based instrumentation system to monitor air pressure using optical fiber sensors. The principle of macrobending is used to develop the sensor system. The instrumentation system consists of a laser source, a beam splitter, two multi mode optical fibers, two Light Dependent Resistance (LDR) based timer circuits and a AT89S8252 micro-controller. The beam splitter is used to divide the laser beam into two parts and then these two beams are launched into two multi mode fibers. One of the multi mode fibers is used as the sensor fiber and the other one is used as the reference fiber. The use of the reference fiber is to eliminate the environmental effects while measuring the air pressure magnitude. The laser beams from the sensor and reference fibers are applied to two identical LDR based timer circuits. The LDR based timer circuits are interfaced to a micro-controller through its counter pins. The micro-controller samples the frequencies of the timer circuits using its counter-0 and counter-1 and the counter values are then processed to provide the measure of air pressure magnitude.
Photo-acoustic sensor for detection of oil contamination in compressed air systems.
Lassen, Mikael; Harder, David Baslev; Brusch, Anders; Nielsen, Ole Stender; Heikens, Dita; Persijn, Stefan; Petersen, Jan C
2017-02-06
We demonstrate an online (in-situ) sensor for continuous detection of oil contamination in compressed air systems complying with the ISO-8573 standard. The sensor is based on the photo-acoustic (PA) effect. The online and real-time PA sensor system has the potential to benefit a wide range of users that require high purity compressed air. Among these are hospitals, pharmaceutical industries, electronics manufacturers, and clean room facilities. The sensor was tested for sensitivity, repeatability, robustness to molecular cross-interference, and stability of calibration. Explicit measurements of hexane (C6H14) and decane (C10H22) vapors via excitation of molecular C-H vibrations at approx. 2950 cm-1 (3.38 μm) were conducted with a custom made interband cascade laser (ICL). For the decane measurements a (1 σ) standard deviation (STD) of 0.3 ppb was demonstrated, which corresponds to a normalized noise equivalent absorption (NNEA) coefficient for the prototype PA sensor of 2.8×10-9 W cm-1 Hz1/2.
TiO2-TiO2 composite resistive humidity sensor: ethanol crosssensitivity
NASA Astrophysics Data System (ADS)
Ghalamboran, Milad; Saedi, Yasin
2016-03-01
The fabrication method and characterization results of a TiO2-TiO2 composite bead used for humidity sensing along with its negative cross-sensitivity to ethanol vapor are reported. The bead shaped resistive sample sensors are fabricated by the drop-casting of a TiO2 slurry on two Pt wire segments. The dried bead is pre-fired at 750°C and subsequently impregnated with a Ti-based sol. The sample is ready for characterization after a thermal annealing at 600°C in air. Structurally, the bead is a composite of the micron-sized TiO2 crystallites embedded in a matrix of nanometric TiO2 particle aggregates. The performance of the beads as resistive humidity sensors is recorded at room temperature in standard humidity level chambers. Results evince the wide dynamic range of the sensors fabricated in the low relative humidity range. While the sensor conductance is not sensitive to ethanol vapor in dry air, in humid air, sensor's responses are negatively affected by the contaminant.
Tunable Impedance Spectroscopy Sensors via Selective Nanoporous Materials.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nenoff, Tina M.; Small, Leo J
Impedance spectroscopy was leveraged to directly detect the sorption of I 2 by selective adsorption into nanoporous metal organic frameworks (MOF). Films of three different types of MOF frameworks, respectively, were drop cast onto platinum interdigitated electrodes, dried, and exposed to gaseous I 2 at 25, 40, or 70 C. The MOF frameworks varied in topology from small pores (equivalent to I 2 diameter) to large pore frameworks. The combination of the chemistry of the framework and pore size dictated quantity and kinetics of I 2 adsorption. Air, argon, methanol, and water were found to produce minimal changes in ZIF-8more » impedance. Independent of MOF framework characteristics, all resultant sensors showed high response to I 2 in air. As an example of sensor output, I 2 was readily detected at 25 C in air within 720 s of exposure, using an un-optimized sensor geometry with a small pored MOF. Further optimization of sensor geometry, decreasing MOF film thicknesses and maximizing sensor capacitance, will enable faster detection of trace I 2 .« less
Fault Tolerant Computer Network Study
1980-04-01
2. 1.2. 2 Air Data The air data function processes air pressures, temperature , and angle- of-attack measurements, and provides calibrated airspeed...attitude direction indicator. 2.1.5.2 Fixtaking Sensors used for fixtaking include the radar (in ground map mode), head- up display (for visual...VFR interdiction mission. The radar (ground map mode) is also the primary sensor at night and in adverse weather if the target presents a