Use of Whatman-41 filters in air quality sampling networks (with applications to elemental analysis)
NASA Technical Reports Server (NTRS)
Neustadter, H. E.; Sidik, S. M.; King, R. B.; Fordyce, J. S.; Burr, J. C.
1974-01-01
The operation of a 16-site parallel high volume air sampling network with glass fiber filters on one unit and Whatman-41 filters on the other is reported. The network data and data from several other experiments indicate that (1) Sampler-to-sampler and filter-to-filter variabilities are small; (2) hygroscopic affinity of Whatman-41 filters need not introduce errors; and (3) suspended particulate samples from glass fiber filters averaged slightly, but not statistically significantly, higher than from Whatman-41-filters. The results obtained demonstrate the practicability of Whatman-41 filters for air quality monitoring and elemental analysis.
Dlugokencky, E. J. [National Oceanic and Atmospheric Administration, Boulder, Colorado (USA); Lang, P. M. [National Oceanic and Atmospheric Administration, Boulder, Colorado (USA); Masarie, K. A. [National Oceanic and Atmospheric Administration, Boulder, Colorado (USA); Steele, L. P. [Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria, Australia
1994-01-01
This data base presents atmospheric methane (CH4) mixing ratios from flask air samples collected over the period 1983-1993 by the National Oceanic and Atmospheric Administration, Climate Monitoring and Diagnostics Laboratory's (NOAA/CMDL's) global cooperative air sampling network. Air samples were collected approximately once per week at 44 fixed sites (37 of which were still active at the end of 1993). Samples were also collected at 5 degree latitude intervals along shipboard cruise tracks in the Pacific Ocean between North America and New Zealand (or Australia) and at 3 degree latitude intervals along cruise tracks in the South China Sea between Singapore and Hong Kong. The shipboard measurements were made approximately every 3 weeks per latitude zone by each of two ships in the Pacific Ocean and approximately once every week per latitude zone in the South China Sea. All samples were analyzed for CH4 at the NOAA/CMDL laboratory in Boulder, Colorado, by gas chromatography with flame ionization detection, and each aliquot was referenced to the NOAA/CMDL methane standard scale. In addition to providing the complete set of atmospheric CH4 measurements from flask air samples collected at the NOAA/CMDL network sites, this data base also includes files which list monthly mean mixing ratios derived from the individual flask air measurements. These monthly summary data are available for 35 of the fixed sites and 21 of the shipboard sampling sites.
Conway, Thomas [NOAA Climate Monitoring and Diagnostics Laboratory, Boulder, CO (USA); Tans, Pieter [NOAA Climate Monitoring and Diagnostics Laboratory, Boulder, CO (USA)
2009-01-01
The National Oceanic and Atmospheric Administration's Climate Monitoring and Diagnostics Laboratory (NOAA/CMDL) has measured CO2 in air samples collected weekly at a global network of sites since the late 1960s. Atmospheric CO2 mixing ratios reported in these files were measured by a nondispersive infrared absorption technique in air samples collected in glass flasks. All CMDL flask samples are measured relative to standards traceable to the World Meteorological Organization (WMO) CO2 mole fraction scale. These measurements constitute the most geographically extensive, carefully calibrated, internally consistent atmospheric CO2 data set available and are essential for studies aimed at better understanding the global carbon cycle budget.
EVALUATION OF THE FILTER PACK FOR LONG-DURATION SAMPLING OF AMBIENT AIR
A 14-week filter pack (FP) sampler evaluation field study was conducted at a site near Bondville, IL to investigate the impact of weekly sampling duration. Simultaneous samples were collected using collocated filter packs (FP) from two independent air quality monitoring networks...
Novelli, P. C.; Masarie, K. A.
1994-01-01
Individual site files provide CO mixing ratios in parts per billion (ppb) (ppb = parts in 109 by mole fraction) based on measurements from the NOAA/CMDL Cooperative Air Sampling Network beginning 1988. Data are provided through June 1993 for stations at which the first sample was collected before July 1991. All samples were analyzed for CO at the NOAA/CMDL laboratory in Boulder by gas chromatography with mercuric oxide reduction detection, and all measurements are referenced to the CMDL CO scale (Novelli et al., 1991, Novelli et al., 1994).
Federal Register 2010, 2011, 2012, 2013, 2014
2013-06-20
... restricted by statute. FOR FURTHER INFORMATION CONTACT: Charles M. Petko, Office of Radiation and Indoor Air... national network of stations collecting sampling media that include air, precipitation, drinking water, and milk. Samples are sent to EPA's National Air and Radiation Environmental Laboratory (NAREL) in...
PRECISION OF ATMOSPHERIC DRY DEPOSITION DATA FROM THE CLEAN AIR STATUS AND TRENDS NETWORK (CASTNET)
A collocated, dry deposition sampling program was begun in January 1987 by the US Environmental Protection Agency to provide ongoing estimates of the overall precision of dry deposition and supporting data entering the Clean Air Status and Trends Network (CASTNet) archives Duplic...
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
Characterizing air quality data from complex network perspective.
Fan, Xinghua; Wang, Li; Xu, Huihui; Li, Shasha; Tian, Lixin
2016-02-01
Air quality depends mainly on changes in emission of pollutants and their precursors. Understanding its characteristics is the key to predicting and controlling air quality. In this study, complex networks were built to analyze topological characteristics of air quality data by correlation coefficient method. Firstly, PM2.5 (particulate matter with aerodynamic diameter less than 2.5 μm) indexes of eight monitoring sites in Beijing were selected as samples from January 2013 to December 2014. Secondly, the C-C method was applied to determine the structure of phase space. Points in the reconstructed phase space were considered to be nodes of the network mapped. Then, edges were determined by nodes having the correlation greater than a critical threshold. Three properties of the constructed networks, degree distribution, clustering coefficient, and modularity, were used to determine the optimal value of the critical threshold. Finally, by analyzing and comparing topological properties, we pointed out that similarities and difference in the constructed complex networks revealed influence factors and their different roles on real air quality system.
NASA Astrophysics Data System (ADS)
Montzka, S. A.
2016-12-01
Measurements from global surface-based air sampling networks provide a fundamental understanding of how and why concentrations of long-lived trace gases are changing over time. Results from these networks are used to quantify trace-gas concentrations and their time-dependent changes on global and smaller scales, and thus provide a means to quantify emission rates, loss frequencies, and mixing processes. Substantial advances in measurement and sampling technologies and the ability of these programs to create and maintain reliable gas standards mean that spatial concentration gradients and time-dependent changes are often very reliably measured. The presence of multiple independent networks allows an assessment of this reliability. Furthermore, recent global `snap-shot' surveys (e.g., HIPPO and ATom) and ongoing atmospheric profiling programs help us assess the ability of surface-based data to describe concentration distributions throughout most of the atmosphere ( 80% of its mass). In this overview talk, I'll explore the usefulness and limitations of existing long-term, ongoing sampling network programs and their advantages and disadvantages for characterizing concentrations on global and regional scales, and how recent advances (and short-term sampling programs) help us assess the accuracy of the surface networks to provide estimates of source and sink magnitudes, and inter-annual variability in both.
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.
Determination of beryllium concentrations in UK ambient air
NASA Astrophysics Data System (ADS)
Goddard, Sharon L.; Brown, Richard J. C.; Ghatora, Baljit K.
2016-12-01
Air quality monitoring of ambient air is essential to minimise the exposure of the general population to toxic substances such as heavy metals, and thus the health risks associated with them. In the UK, ambient air is already monitored under the UK Heavy Metals Monitoring Network for a number of heavy metals, including nickel (Ni), arsenic (As), cadmium (Cd) and lead (Pb) to ensure compliance with legislative limits. However, the UK Expert Panel on Air Quality Standards (EPAQS) has highlighted a need to limit concentrations of beryllium (Be) in air, which is not currently monitored, because of its toxicity. The aim of this work was to analyse airborne particulate matter (PM) sampled onto filter papers from the UK Heavy Metals Monitoring Network for quantitative, trace level beryllium determination and compare the results to the guideline concentration specified by EPAQS. Samples were prepared by microwave acid digestion in a matrix of 2% sulphuric acid and 14% nitric acid, verified by the use of Certified Reference Materials (CRMs). The digested samples were then analysed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The filters from the UK Heavy Metals Monitoring Network were tested using this procedure and the average beryllium concentration across the network for the duration of the study period was 7.87 pg m-3. The highest site average concentration was 32.0 pg m-3 at Scunthorpe Low Santon, which is significantly lower than levels that are thought to cause harm. However the highest levels were observed at sites monitoring industrial point sources, indicating that beryllium is being used and emitted, albeit at very low levels, from these point sources. Comparison with other metals concentrations and data from the UK National Atmospheric Emissions Inventory suggests that current emissions of beryllium may be significantly overestimated.
Assessment of SRS ambient air monitoring network
DOE Office of Scientific and Technical Information (OSTI.GOV)
Abbott, K.; Jannik, T.
Three methodologies have been used to assess the effectiveness of the existing ambient air monitoring system in place at the Savannah River Site in Aiken, SC. Effectiveness was measured using two metrics that have been utilized in previous quantification of air-monitoring network performance; frequency of detection (a measurement of how frequently a minimum number of samplers within the network detect an event), and network intensity (a measurement of how consistent each sampler within the network is at detecting events). In addition to determining the effectiveness of the current system, the objective of performing this assessment was to determine what, ifmore » any, changes could make the system more effective. Methodologies included 1) the Waite method of determining sampler distribution, 2) the CAP88- PC annual dose model, and 3) a puff/plume transport model used to predict air concentrations at sampler locations. Data collected from air samplers at SRS in 2015 compared with predicted data resulting from the methodologies determined that the frequency of detection for the current system is 79.2% with sampler efficiencies ranging from 5% to 45%, and a mean network intensity of 21.5%. One of the air monitoring stations had an efficiency of less than 10%, and detected releases during just one sampling period of the entire year, adding little to the overall network intensity. By moving or removing this sampler, the mean network intensity increased to about 23%. Further work in increasing the network intensity and simulating accident scenarios to further test the ambient air system at SRS is planned« less
Atmospheric Hydrogen (H2) Concentrations from the CSIRO GASLAB Flask Sampling Network (1992 - 2001)
Steele, L. P. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Atmospheric Research, Aspendale, Victoria, Australia; Krummel, P. B. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Atmospheric Research, Aspendale, Victoria, Australia; Langenfelds, R. L. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Atmospheric Research, Aspendale, Victoria, Australia
2003-01-01
Air samples from nine sites were collected from the CSIRO GASLAB Flask Sampling Network for the purpose of monitoring the atmospheric hydrogen (H2) concentrations. The listed data were obtained from flask air samples returned to the CSIRO GASLAB for analysis. Typical sample storage times ranged from days to weeks for some sites (e.g., Cape Grim) to as much as one year for Macquarie Island and the Antarctic sites. Experiments carried out to test for any change in sample H22 mixing ratio during storage have shown no consistent and systematic drift in these flask types over test periods of several months to years (Cooper et al., 1999). An annual cycle of H2 is evident, reflecting the seasonal nature of some of the major sources and sinks (Novelli et al., 1999).
The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric CDDs, CDFs and coplanar PCBs at rural and nonimpacted locations throughout the United States. Currently operating at 32 sampling st...
Microfluidics-based integrated airborne pathogen detection systems
NASA Astrophysics Data System (ADS)
Northrup, M. Allen; Alleman-Sposito, Jennifer; Austin, Todd; Devitt, Amy; Fong, Donna; Lin, Phil; Nakao, Brian; Pourahmadi, Farzad; Vinas, Mary; Yuan, Bob
2006-09-01
Microfluidic Systems is focused on building microfluidic platforms that interface front-end mesofluidics to handle real world sample volumes for optimal sensitivity coupled to microfluidic circuitry to process small liquid volumes for complex reagent metering, mixing, and biochemical analysis, particularly for pathogens. MFSI is the prime contractor on two programs for the US Department of Homeland Security: BAND (Bioagent Autonomous Networked Detector) and IBADS (Instantaneous Bio-Aerosol Detection System). The goal of BAND is to develop an autonomous system for monitoring the air for known biological agents. This consists of air collection, sample lysis, sample purification, detection of DNA, RNA, and toxins, and a networked interface to report the results. For IBADS, MFSI is developing the confirmatory device which must verify the presence of a pathogen with 5 minutes of an air collector/trigger sounding an alarm. Instrument designs and biological assay results from both BAND and IBADS will be presented.
NASA Astrophysics Data System (ADS)
Mielke-Maday, I.
2015-12-01
The National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Division (GMD) maintains a global reference network for over 50 trace gas species and analyzes discrete air samples collected by this network throughout the world at the Earth System Research Laboratory in Boulder, Colorado. In particular, flask samples are analyzed for a number of hydrocarbons with policy and health relevance such as ozone precursors, greenhouse gases, and hazardous air pollutants. Because this global network's sites are remote and therefore minimally influenced by local anthropogenic emissions, these data yield information about background ambient mole fractions and can provide a context for observations collected in intensive field campaigns, such as the Front Range Air Pollution and Photochemistry Experiment (FRAPPE), the Southeast Nexus (SENEX) study, and the DISCOVER-AQ deployments. Information about background mole fractions during field campaigns is critical for calculating hydrocarbon enhancements in the region of study and for assessing the extent to which a particular region's local emissions sources contribute to these enhancements. Understanding the geographic variability of the background and its contribution to regional ambient mole fractions is also crucial for the development of realistic regulations. We present background hydrocarbon mole fractions and their ratios in North America using data from air samples collected in the planetary boundary layer at tall towers and aboard aircraft from 2008 to 2014. We discuss the spatial and seasonal variability in these data. We present trends over the time period of measurements and propose possible explanations for these trends.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harlos, D.P.; Edgerton, E.S.
1994-12-31
The US EPA has, under the auspices of the CASTNet program (Clean Air Status and Trends Network), initiated the CASTNet Air Toxics Monitoring Program (CATMP). Volatile Organic Compounds (VOC) and carbonyls and metals are sampled for 24-hour periods on a 12-day schedule using TO-14 samplers (SUMMA canisters) and dinitrophenylhydrazine-coated (dmph) sorbent cartridges and high volume particle samplers. Sampling was begun at most sites in July of 1993. The sites are operated by state and local air pollution control programs and all analysis is performed by Environmental Science and Engineering (ESE) in Gainesville, Florida. The network currently supports 15 VOC sites,more » of which 7 also sample carbonyls. Three sites sample metals only in Pinellas County, Florida. The limits of detection of 0.05 ppb for VOCs allow routine tracking of a wide range of pollutants including several greenhouse gases, transportation pollutants and photochemically-derived compounds. The sites range from major urban areas (Chicago, St. Louis) to a rural village (Waterbury, Vermont). Results of the first three quarters of VOC and carbonyl data collection are summarized in this presentation.« less
ERIC Educational Resources Information Center
Craig, R. Stephen
A content analysis comparing gender portrayals in 2,209 network television commercials was conducted. Many earlier studies treated television advertising's portrayal of men as unproblematic and excluded ads aimed specifically at men from the study sample. To address this shortcoming, the sample was chosen from three different day parts: (1)…
PM2.5 Monitors in New England | Air Quality Planning Unit ...
2017-04-10
The New England states are currently operating a network of 58 ambient PM2.5 air quality monitors that meet EPA's Federal Reference Method (FRM) for PM2.5, which is necessary in order for the resultant data to be used for attainment/non-attainment purposes. These monitors collect particles in the ambient air smaller than 2.5 microns in size on a filter, which is weighed prior and post sampling to produce a 24-hour sample concentration.
MONITORING ENVIRONMENTAL RADIATION IN THE UNITED STATES(RADNET)
Operate a national network of sampling stations that regularly submit environmental samples of air, precipitation and drinking water; analyze all samples for radiation at the laboratory; and report data to the public and the radiation protection community. During national radiat...
Schuster, Jasmin K; Harner, Tom; Fillmann, Gilberto; Ahrens, Lutz; Altamirano, Jorgelina C; Aristizábal, Beatriz; Bastos, Wanderley; Castillo, Luisa Eugenia; Cortés, Johana; Fentanes, Oscar; Gusev, Alexey; Hernandez, Maricruz; Ibarra, Martín Villa; Lana, Nerina B; Lee, Sum Chi; Martínez, Ana Patricia; Miglioranza, Karina S B; Puerta, Andrea Padilla; Segovia, Federico; Siu, May; Tominaga, Maria Yumiko
2015-03-17
A passive air sampling network has been established to investigate polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) at Global Atmospheric Passive Sampling (GAPS) sites and six additional sites in the Group of Latin American and Caribbean Countries (GRULAC) region. The air sampling network covers background, agricultural, rural, and urban sites. Samples have been collected over four consecutive periods of 6 months, which started in January 2011 [period 1 (January to June 2011), period 2 (July to December 2011), period 3 (January to June 2012), and period 4 (July 2012 to January 2013)]. Results show that (i) the GAPS passive samplers (PUF disk type) and analytical methodology are adequate for measuring PCDD/F burdens in air and (ii) PCDD/F concentrations in air across the GRULAC region are widely variable by almost 2 orders of magnitude. The highest concentrations in air of Σ4-8PCDD/Fs were found at the urban site São Luis (Brazil, UR) (i.e., 2560 fg/m3) followed by the sites in São Paulo (Brazil, UR), Mendoza (Argentina, RU), and Sonora (Mexico, AG) with values of 1690, 1660, and 1610 fg/m3, respectively. Very low concentrations of PCDD/Fs in air were observed at the background site Tapanti (Costa Rica, BA), 10.8 fg/m3. This variability is attributed to differences in site characteristics and potential local/regional sources as well as meteorological influences. The measurements of PCDD/Fs in air agree well with model-predicted concentrations performed using the Global EMEP Multimedia Modeling System (GLEMOS) and emission scenario constructed on the basis of the UNEP Stockholm Convention inventory of dioxin and furan emissions.
Journal Article: EPA's National Dioxin Air Monitoring Network ...
The U.S. Environmental Protection Agency (U.S. EPA) established the National Dioxin Air Monitoring Network (NDAMN) in June of 1998, and operated it until November of 2004. The objective of NDAMN was to determine background air concentrations of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (dl-PCBs). NDAMN started with 10 sampling sites, adding more over time until the final count of 34 sites was reached by the beginning of 2003. Samples were taken quarterly, and the final sample count was 685. All samples were measured for 17 PCDD/PCDF congeners, 8 PCDD/PCDF homologue groups, and 7 dl-PCBs (note: 5 additional dl-PCBs were added for samples starting in the summer of 2002; 317 samples had measurements of 12 dl-PCBs). The overall average total toxic equivalent (TEQ) concentration in the United States was 11.2 fg TEQ m−3 with dl-PCBs contributing 0.8 fg TEQ m−3 (7%) to this total. The archetype dioxin and furan background air congener profile was seen in the survey averages and in most individual samples. This archetype profile is characterized by low and similar concentrations for tetra – through hexa PCDD/PCDF congeners, with elevations in four congeners – a hepta dioxin and furan congener, and both octa congeners. Sites were generally categorized as urban (4 sites), rural (23 sites), or remote (7 sites). The average TEQ concentrations over all sites and samples within these cat
A Study of Voluntary Turnover of Air Force Officers in Critically-Manned Career Fields
2003-03-01
sampling and the USAF Academy Association of Graduates (AOG). For network sampling, fellow students in the Air Force Institute of Technology (AFIT) were...the voluntary leavers, five independent judges who are graduate students in AFIT will review five random questionnaires and independently...significantly higher levels of emotional exhaustion that did Administrative Assistants and had significantly higher levels of depersonalization than all
Multiple site receptor modeling with a minimal spanning tree combined with a Kohonen neural network
NASA Astrophysics Data System (ADS)
Hopke, Philip K.
1999-12-01
A combination of two pattern recognition methods has been developed that allows the generation of geographical emission maps form multivariate environmental data. In such a projection into a visually interpretable subspace by a Kohonen Self-Organizing Feature Map, the topology of the higher dimensional variables space can be preserved, but parts of the information about the correct neighborhood among the sample vectors will be lost. This can partly be compensated for by an additional projection of Prim's Minimal Spanning Tree into the trained neural network. This new environmental receptor modeling technique has been adapted for multiple sampling sites. The behavior of the method has been studied using simulated data. Subsequently, the method has been applied to mapping data sets from the Southern California Air Quality Study. The projection of a 17 chemical variables measured at up to 8 sampling sites provided a 2D, visually interpretable, geometrically reasonable arrangement of air pollution source sin the South Coast Air Basin.
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.
The GCOS Reference Upper-Air Network (GRUAN)
NASA Astrophysics Data System (ADS)
Vömel, H.; Berger, F. H.; Immler, F. J.; Seidel, D.; Thorne, P.
2009-04-01
While the global upper-air observing network has provided useful observations for operational weather forecasting for decades, its measurements lack the accuracy and long-term continuity needed for understanding climate change. Consequently, the scientific community faces uncertainty on such key issues as the trends of temperature in the upper troposphere and stratosphere or the variability and trends of stratospheric water vapour. To address these shortcomings, and to ensure that future climate records will be more useful than the records to date, the Global Climate Observing System (GCOS) program initiated the GCOS Reference Upper Air Network (GRUAN). GRUAN will be a network of about 30-40 observatories with a representative sampling of geographic regions and surface types. These stations will provide upper-air reference observations of the essential climate variables, i.e. temperature, geopotential, humidity, wind, radiation and cloud properties using specialized radiosondes and complementary remote sensing profiling instrumentation. Long-term stability, quality assurance / quality control, and a detailed assessment of measurement uncertainties will be the key aspects of GRUAN observations. The network will not be globally complete but will serve to constrain and adjust data from more spatially comprehensive global observing systems including satellites and the current radiosonde networks. This paper outlines the scientific rationale for GRUAN, its role in the Global Earth Observation System of Systems, network requirements and likely instrumentation, management structure, current status and future plans.
Woodward, N C; Gunning, A P; Mackie, A R; Wilde, P J; Morris, V J
2009-06-16
Displacement of sodium caseinate from the air-water interface by nonionic surfactants Tween 20 and Tween 60 was observed by atomic force microscopy (AFM). The interfacial structure was sampled by Langmuir-Blodgett deposition onto freshly cleaved mica substrates. Protein displacement occurred through an orogenic mechanism: it involved the nucleation and growth of surfactant domains within the protein network, followed by failure of the protein network. The surface pressure at which failure of the protein network occurred was essentially independent of the type of surfactant. The major component of sodium caseinate is beta-casein, and previous studies at the air-water interface have shown that beta-casein networks are weak, failing at surface pressures below that observed for sodium caseinate. The other components of sodium caseinate are alpha(s)- and kappa-caseins. Studies of the displacement of alpha(s)-caseins from air-water interfaces show that these proteins also form weak networks that fail at surface pressures below that observed for sodium caseinate. However, kappa-casein was found to form strong networks that resisted displacement and failed at surface pressures comparable to those observed for sodium caseinate. The AFM images of the displacement suggest that, despite kappa-casein being a minor component, it dominates the failure of sodium caseinate networks: alpha(s)-casein and beta-casein are preferentially desorbed at lower surface pressures, allowing the residual kappa-casein to control the breakdown of the sodium caseinate network at higher surface pressures.
Pollmann, Jan; Helmig, Detlev; Hueber, Jacques; Plass-Dülmer, Christian; Tans, Pieter
2008-04-25
An analytical technique was developed to analyze light non-methane hydrocarbons (NMHC), including ethane, propane, iso-butane, n-butane, iso-pentane, n-pentane, n-hexane, isoprene, benzene and toluene from whole air samples collected in 2.5l-glass flasks used by the National Oceanic and Atmospheric Administration, Earth System Research Laboratory, Global Monitoring Division (NOAA ESRL GMD, Boulder, CO, USA) Cooperative Air Sampling Network. This method relies on utilizing the remaining air in these flasks (which is at below-ambient pressure at this stage) after the completion of all routine greenhouse gas measurements from these samples. NMHC in sample aliquots extracted from the flasks were preconcentrated with a custom-made, cryogen-free inlet system and analyzed by gas chromatography (GC) with flame ionization detection (FID). C2-C7 NMHC, depending on their ambient air mixing ratios, could be measured with accuracy and repeatability errors of generally < or =10-20%. Larger deviations were found for ethene and propene. Hexane was systematically overestimated due to a chromatographic co-elution problem. Saturated NMHC showed less than 5% changes in their mixing ratios in glass flask samples that were stored for up to 1 year. In the same experiment ethene and propene increased at approximately 30% yr(-1). A series of blank experiments showed negligible contamination from the sampling process and from storage (<10 pptv yr(-1)) of samples in these glass flasks. Results from flask NMHC analyses were compared to in-situ NMHC measurements at the Global Atmospheric Watch station in Hohenpeissenberg, Germany. This 9-months side-by-side comparison showed good agreement between both methods. More than 94% of all data comparisons for C2-C5 alkanes, isoprene, benzene and toluene fell within the combined accuracy and precision objectives of the World Meteorological Organization Global Atmosphere Watch (WMO-GAW) for NMHC measurements.
On the Effect of Preferential Sampling in Spatial Prediction
The choice of the sampling locations in a spatial network is often guided by practical demands. In particular, typically, locations are preferentially chosen to capture high values of a response, for example, air pollution levels in environmental monitoring. Then, model estimatio...
US EPA's National Dioxin Air Monitoring Network: Analytical ...
The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric chlorinated dibenzo-p-dioxins (CDDs), furans (CDFs), and coplanar polychlorinated biphenyls (PCBs) at rural and non-impacted locations throughout the United States. Currently operating at 32 sampling stations, NDAMN has three primary purposes: (1) to determine the atmospheric levels and occurrences of dioxin-like compounds in rural and agricultural areas where livestock, poultry, and animal feed crops are grown; (2) to provide measurements of atmospheric levels in different geographic regions of the U.S.; and (3) to provide information regarding the long-range transport of dioxin-like compounds in air over the U.S. Designed in 1997, NDAMN has been implemented in phases, with the first phase consisting of 9 monitoring stations and is achieving congener-specific detection lmits of 0.1 fg/m3 for 2,3,7,8-TCDD and 10 fg/m3 for OCDD. With respect to coplanar PCBs, the detection limits are generally higher due to the presence of background levels in the air during the preparation and processing of the samples. Achieving these extremely low levels of detection present a host of analytical issues. Among these issues are the methods used to establish ultra-trace detection limits, measures to ensure against and monitor for breakthrough of native analytes when sampling large volumes of air, and procedures for handling and e
Ambient air quality has traditionally been monitored using a network of fixed point sampling sites that are strategically placed to represent regional (e.g., county or town) rather than local (e.g., neighborhood) air quality trends. This type of monitoring data has been used to m...
Spatial Analysis and Land Use Regression of VOCs and NO2 in Dallas, Texas during Two Seasons
Passive air sampling for nitrogen dioxide (NO2) and select volatile organic compounds (VOCs) was conducted at 24 fire stations and a compliance monitoring site in Dallas, Texas, USA during summer 2006 and winter 2008. This ambient air monitoring network was established...
RadNet Map Interface for Near-Real-Time Radiation Monitoring Data
RadNet is a national network of monitoring stations that regularly collect air, precipitation, drinking water, and milk samples for analysis of radioactivity. The RadNet network, which has stations in each state, has been used to track environmental releases of radioactivity from nuclear weapons tests and nuclear accidents.
Air quality measurements-From rubber bands to tapping the rainbow.
Hidy, George M; Mueller, Peter K; Altshuler, Samuel L; Chow, Judith C; Watson, John G
2017-06-01
It is axiomatic that good measurements are integral to good public policy for environmental protection. The generalized term for "measurements" includes sampling and quantitation, data integrity, documentation, network design, sponsorship, operations, archiving, and accessing for applications. Each of these components has evolved and advanced over the last 200 years as knowledge of atmospheric chemistry and physics has matured. Air quality was first detected by what people could see and smell in contaminated air. Gaseous pollutants were found to react with certain materials or chemicals, changing the color of dissolved reagents such that their light absorption at selected wavelengths could be related to both the pollutant chemistry and its concentration. Airborne particles have challenged the development of a variety of sensory devices and laboratory assays for characterization of their enormous range of physical and chemical properties. Advanced electronics made possible the sampling, concentration, and detection of gases and particles, both in situ and in laboratory analysis of collected samples. Accurate and precise measurements by these methods have made possible advanced air quality management practices that led to decreasing concentrations over time. New technologies are leading to smaller and cheaper measurement systems that can further expand and enhance current air pollution monitoring networks. Ambient air quality measurement systems have a large influence on air quality management by determining compliance, tracking trends, elucidating pollutant transport and transformation, and relating concentrations to adverse effects. These systems consist of more than just instrumentation, and involve extensive support efforts for siting, maintenance, calibration, auditing, data validation, data management and access, and data interpretation. These requirements have largely been attained for criteria pollutants regulated by National Ambient Air Quality Standards, but they are rarely attained for nonroutine measurements and research studies.
Wetherbee, Gregory A.; Shaw, Michael J.; Latysh, Natalie E.; Lehmann, Christopher M.B.; Rothert, Jane E.
2010-01-01
Precipitation chemistry and depth measurements obtained by the Canadian Air and Precipitation Monitoring Network (CAPMoN) and the US National Atmospheric Deposition Program/National Trends Network (NADP/NTN) were compared for the 10-year period 1995–2004. Colocated sets of CAPMoN and NADP instrumentation, consisting of precipitation collectors and rain gages, were operated simultaneously per standard protocols for each network at Sutton, Ontario and Frelighsburg, Ontario, Canada and at State College, PA, USA. CAPMoN samples were collected daily, and NADP samples were collected weekly, and samples were analyzed exclusively by each network’s laboratory for pH, H + , Ca2+ , Mg2+ , Na + , K + , NH+4 , Cl − , NO−3 , and SO2−4 . Weekly and annual precipitation-weighted mean concentrations for each network were compared. This study is a follow-up to an earlier internetwork comparison for the period 1986–1993, published by Alain Sirois, Robert Vet, and Dennis Lamb in 2000. Median weekly internetwork differences for 1995–2004 data were the same to slightly lower than for data for the previous study period (1986–1993) for all analytes except NO−3 , SO2−4 , and sample depth. A 1994 NADP sampling protocol change and a 1998 change in the types of filters used to process NADP samples reversed the previously identified negative bias in NADP data for hydrogen-ion and sodium concentrations. Statistically significant biases (α = 0.10) for sodium and hydrogen-ion concentrations observed in the 1986–1993 data were not significant for 1995–2004. Weekly CAPMoN measurements generally are higher than weekly NADP measurements due to differences in sample filtration and field instrumentation, not sample evaporation, contamination, or analytical laboratory differences.
Delta 13C in CO2 at Alert, NWT, Canada (June 1991 - December 2001)
Allison, C. E. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, Victoria, Australia; Francey, R. J. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, Victoria, Australia; Krummel, P. B. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, Victoria, Australia
2003-04-01
Measurements have been made on air collected in flasks at Alert, Canada, through the CSIRO GASLAB worldwide network. Flasks are filled with air at Alert and returned to the CSIRO GASLAB for analysis; typical sample storage times for flasks collected at Alert range from a few weeks to a few months. No significant effect on the stable carbon isotopic composition, δ13C, has been detected as a consequence of the sample storage time.
Chen, Wen; Hambleton, Sarah; Seifert, Keith A; Carisse, Odile; Diarra, Moussa S; Peters, Rick D; Lowe, Christine; Chapados, Julie T; Lévesque, C André
2018-05-01
Spore samplers are widely used in pathogen surveillance but not so much for monitoring the composition of aeromycobiota. In Canada, a nationwide spore-sampling network (AeroNet) was established as a pilot project to assess fungal community composition in air and rain samples collected using three different spore samplers in the summers of 2010 and 2011. Metabarcodes of the internal transcribed spacer (ITS) were exhaustively characterized for three of the network sites, in British Columbia (BC), Québec (QC), and Prince Edward Island (PEI), to compare performance of the samplers. Sampler type accounted for ca. 20% of the total explainable variance in aeromycobiota compositional heterogeneity, with air samplers recovering more Ascomycota and rain samplers recovering more Basidiomycota. Spore samplers showed different abilities to collect 27 fungal genera that are plant pathogens. For instance, Cladosporium spp., Drechslera spp., and Entyloma spp. were collected mainly by air samplers, while Fusarium spp., Microdochium spp., and Ustilago spp. were recovered more frequently with rain samplers. The diversity and abundance of some fungi were significantly affected by sampling location and time (e.g., Alternaria and Bipolaris ) and weather conditions (e.g., Mycocentrospora and Leptosphaeria ), and depended on using ITS1 or ITS2 as the barcoding region (e.g., Epicoccum and Botrytis ). The observation that Canada's aeromycobiota diversity correlates with cooler, wetter conditions and northward wind requires support from more long-term data sets. Our vision of the AeroNet network, combined with high-throughput sequencing (HTS) and well-designed sampling strategies, may contribute significantly to a national biovigilance network for protecting plants of agricultural and economic importance in Canada. IMPORTANCE The current study compared the performance of spore samplers for collecting broad-spectrum air- and rain-borne fungal pathogens using a metabarcoding approach. The results provided a thorough characterization of the aeromycobiota in the coastal regions of Canada in relation to the influence of climatic factors. This study lays the methodological basis to eventually develop knowledge-based guidance on pest surveillance by assisting in the selection of appropriate spore samplers. © Crown copyright 2018.
Ground-Based Aerosol Measurements | Science Inventory ...
Atmospheric particulate matter (PM) is a complex chemical mixture of liquid and solid particles suspended in air (Seinfeld and Pandis 2016). Measurements of this complex mixture form the basis of our knowledge regarding particle formation, source-receptor relationships, data to test and verify complex air quality models, and how PM impacts human health, visibility, global warming, and ecological systems (EPA 2009). Historically, PM samples have been collected on filters or other substrates with subsequent chemical analysis in the laboratory and this is still the major approach for routine networks (Chow 2005; Solomon et al. 2014) as well as in research studies. In this approach, air, at a specified flow rate and time period, is typically drawn through an inlet, usually a size selective inlet, and then drawn through filters, 1 INTRODUCTION Atmospheric particulate matter (PM) is a complex chemical mixture of liquid and solid particles suspended in air (Seinfeld and Pandis 2016). Measurements of this complex mixture form the basis of our knowledge regarding particle formation, source-receptor relationships, data to test and verify complex air quality models, and how PM impacts human health, visibility, global warming, and ecological systems (EPA 2009). Historically, PM samples have been collected on filters or other substrates with subsequent chemical analysis in the laboratory and this is still the major approach for routine networks (Chow 2005; Solomo
NASA Technical Reports Server (NTRS)
Haines, Jennifer C.; Chen, Lung-Wen A.; Taubman, Brett F.; Doddridge, Bruce G.; Dickerson, Russell R.
2007-01-01
Reliable determination of the effects of air quality on public health and the environment requires accurate measurement of PM(sub 2.5) mass and the individual chemical components of fine aerosols. This study seeks to evaluate PM(sub 2.5) measurements that are part of a newly established national network by comparing them with a more conventional sampling system. Experiments were carried out during 2002 at a suburban site in Maryland, United States, where two samplers from the U.S. Environmental Protection Agency (USEPA) Speciation Trends Network: Met One Speciation Air Sampling System STNS and Thermo Scientific Reference Ambient Air Sampler STNR, two Desert Research Institute Sequential Filter Samplers DRIF, and a continuous TEOM monitor (Thermo Scientific Tapered Element Oscillating Microbalance) were sampling air in parallel. These monitors differ not only in sampling configuration but also in protocol-specific sample analysis procedures. Measurements of PM(sub 2.5) mass and major contributing species were well correlated among the different methods with r-values > 0.8. Despite the good correlations, daily concentrations of PM(sub 2.5) mass and major contributing species were significantly different at the 95% confidence level from 5 to 100% of the time. Larger values of PM(sub 2.5) mass and individual species were generally reported from STNR and STNS. The January STNR average PM(sub 2.5) mass (8.8 (micro)g/per cubic meter) was 1.5 (micro)g/per cubic meter larger than the DRIF average mass. The July STNS average PM(sub 2.5) mass (27.8 (micro)g/per cubic meter) was 3.8 (micro)g/per cubic meter larger than the DRIF average mass. These differences can only be partially accounted for by known random errors. Variations in flow control, face velocity, and sampling artifacts likely influence the measurement of PM(sub 2.5) speciation and mass closure. Simple statistical tests indicate that the current uncertainty estimates used in the STN network may underestimate the actual uncertainty.
ERIC Educational Resources Information Center
Lee, Ronald T., Ed.
This resource guide is intended to aid practitioners in the design of new curriculum units or the enrichment of existing units by suggesting activities and resources in the topic areas of earth, air, fire, and water. Special projects and trips relating to these topic areas are proposed. A sample arts networking system used to integrate various…
NASA Astrophysics Data System (ADS)
Clark, O.; Rice, A. L.
2017-12-01
Carbon dioxide (CO2) is the most abundant, anthropogenically forced greenhouse gas (GHG) in the global atmosphere. Emissions of CO2 account for approximately 75% of the world's total GHG emissions. Atmospheric concentrations of CO2 are higher now than they've been at any other time in the past 800,000 years. Currently, the global mean concentration exceeds 400 ppm. Today, global networks regularly monitor CO2 concentrations and isotopic composition (δ13C and δ18O). However, past data is sparse. Over 200 ambient air samples from Cape Meares, Oregon (45.5°N, 124.0°W), a coastal site in Western United States, were obtained by researchers at Oregon Institute of Science and Technology (OGI, now Oregon Health & Science University), between the years of 1977 and 1998 as part of a global monitoring program of six different sites in the polar, middle, and tropical latitudes of the Northern and Southern Hemispheres. Air liquefaction was used to compress approximately 1000L of air (STP) to 30bar, into 33L electropolished (SUMMA) stainless steel canisters. Select archived air samples from the original network are maintained at Portland State University (PSU) Department of Physics. These archived samples are a valuable look at changing atmospheric concentrations of CO2 and δ13C, which can contribute to a better understanding of changes in sources during this time. CO2 concentrations and δ13C of CO2 were measured at PSU, with a Picarro Cavity Ringdown Spectrometer, model G1101-i analytical system. This study presents the analytical methods used, calibration techniques, precision, and reproducibility. Measurements of select samples from the archive show rising CO2 concentrations and falling δ13C over the 1977 to 1998 period, compatible with previous observations and rising anthropogenic sources of CO2. The resulting data set was statistically analyzed in MATLAB. Results of preliminary seasonal and secular trends from the archive samples are presented.
Air Quality and Road Emission Results for Fort Stewart, Georgia
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kirkham, Randy R.; Driver, Crystal J.; Chamness, Mickie A.
2004-02-02
The Directorate of Public Works Environmental & Natural Resources Division (Fort Stewart /Hunter Army Airfield) contracted with the Pacific Northwest National Laboratory (PNNL) to monitor particulate matter (PM) concentrations on Fort Stewart, Georgia. The purpose of this investigation was to establish a PM sampling network using monitoring equipment typically used in U.S. Environmental Protection Agency (EPA) ''saturation sampling'', to determine air quality on the installation. In this initial study, the emphasis was on training-generated PM, not receptor PM loading. The majority of PM samples were 24-hr filter-based samples with sampling frequency ranging from every other day, to once every sixmore » days synchronized with the EPA 6th day national sampling schedule. Eight measurement sites were established and used to determine spatial variability in PM concentrations and evaluate whether fluctuations in PM appear to result from training activities and forest management practices on the installation. Data collected to date indicate the average installation PM2.5 concentration is lower than that of nearby urban Savannah, Georgia. At three sites near the installation perimeter, analyses to segregate PM concentrations by direction of air flow across the installation boundary indicate that air (below 80 ft) leaving the installation contains less PM2.5 than that entering the installation. This is reinforced by the observation that air near the ground is cleaner on average than the air at the top of the canopy.« less
Recent Results From the NOAA/ESRL GMD Tall Tower Network
NASA Astrophysics Data System (ADS)
Andrews, A. E.; Tans, P. P.; Peters, W.; Hirsch, A.; Sweeney, C.; Petron, G.; Kofler, J.; Zhao, C.; Masarie, K.; Wofsy, S. C.; Matross, D. M.; Mahadevan, P.; Longo, M.; Gerbig, C.; Lin, J. C.
2006-12-01
We will present a summary of new results from NOAA Earth System Research Laboratory`s Tall Tower greenhouse gas monitoring network. The tower network is operated by the Global Monitoring Division, which also maintains the global Cooperative Air Sampling network and a network of aircraft profiling sites over North America. Tall tower CO2 mixing ratio measurements are sensitive to upwind fluxes over scales of hundreds of kilometers, and the primary objective of the tower network is to obtain regionally representative carbon flux estimates for the North American continent. Mixing ratios of CO2 and CO are measured semi-continuously at the towers, and the KWKT-TV tower site near Moody, TX has recently also been equipped with sensors to measure radon and O3. Daily flask samples are collected at the KWKT tower and analyzed for CO2, CO, CH4, SF6, N2O, H2, stable isotopes of CO2 and CH4, COS, and a variety of halocarbon and hydrocarbon species. Daily flask sampling will be implemented at all tower sites within the next few years. We have used the Stochastic Time Inverted Lagrangian Transport (STILT) model to investigate upwind influences on the tower observations. CO measurements provide an indicator of polluted air masses, and we will present a summary of the frequency and origin of pollution events observed at the towers. We will present an analysis of the primary factors contributing to observed CO2 variability along with average seasonal and diurnal cycles of CO2 at the tower sites. Tower measurements are being used to evaluate atmospheric transport models in the context of the Transcom Continuous experiment and are an important constraint for CO2 data assimilation systems that produce regional to global carbon flux estimates with up to weekly resolution.
Keeling, R. F. [Scripps Institution of Oceanography (SIO) University of California, La Jolla, California (USA); Piper, S. C. [Scripps Institution of Oceanography (SIO) University of California, La Jolla, California (USA); Bollenbacher, A. F. [Scripps Institution of Oceanography (SIO) University of California, La Jolla, California (USA); Walker , J. S. [Scripps Institution of Oceanography (SIO) University of California, La Jolla, California (USA)
2008-05-01
At Alert weekly air samples are collected in 5-L evacuated glass flasks exposed in triplicate. Flasks are returned to the SIO for CO2 determinations, which are made using an Applied Physics Corporation nondispersive infrared gas analyzer. In May 1983, the CO2-in-N2 calibration gases were replaced with CO2-in-air calibration gases, which are currently used (Keeling et al. 2002). Data are in terms of the Scripps "03A" calibration scale. On the basis of flask samples collected at Alert and analyzed by SIO, the annual average of the fitted monthly concentrations CO2 rose from 348.48 ppmv in 1986 to 384.84 ppmv in 2007. This represents an average annual growth rate of 1.73 ppmv per year at Alert.
Journal Article: the National Dioxin Air Monitoring Network ...
The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric CDDs, CDFs and coplanar PCBs at rural and nonimpacted locations throughout the United States. Currently operating at 32 sampling stations, NDAMN has three primary purposes: (1) to determine the atmospheric levels and occurrences of dioxin-like compounds in rural and agricultural areas where livestock, poultry and animal feed crops are grown; (2) to provide measurements of atmospheric levels of dioxin-like compounds in different geographic regions of the U.S.; and (3) to provide information regarding the long-range transport of dioxin-like compounds in air over the U.S. Designed in 1997, NDAMN has been implemented in phases, with the first phase consisting of 9 monitoring stations. Previously EPA has reported on the preliminary results of monitoring at 9 rural locations from June1998 through June 19991. The one-year measurement at the 9 stations indicated an annual mean TEQDF–WHO98 air concentration of 12 fg m-3. Since this reporting, NDAMN has been extended to include additional stations. The following is intended to be an update to this national monitoring effort. We are reporting the air monitoring results of 22 NDAMN stations operational over 9 sampling moments from June 1998 to December 1999. Fifteen stations are in rural areas, and 6 are located in National Parks. One station is located in suburban Wa
Effects of the soil pore network architecture on the soil's physical functionalities
NASA Astrophysics Data System (ADS)
Smet, Sarah; Beckers, Eléonore; Léonard, Angélique; Degré, Aurore
2017-04-01
The soil fluid movement's prediction is of major interest within an agricultural or environmental scope because many processes depend ultimately on the soil fluids dynamic. It is common knowledge that the soil microscopic pore network structure governs the inner-soil convective fluids flow. There isn't, however, a general methodthat consider the pore network structure as a variable in the prediction of thecore scale soil's physical functionalities. There are various possible representations of the microscopic pore network: sample scale averaged structural parameters, extrapolation of theoretic pore network, or use of all the information available by modeling within the observed pore network. Different representations implydifferent analyzing methodologies. To our knowledge, few studies have compared the micro-and macroscopic soil's characteristics for the same soil core sample. The objective of our study is to explore the relationship between macroscopic physical properties and microscopic pore network structure. The saturated hydraulic conductivity, the air permeability, the retention curve, and others classical physical parameters were measured for ten soil samples from an agricultural field. The pore network characteristics were quantified through the analyses of X-ray micro-computed tomographic images(micro-CT system Skyscan-1172) with a voxel size of 22 µm3. Some of the first results confirmed what others studies had reported. Then, the comparison between macroscopic properties and microscopic parameters suggested that the air movements depended mostly on the pore connectivity and tortuosity than on the total porosity volume. We have also found that the fractal dimension calculated from the X-ray images and the fractal dimension calculated from the retention curve were significantly different. Our communication will detailthose results and discuss the methodology: would the results be similar with a different voxel size? What are the calculated and measured parameters uncertainties? Sarah Smet, as a research fellow, acknowledges the support of the National Fund for Scientific Research (Brussels, Belgium).
Journal Article: the National Dioxin Air Monitoring Network ...
In June, 1998, the U.S. EPA established the National Dioxin Air Monitoring Network (NDAMN). The primary goal of NDAMN is determine the temporal and geographical variability of atmospheric CDDs, CDFs, and coplanar PCBs at rural and nonimpacted locations throughout the United States. Currently operating at 32 sampling stations, NDAMN has three primary purposes: (1) to determine the atmospheric levels and occurrences of dioxin-like compounds in rural and agricultural areas where livestock, poultry and animal feed crops are grown; (2) to provide measurements of atmospheric levels of dioxin-like compounds in different geographic regions of the U.S.; and (3) to provide information regarding the long-range transport of dioxin-like compounds in air over the U.S. At Dioxin 2000, we reported on the preliminary results of monitoring at 9 rural locations from June 1998 through June 1999. By the end of 1999, NDAMN had expanded to 21 sampling stations. Then, at Dioxin 2001, we reported the results of the first 18 months of operation of NDAMN at 15 rural and 6 National Park stations in the United States. The following is intended to be an update to this national monitoring effort. We are reporting the air monitoring results of 17 rural and 8 National Park NDAMN stations operational over 4 sampling moments during calendar year 2000. Two stations located in suburban Washington DC and San Francisco, CA are more urban in character and serve as an indicator of CDD/F and cop
Innovations in air sampling to detect plant pathogens
West, JS; Kimber, RBE
2015-01-01
Many innovations in the development and use of air sampling devices have occurred in plant pathology since the first description of the Hirst spore trap. These include improvements in capture efficiency at relatively high air-volume collection rates, methods to enhance the ease of sample processing with downstream diagnostic methods and even full automation of sampling, diagnosis and wireless reporting of results. Other innovations have been to mount air samplers on mobile platforms such as UAVs and ground vehicles to allow sampling at different altitudes and locations in a short space of time to identify potential sources and population structure. Geographical Information Systems and the application to a network of samplers can allow a greater prediction of airborne inoculum and dispersal dynamics. This field of technology is now developing quickly as novel diagnostic methods allow increasingly rapid and accurate quantifications of airborne species and genetic traits. Sampling and interpretation of results, particularly action-thresholds, is improved by understanding components of air dispersal and dilution processes and can add greater precision in the application of crop protection products as part of integrated pest and disease management decisions. The applications of air samplers are likely to increase, with much greater adoption by growers or industry support workers to aid in crop protection decisions. The same devices are likely to improve information available for detection of allergens causing hay fever and asthma or provide valuable metadata for regional plant disease dynamics. PMID:25745191
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.
Code of Federal Regulations, 2013 CFR
2013-07-01
... monitors utilize the same specific sampling and analysis method. Combined site data record is the data set... monitors are suitable monitors designated by a state or local agency in their annual network plan (and in... appendix. Seasonal sampling is the practice of collecting data at a reduced frequency during a season of...
Trivett, N. B.A. [Atmospheric Environment Service, Downsview, Ontario, Canada; Hudec, V. C. [Atmospheric Environment Service, Downsview, Ontario, Canada; Wong, C. S. [Marine Carbon Research Centre, Institute of Ocean Sciences, Sidney, British Columbia, Canada
1997-01-01
From the mid-1970s through the mid-1990s, air samples were collected for the purposes of monitoring atmospheric CO2 from four sites in the AES air sampling network. Air samples were collected approximately once per week, between 12:00 and 16:00 local time, in a pair of evacuated 2-L thick-wall borosilicate glass flasks. Samples were collected under preferred conditions of wind speed and direction (i.e., upwind of the main station and when winds are strong and steady). The flasks were evacuated to pressures of ~1 × 10-4 mbar or 0.01 Pa prior to being sent to the stations. The airwas not dried during sample collection. The flask data from Alert show an increase in the annual atmospheric CO2 concentration from 341.35 parts per million by volume (ppmv) in 1981 to 357.21 ppmv in 1991. For Cape St. James, Trivett and Higuchi (1989) reported that the mean annual rate of increase, obtained from the slope of a least-squares regression line through the annual averages, was 1.43 ppmv per year. In August 1992, the weather station at Cape St. James was automated; as a result, the flask sampling program was discontinued at this site. Estevan Point, on the West Coast of Vancouver Island, was chosen as a replacement station. Sampling at Estevan Point started in 1992; thus, the monthly and annual CO2record from Estevan Point is too short to show any long-term trends. The sampling site at Sable Island, off the coast of Nova Scotia, was established in 1975. The flask data from Sable Island show an increase in the annual atmospheric CO2 concentration from 334.49 parts per million by volume (ppmv) in 1977 (the first full year of data) to 356.02 ppmv in 1990. For Sable Island, Trivett and Higuchi (1989) reported that the mean annual rate of increase, obtained from the slope of a least-squares regression line through the annual averages, was 1.48 ppmv per year.
Brounshtein, A. M. [Main Geophysical Observatory, St. Petersburg, Russia; Shaskov, A. A. [Main Geophysical Observatory, St. Petersburg, Russia; Paramonova, N. N. [Main Geophysical Observatory, St. Petersburg, Russia; Privalov, V. I. [Main Geophysical Observatory, St. Petersburg, Russia; Starodubtsev, Y. A. [Main Geophysical Observatory, St. Petersburg, Russia
1997-01-01
Air samples were collected from five sites in the Main Geophysical Observatory air sampling network to monitor the atmospheric CO2 from 1983 - 1993. Airwas collected generally four times per month in pairs of 1.5-L stainless steel electropolished flasks with one greaseless stainless steel stopcock. Sampling was performed by opening the stopcock of the flasks, which have been evacuated at the central laboratory at the Main Geophysical Observatory (MGO). The air was not dried during sample collection. Attempts were made to obtain samples when the wind speed was >5 m/s and the wind direction corresponded to the predetermined "clean air" sector. The period of record at Bering Island is too short to identify any long-term trends in atmospheric CO2 concentrations; however, the yearly mean atmospheric CO2 concentration at Bering Island rose from approximately 346 parts per million by volume (ppmv) in 1986 to 362.6 ppmv in 1993. Measurements from this station are considered indicative of maritime air masses. The period of record at Kotelny Island is too short to identify any long-term trends in atmospheric CO2 concentrations; however, the yearly mean atmospheric CO2 concentration at Kotelny Island rose from 356.08 parts per million by volume (ppmv) in 1988 to 358.8 ppmv in 1993. Because Kotelny Island is the northernmost Russian sampling site, measurements from this site serve as a useful comparison to other northern sites (e.g., Alert, Northwest Territories). In late 1989, air sampling began at the Russian site of Kyzylcha, located in the Republic of Uzbekistan. Unfortunately, the desert site at Kyzylcha has been out of operation since mid-1991 due to financial difficulties in Russia. The annual mean value of 359.02 parts per million by volume (ppmv) for 1990, the lone full year of operation, is higher than measurements from other monitoring programs at this latitude [e.g., Niwot Ridge (354.7 ppmv in 1990) and Tae-ahn Peninsula]. Station "C," an open ocean site, in the North Atlantic, east of Greenland, was established in 1968 and was operated in cooperation with NOAA's National Weather Service through 1973. The Main Geophysical Observatory collected flask samples at the site from January 1983 through October 1990. The yearly mean atmospheric CO concentration at Station "C" rose from 348.15 parts per million by volume (ppmv) in 1985 to 354.33 ppmv in 1989. The period of record at Teriberka Station is too short to identify any long-term trends in atmospheric CO2 concentrations; however, the yearly mean atmospheric CO2 concentration at Teriberka Station rose from 354.8 parts per million by volume (ppmv) in 1989 to 358.7 ppmv in 1993.
Across North America tracer experiment (ANATEX): Sampling and analysis
NASA Astrophysics Data System (ADS)
Draxler, R. R.; Dietz, R.; Lagomarsino, R. J.; Start, G.
Between 5 January 1987 and 29 March 1987, there were 33 releases of different tracers from each of two sites: Glasgow, MT and St. Cloud, MN. The perfluorocarbon tracers were routinely released in a 3-h period every 2.5 days, alternating between daytime and night-time tracer releases. Ground-level air samples of 24-h duration were taken at 77 sites mostly located near rawinsonde stations east of 105°W and between 26°N and 55°N. Weekly air samples were taken at 12 remote sites between San Diego, CA and Pt. Barrow, AK and between Norway and the Canary Islands. Short-term 6-h samples were collected at ground level and 200 m AGL along an arc of five towers between Tulsa, OK and Green Bay, WI. Aircraft sampling within several hundred kilometers of both tracer release sites was used to establish the initial tracer path. Experimental design required improved sampler performance, new tracers with lower atmospheric backgrounds, and improvements in analytic precision. The advances to the perfluorocarbon tracer system are discussed in detail. Results from the tracer sampling showed that the average and peak concentrations measured over the daily ground-level sampling network were consistent with what would be calculated using mass conservative approaches. however, ground-level samples from individual tracer patterns showed considerable complexity due to vertical stability or the interaction of the tracer plumes with low pressure and frontal systems. These systems could pass right through the tracer plume without appreciable effect. Aircraft tracer measurements are used to confirm the initial tracer trajectory when the narrow plume may miss the coarser spaced ground-level sampling network. Tower tracer measurements showed a more complex temporal structure than evident from the longer duration ground-level sampling sites. Few above background plume measurements were evident in the more distant remote sampling network due to larger than expected uncertainties in the ambient background concentrations.
Trivett, N. B. A. [Environment Canada, Atmospheric Environment Service, Downsview, Ontario, Canada; Hudec, V. C. [Environment Canada, Atmospheric Environment Service, Downsview, Ontario, Canada; Wong, C. S. [Marine Carbon Research Centre, Institute of Ocean Sciences, Sidney, British Columbia, Canada
1993-01-01
Flask air samples collected at roughly weekly intervals at three Canadian sites [Alert, Northwest Territories (July 1975 through July 1992); Sable Island, Nova Scotia (March 1975 through July 1992); and Cape St. James, British Columbia (May 1979 through July 1992)] were analyzed for CO2 concentration with the measurements directly traceable to the WMO primary CO2 standards. Each record includes the date, atmospheric CO2 concentration, and flask classification code. They provide an accurate record of CO2 concentration levels in Canada during the past two decades. Because these data are directly traceable to WMO standards, this record may be compared with records from other Background Air Pollution Monitoring Network (BAPMoN) stations. The data are in three files (one for each of the monitoring stations) ranging in size from 9.4 to 20.1 kB.
Structural Properties of the Brazilian Air Transportation Network.
Couto, Guilherme S; da Silva, Ana Paula Couto; Ruiz, Linnyer B; Benevenuto, Fabrício
2015-09-01
The air transportation network in a country has a great impact on the local, national and global economy. In this paper, we analyze the air transportation network in Brazil with complex network features to better understand its characteristics. In our analysis, we built networks composed either by national or by international flights. We also consider the network when both types of flights are put together. Interesting conclusions emerge from our analysis. For instance, Viracopos Airport (Campinas City) is the most central and connected airport on the national flights network. Any operational problem in this airport separates the Brazilian national network into six distinct subnetworks. Moreover, the Brazilian air transportation network exhibits small world characteristics and national connections network follows a power law distribution. Therefore, our analysis sheds light on the current Brazilian air transportation infrastructure, bringing a novel understanding that may help face the recent fast growth in the usage of the Brazilian transport network.
Forecasting PM10 in Algiers: efficacy of multilayer perceptron networks.
Abderrahim, Hamza; Chellali, Mohammed Reda; Hamou, Ahmed
2016-01-01
Air quality forecasting system has acquired high importance in atmospheric pollution due to its negative impacts on the environment and human health. The artificial neural network is one of the most common soft computing methods that can be pragmatic for carving such complex problem. In this paper, we used a multilayer perceptron neural network to forecast the daily averaged concentration of the respirable suspended particulates with aerodynamic diameter of not more than 10 μm (PM10) in Algiers, Algeria. The data for training and testing the network are based on the data sampled from 2002 to 2006 collected by SAMASAFIA network center at El Hamma station. The meteorological data, air temperature, relative humidity, and wind speed, are used as inputs network parameters in the formation of model. The training patterns used correspond to 41 days data. The performance of the developed models was evaluated on the basis index of agreement and other statistical parameters. It was seen that the overall performance of model with 15 neurons is better than the ones with 5 and 10 neurons. The results of multilayer network with as few as one hidden layer and 15 neurons were quite reasonable than the ones with 5 and 10 neurons. Finally, an error around 9% has been reached.
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.
Steele, L. P. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, Victoria, Australia; Krummel, P. B. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, Victoria, Australia; Langenfelds, R. L. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, Victoria, Australia
2003-01-01
The listed data were obtained from flask air samples returned to the CSIRO GASLAB for analysis. Typical sample storage times ranged from days to weeks for some sites (e.g., Cape Grim) to as much as one year for Macquarie Island and the Antarctic sites. Experiments carried out to test for any change in sample CH4 mixing ratio during storage have shown no drift to within detection limits over test periods of several months to years (Cooper et al., 1999).
In 1993, the University of Michigan Air Quality Laboratory (UMAQL) designed a new wet-only precipitation collection system that was utilized in the Lake Michigan Loading Study. The collection system was designed to collect discrete mercury and trace element samples on an event b...
A source of PCB contamination in modified high-volume air samplers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Basu, I.; O'Dell, J.M.; Arnold, K.
2000-02-01
Modified Anderson High Volume (Hi-Vol) air samplers are widely used for the collection of semi-volatile organic compounds (such as PCBs) from air. The foam gasket near the main air flow path in these samplers can become contaminated with PCBs if the sampler or the gasket is stored at a location with high indoor air PCB levels. Once the gasket is contaminated, it releases PCBs back into the air stream during sampling, and as a result, incorrectly high air PCB concentrations are measured. This paper presents data demonstrating this contamination problem using measurements from two Integrated Atmospheric Deposition Network sites: onemore » at Sleeping Bear Dunes on Lake Michigan and the other at Point Petre on Lake Ontario. The authors recommend that these gaskets be replaced by Teflon tape and that the storage history of each sampler be carefully tracked.« less
The U.S. Environmental Protection Agency (EPA) established the Clean Air Status and Trends Network (CASTNET) and its predecessor, the National Dry Deposition Network (NDDN), as national air quality and meteorological monitoring networks. The purpose of CASTNET is to track the pr...
EPA's National Dioxin Air Monitoring Network (NDAMN): Design, implementation, and final results
NASA Astrophysics Data System (ADS)
Lorber, Matthew; Ferrario, Joseph; Byrne, Christian
2013-10-01
The U.S. Environmental Protection Agency (U.S. EPA) established the National Dioxin Air Monitoring Network (NDAMN) in June of 1998, and operated it until November of 2004. The objective of NDAMN was to determine background air concentrations of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (dl-PCBs). NDAMN started with 10 sampling sites, adding more over time until the final count of 34 sites was reached by the beginning of 2003. Samples were taken quarterly, and the final sample count was 685. All samples were measured for 17 PCDD/PCDF congeners, 8 PCDD/PCDF homologue groups, and 7 dl-PCBs (note: 5 additional dl-PCBs were added for samples starting in the summer of 2002; 317 samples had measurements of 12 dl-PCBs). The overall average total toxic equivalent (TEQ) concentration in the United States was 11.2 fg TEQ m-3 with dl-PCBs contributing 0.8 fg TEQ m-3 (7%) to this total. The archetype dioxin and furan background air congener profile was seen in the survey averages and in most individual samples. This archetype profile is characterized by low and similar concentrations for tetra - through hexa PCDD/PCDF congeners, with elevations in four congeners - a hepta dioxin and furan congener, and both octa congeners. Sites were generally categorized as urban (4 sites), rural (23 sites), or remote (7 sites). The average TEQ concentrations over all sites and samples within these categories were: urban = 15.9 fg TEQ m-3, rural = 13.9 fg TEQ m-3, and remote = 1.2 fg TEQ m-3. Rural sites showed elevations during the fall or winter months when compared to the spring or summer months, and the same might be said for urban sites, but the remote sites appear to show little variation over time. The four highest individual moment measurements were 847, 292, 241, and 132 fg TEQ m-3. For the 847 and 292 fg TEQ m-3 samples, the concentrations of all congeners were elevated over their site averages, but for the 241 and 132 fg TEQ m-3 measurements, only the PCDD congeners were elevated while PCDF and dl-PCB concentrations were similar to the site averages.
GENASIS national and international monitoring networks for persistent organic pollutants
NASA Astrophysics Data System (ADS)
Brabec, Karel; Dušek, Ladislav; Holoubek, Ivan; Hřebíček, Jiří; Kubásek, Miroslav; Urbánek, Jaroslav
2010-05-01
Persistent organic pollutants (POPs) remain in the centre of scientific attention due to their slow rates of degradation, their toxicity, and potential for both long-range transport and bioaccumulation in living organisms. This group of compounds covers large number of various chemicals from industrial products, such as polychlorinated biphenyls, etc. The GENASIS (Global Environmental Assessment and Information System) information system utilizes data from national and international monitoring networks to obtain as-complete-as-possible set of information and a representative picture of environmental contamination by persistent organic pollutants (POPs). There are data from two main datasets on POPs monitoring: 1.Integrated monitoring of POPs in Košetice Observatory (Czech Republic) which is a long term background site of the European Monitoring and Evaluation Programme (EMEP) for the Central Europe; the data reveals long term trends of POPs in all environmental matrices. The Observatory is the only one in Europe where POPs have been monitored not only in ambient air, but also in wet atmospheric deposition, surface waters, sediments, soil, mosses and needles (integrated monitoring). Consistent data since the year 1996 are available, earlier data (up to 1998) are burdened by high variability and high detection limits. 2.MONET network is ambient air monitoring activities in the Central and Eastern European region (CEEC), Central Asia, Africa and Pacific Islands driven by RECETOX as the Regional Centre of the Stockholm Convention for the region of Central and Eastern Europe under the common name of the MONET networks (MONitoring NETwork). For many of the participating countries these activities generated first data on the atmospheric levels of POPs. The MONET network uses new technologies of air passive sampling, which was developed, tested, and calibrated by RECETOX in cooperation with Environment Canada and Lancaster University, and was originally launched as a model monitoring network providing public administration, private subject, and general public information about air pollution by POPs that had not been previously regularly monitored and whose measurement is further required by global monitoring plan of the Stockholm Convention. The MONET network is international project with many participants. Monitoring in the MONET-CZ network started in 2004 with the pilot project and continues to the current days, MONET CEEC started in 2006 and continues nowadays, MONET Africa started in 2008. The database of the GENASIS systems currently covers MONET-CZ data until the year 2008. The MONET network currently covers 37 countries in the Europe, Asia and Africa with more than 350 sampling sites. The paper will discuss about following topics * Data Fusion in GENASIS: how can GENASIS maximize the value and accuracy of the information gathered from heterogeneous data sources? * Sensor types in GENASIS: which POPs can be measured; what are the physical limitations to achievable accuracy, reliability, and long-term stability of miniaturized sensors; which applications can (not) be realized within these limitations?
Jungers, R H; Lee, R E; von Lehmden, D J
1975-01-01
A National Fuels Surveillance Network has been established to collect gasoline and other fuels through the 10 regional offices of the Environmental Protection Agency. Physical, chemical, and trace element analytical determinations are made on the collected fuel samples to detect components which may present an air pollution hazard or poison exhaust catalytic control devices. A summary of trace elemental constituents in over 50 gasoline samples and 18 commercially marketed consumer purchased gasoline additives is presented. Quantities of Mn, Ni, Cr, Zn, Cu, Fe, Sb, B, Mg, Pb, and S were found in most regular and premium gasoline. Environmental implications of trace constituents in gasoline are discussed. PMID:1157783
Baumgardner, Ralph E; Isil, Selma S; Bowser, Jon J; Fitzgerald, Kelley M
1999-11-01
The Clean Air Status and Trends Network (CASTNet) was implemented by the U.S. Environmental Protection Agency (EPA) in 1991 in response to Title IX of the Clean Air Amendments of 1990, which mandated the deployment of a national ambient air monitoring network to track progress of the implementation of emission reduction programs in terms of deposition, air quality, and changes to affected ecosystems. CASTNet evolved from the National Dry Deposition Network (NDDN). CASTNet currently consists of 45 sites in the eastern United States and 28 sites in the West. Each site measures sulfur dioxide (SO 2 ), nitric acid (HNO 3 ), particle sulfate (SO 4 = ), particle nitrate (NO 3 - ), and ozone. Nineteen sites collect precipitation samples. NDDN/CASTNet uses a uniform set of site-selection criteria which provides the data user with consistent measures to compare each site. These criteria also ensure that, to the extent possible, CASTNet sites are located away from local emission sources. This paper presents an analysis of SO 2 and SO 4 = concentration data collected from 1987 through 1996 at rural NDDN/CASTNet sites. Annual and seasonal variability is examined. Gradients of SO 2 and SO 4 = are discussed. The variability of the atmospheric mix of SO 2 and SO 4 = is explored spatially and seasonally. Data from CASTNet are also compared to SO 2 and SO 4 = data from concurrent monitoring studies in rural areas.
NASA Astrophysics Data System (ADS)
Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.
2015-12-01
The Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) wireless sensor network has been developed to support Calibration and Validation activities (Cal/Val) for large scale soil moisture remote sensing missions (SMAP and AirMOSS). The technology developed here also readily supports small scale hydrological studies by providing sub-kilometer widespread soil moisture observations. An extensive collection of semi-sparse sensor clusters deployed throughout north-central California and southern Arizona provide near real time soil moisture measurements. Such a wireless network architecture, compared to conventional single points measurement profiles, allows for significant and expanded soil moisture sampling. The work presented here aims at discussing and highlighting novel and new technology developments which increase in situ soil moisture measurements' accuracy, reliability, and robustness with reduced data delivery latency. High efficiency and low maintenance custom hardware have been developed and in-field performance has been demonstrated for a period of three years. The SoilSCAPE technology incorporates (a) intelligent sensing to prevent erroneous measurement reporting, (b) on-board short term memory for data redundancy, (c) adaptive scheduling and sampling capabilities to enhance energy efficiency. A rapid streamlined data delivery architecture openly provides distribution of in situ measurements to SMAP and AirMOSS cal/val activities and other interested parties.
Guiné, Raquel P F; Barroca, Maria João; Gonçalves, Fernando J; Alves, Mariana; Oliveira, Solange; Mendes, Mateus
2015-02-01
Bananas (cv. Musa nana and Musa cavendishii) fresh and dried by hot air at 50 and 70°C and lyophilisation were analysed for phenolic contents and antioxidant activity. All samples were subject to six extractions (three with methanol followed by three with acetone/water solution). The experimental data served to train a neural network adequate to describe the experimental observations for both output variables studied: total phenols and antioxidant activity. The results show that both bananas are similar and air drying decreased total phenols and antioxidant activity for both temperatures, whereas lyophilisation decreased the phenolic content in a lesser extent. Neural network experiments showed that antioxidant activity and phenolic compounds can be predicted accurately from the input variables: banana variety, dryness state and type and order of extract. Drying state and extract order were found to have larger impact in the values of antioxidant activity and phenolic compounds. Copyright © 2014 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wiersma, G.B.; Kohler, A.; Boelcke, C.
1985-10-01
During 1984, a pilot project was initiated for monitoring pollution at Torres del Paine National Park in southern Chile and Olympic National Park in the United States. These are two of three initial sites that are to be established as part of an integrated global backgound monitoring network. Eventually, the plan is to establish a world-wide system of such sites. We collected and analyzed samples of the soil, water, air, and two species of plants (moss and lichen). We also collected and analyzed samples of the forest litter. We compared the samples of soil and vegetation against reference samples. Wemore » also compared samples of soil, vegetation, and of organic material from Torres del Paine against similar samples from Olympic and Sequoia-Kings Canyon National Parks in the United States. Although the data is preliminary, it is in agreement with out initial hypothesis that Torres del Paine and Olympic National Parks are not a polluted sites.« less
Risk management in air protection in the Republic of Croatia.
Peternel, Renata; Toth, Ivan; Hercog, Predrag
2014-03-01
In the Republic of Croatia, according to the Air Protection Act, air pollution assessment is obligatory on the whole State territory. For individual regions and populated areas in the State a network has been established for permanent air quality monitoring. The State network consists of stations for measuring background pollution, regional and cross-border remote transfer and measurements as part of international government liabilities, then stations for measuring air quality in areas of cultural and natural heritage, and stations for measuring air pollution in towns and industrial zones. The exceeding of alert and information threshold levels of air pollutants are related to emissions from industrial plants, and accidents. Each excess represents a threat to human health in case of short-time exposure. Monitoring of alert and information threshold levels is carried out at stations from the state and local networks for permanent air quality monitoring according to the Air Quality Measurement Program in the State network for permanent monitoring of air quality and air quality measurement programs in local networks for permanent air quality monitoring. The State network for permanent air quality monitoring has a developed automatic system for reporting on alert and information threshold levels, whereas many local networks under the competence of regional and local self-governments still lack any fully installed systems of this type. In case of accidents, prompt action at all responsibility levels is necessary in order to prevent crisis and this requires developed and coordinated competent units of State Administration as well as self-government units. It is also necessary to be continuously active in improving the implementation of legislative regulations in the field of crises related to critical and alert levels of air pollutants, especially at local levels.
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
ARM Carbon Cycle Gases Flasks at SGP Site
Biraud, Sebastien
2013-03-26
Data from flasks are sampled at the Atmospheric Radiation Measurement Program ARM, Southern Great Plains Site and analyzed by the National Oceanic and Atmospheric Administration NOAA, Earth System Research Laboratory ESRL. The SGP site is included in the NOAA Cooperative Global Air Sampling Network. The surface samples are collected from a 60 m tower at the ARM SGP Central Facility, usually once per week in the afternoon. The aircraft samples are collected approximately weekly from a chartered aircraft, and the collection flight path is centered over the tower where the surface samples are collected. The samples are collected by the ARM and LBNL Carbon Project.
Analysis of the Chinese air route network as a complex network
NASA Astrophysics Data System (ADS)
Cai, Kai-Quan; Zhang, Jun; Du, Wen-Bo; Cao, Xian-Bin
2012-02-01
The air route network, which supports all the flight activities of the civil aviation, is the most fundamental infrastructure of air traffic management system. In this paper, we study the Chinese air route network (CARN) within the framework of complex networks. We find that CARN is a geographical network possessing exponential degree distribution, low clustering coefficient, large shortest path length and exponential spatial distance distribution that is obviously different from that of the Chinese airport network (CAN). Besides, via investigating the flight data from 2002 to 2010, we demonstrate that the topology structure of CARN is homogeneous, howbeit the distribution of flight flow on CARN is rather heterogeneous. In addition, the traffic on CARN keeps growing in an exponential form and the increasing speed of west China is remarkably larger than that of east China. Our work will be helpful to better understand Chinese air traffic systems.
The Clean Air Status and Trends Network (CASTNET) is a national air quality monitoring network designed to provide data to assess trends in air quality, atmospheric deposition, and ecological effects due to changes in air pollutant emissions.
NASA Technical Reports Server (NTRS)
Fairlie, T. D.; Szykman, Jim; Pierce, Robert B.; Gilliland, A. B.; Engel-Cox, Jill; Weber, Stephanie; Kittaka, Chieko; Al-Saadi, Jassim A.; Scheffe, Rich; Dimmick, Fred;
2008-01-01
The Clean Air Interstate Rule (CAIR) is expected to reduce transport of air pollutants (e.g. fine sulfate particles) in nonattainment areas in the Eastern United States. CAIR highlights the need for an integrated air quality observational and modeling system to understand sulfate as it moves in multiple dimensions, both spatially and temporally. Here, we demonstrate how results from an air quality model can be combined with a 3d monitoring network to provide decision makers with a tool to help quantify the impact of CAIR reductions in SO2 emissions on regional transport contributions to sulfate concentrations at surface monitors in the Baltimore, MD area, and help improve decision making for strategic implementation plans (SIPs). We sample results from the Community Multiscale Air Quality (CMAQ) model using ensemble back trajectories computed with the NASA Langley Research Center trajectory model to provide Lagrangian time series and vertical profile information, that can be compared with NASA satellite (MODIS), EPA surface, and lidar measurements. Results are used to assess the regional transport contribution to surface SO4 measurements in the Baltimore MSA, and to characterize the dominant source regions for low, medium, and high SO4 episodes.
AEROCAN, the Canadian sub-network of AERONET: Aerosol monitoring and air quality applications
NASA Astrophysics Data System (ADS)
Sioris, Christopher E.; Abboud, Ihab; Fioletov, Vitali E.; McLinden, Chris A.
2017-10-01
Previous studies have demonstrated the utility of AERONET (Aerosol Robotic Network) aerosol optical depth (AOD) data for monitoring the spatial variability of particulate matter (PM) in relatively polluted regions of the globe. AEROCAN, a Canadian sub-network of AERONET, was established 20 years ago and currently consists of twenty sites across the country. In this study, we examine whether the AEROCAN sunphotometer data provide evidence of anthropogenic contributions to ambient particulate matter concentrations in relatively clean Canadian locations. The similar weekly cycle of AOD and PM2.5 over Toronto provides insight into the impact of local pollution on observed AODs. High temporal correlations (up to r = 0.78) between daily mean AOD (or its fine-mode component) and PM2.5 are found at southern Ontario AEROCAN sites during May-August, implying that the variability in the aerosol load resides primarily in the boundary layer and that sunphotometers capture day-to-day PM2.5 variations at moderately polluted sites. The sensitivity of AEROCAN AOD data to anthropogenic surface-level aerosol enhancements is demonstrated using boundary-layer wind information for sites near sources of aerosol or its precursors. An advantage of AEROCAN relative to the Canadian in-situ National Air Pollution Surveillance (NAPS) network is the ability to detect free tropospheric aerosol enhancements, which can be large in the case of lofted forest fire smoke or desert dust. These aerosol plumes eventually descend to the surface, sometimes in populated areas, exacerbating air quality. In cases of large AOD (≥0.4), AEROCAN data are also useful in characterizing the aerosol type. The AEROCAN network includes three sites in the high Arctic, a region not sampled by the NAPS PM2.5 monitoring network. These polar sites show the importance of long-range transport and meteorology in the Arctic haze phenomenon. Also, AEROCAN sunphotometers are, by design and due to regular maintenance, the most valuable monitors available for long term aerosol trends. Using a variety of data analysis techniques and timescales, the usefulness of this ground-based remote-sensing sub-network for providing information relevant to air quality is demonstrated.
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).
Wong, Michelle; Bejarano, Esther; Carvlin, Graeme; Fellows, Katie; King, Galatea; Lugo, Humberto; Jerrett, Michael; Meltzer, Dan; Northcross, Amanda; Olmedo, Luis; Seto, Edmund; Wilkie, Alexa; English, Paul
2018-03-15
Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach.
Wong, Michelle; Bejarano, Esther; Carvlin, Graeme; King, Galatea; Lugo, Humberto; Jerrett, Michael; Northcross, Amanda; Olmedo, Luis; Seto, Edmund; Wilkie, Alexa; English, Paul
2018-01-01
Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach. PMID:29543726
2008-02-01
FINAL ENVIRONMENTAL ASSESSMENT February 2008 Malmstrom ® AFB WIDE AREA COVERAGE CONSTRUCT LAND MOBILE NETWORK COMMUNICATIONS INFRASTRUCTURE...Wide Area Coverage Construct Land Mobile Network Communications Infrastructure Malmstrom Air Force Base, Montana 5a. CONTRACT NUMBER 5b. GRANT...SIGNIFICANT IMPACT WIDE AREA COVERAGE CONSTRUCT LAND MOBILE NETWORK COMMUNICATIONS INFRASTRUCTURE MALMSTROM AIR FORCE BASE, MONTANA The
Overview of the new National Near-Road Air Quality Monitoring Network
In 2010, EPA promulgated new National Ambient Air Quality Standards (NAAQS) for nitrogen dioxide (NO2). As part of this new NAAQS, EPA required the establishment of a national near-road air quality monitoring network. This network will consist of one NO2 near-road monitoring st...
Quantitative Assessment of Detection Frequency for the INL Ambient Air Monitoring Network
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sondrup, A. Jeffrey; Rood, Arthur S.
A quantitative assessment of the Idaho National Laboratory (INL) air monitoring network was performed using frequency of detection as the performance metric. The INL air monitoring network consists of 37 low-volume air samplers in 31 different locations. Twenty of the samplers are located on INL (onsite) and 17 are located off INL (offsite). Detection frequencies were calculated using both BEA and ESER laboratory minimum detectable activity (MDA) levels. The CALPUFF Lagrangian puff dispersion model, coupled with 1 year of meteorological data, was used to calculate time-integrated concentrations at sampler locations for a 1-hour release of unit activity (1 Ci) formore » every hour of the year. The unit-activity time-integrated concentration (TICu) values were calculated at all samplers for releases from eight INL facilities. The TICu values were then scaled and integrated for a given release quantity and release duration. All facilities modeled a ground-level release emanating either from the center of the facility or at a point where significant emissions are possible. In addition to ground-level releases, three existing stacks at the Advanced Test Reactor Complex, Idaho Nuclear Technology and Engineering Center, and Material and Fuels Complex were also modeled. Meteorological data from the 35 stations comprising the INL Mesonet network, data from the Idaho Falls Regional airport, upper air data from the Boise airport, and three-dimensional gridded data from the weather research forecasting model were used for modeling. Three representative radionuclides identified as key radionuclides in INL’s annual National Emission Standards for Hazardous Air Pollutants evaluations were considered for the frequency of detection analysis: Cs-137 (beta-gamma emitter), Pu-239 (alpha emitter), and Sr-90 (beta emitter). Source-specific release quantities were calculated for each radionuclide, such that the maximum inhalation dose at any publicly accessible sampler or the National Emission Standards for Hazardous Air Pollutants maximum exposed individual location (i.e., Frenchman’s Cabin) was no more than 0.1 mrem yr–1 (i.e., 1% of the 10 mrem yr–1 standard). Detection frequencies were calculated separately for the onsite and offsite monitoring network. As expected, detection frequencies were generally less for the offsite sampling network compared to the onsite network. Overall, the monitoring network is very effective at detecting the potential releases of Cs-137 or Sr-90 from all sources/facilities using either the ESER or BEA MDAs. The network was less effective at detecting releases of Pu-239. Maximum detection frequencies for Pu-239 using ESER MDAs ranged from 27.4 to 100% for onsite samplers and 3 to 80% for offsite samplers. Using BEA MDAs, the maximum detection frequencies for Pu-239 ranged from 2.1 to 100% for onsite samplers and 0 to 5.9% for offsite samplers. The only release that was not detected by any of the samplers under any conditions was a release of Pu-239 from the Idaho Nuclear Technology and Engineering Center main stack (CPP-708). The methodology described in this report could be used to improve sampler placement and detection frequency, provided clear performance objectives are defined.« less
The use of hierarchical clustering for the design of optimized monitoring networks
NASA Astrophysics Data System (ADS)
Soares, Joana; Makar, Paul Andrew; Aklilu, Yayne; Akingunola, Ayodeji
2018-05-01
Associativity analysis is a powerful tool to deal with large-scale datasets by clustering the data on the basis of (dis)similarity and can be used to assess the efficacy and design of air quality monitoring networks. We describe here our use of Kolmogorov-Zurbenko filtering and hierarchical clustering of NO2 and SO2 passive and continuous monitoring data to analyse and optimize air quality networks for these species in the province of Alberta, Canada. The methodology applied in this study assesses dissimilarity between monitoring station time series based on two metrics: 1 - R, R being the Pearson correlation coefficient, and the Euclidean distance; we find that both should be used in evaluating monitoring site similarity. We have combined the analytic power of hierarchical clustering with the spatial information provided by deterministic air quality model results, using the gridded time series of model output as potential station locations, as a proxy for assessing monitoring network design and for network optimization. We demonstrate that clustering results depend on the air contaminant analysed, reflecting the difference in the respective emission sources of SO2 and NO2 in the region under study. Our work shows that much of the signal identifying the sources of NO2 and SO2 emissions resides in shorter timescales (hourly to daily) due to short-term variation of concentrations and that longer-term averages in data collection may lose the information needed to identify local sources. However, the methodology identifies stations mainly influenced by seasonality, if larger timescales (weekly to monthly) are considered. We have performed the first dissimilarity analysis based on gridded air quality model output and have shown that the methodology is capable of generating maps of subregions within which a single station will represent the entire subregion, to a given level of dissimilarity. We have also shown that our approach is capable of identifying different sampling methodologies as well as outliers (stations' time series which are markedly different from all others in a given dataset).
2015-05-22
sensor networks for managing power levels of wireless networks ; air and ground transportation systems for air traffic control and payload transport and... network systems, large-scale systems, adaptive control, discontinuous systems 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF...cover a broad spectrum of ap- plications including cooperative control of unmanned air vehicles, autonomous underwater vehicles, distributed sensor
2009-01-01
events. In an ideal situation, sample transportation will be in com- pliance with the UN sample shipment regulations (32); de - tailed information will...Berard, F. Briot, P. Boisson, D. Cavadore, C. Challeton- de Vathaire, S. Distinguin and A. Miele , Dosimetric management during a criticality accident. Nucl...Institute of Radiological Sciences (NIRS), Chiba, Japan; j Institut de Radioprotection et Sureté Nucléaire, Fontenay-Aux-Roses, France; and k Consumer
NASA Astrophysics Data System (ADS)
Markovic, Milos Z.; Prokop, Sebastian; Staebler, Ralf M.; Liggio, John; Harner, Tom
2015-07-01
The particle infiltration efficiencies (PIE) of three passive and one active air samplers were evaluated under field conditions. A wide-range particle spectrometer operating in the 250-4140 nm range was used to acquire highly temporally resolved particle-number and size distributions for the different samplers compared to ambient air. Overall, three of the four evaluated samplers were able to acquire a representative sample of ambient particles with PIEs of 91.5 ± 13.7% for the GAPS Network sampler, 103 ± 15.5% for the Lancaster University sampler, and 89.6 ± 13.4% for a conventional PS-1 high-volume active air sampler (Hi-Vol). Significantly (p = 0.05) lower PIE of 54 ± 8.0% was acquired for the passive sampler used under the MONET program. These findings inform the comparability and use of passive and active samplers for measuring particle-associated priority chemicals in air.
40 CFR 58.10 - Annual monitoring network plan and periodic network assessment.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Annual monitoring network plan and periodic network assessment. 58.10 Section 58.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.10 Annual...
40 CFR 58.10 - Annual monitoring network plan and periodic network assessment.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Annual monitoring network plan and periodic network assessment. 58.10 Section 58.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.10 Annual...
Verardo, Vito; Gómez-Caravaca, Ana Maria; Messia, Maria Cristina; Marconi, Emanuele; Caboni, Maria Fiorenza
2011-09-14
Barley byproducts obtained by air classification have been used to produce a different barley functional spaghetti, which were compared to different commercial whole semolina samples. Total, insoluble, and soluble fiber and β-glucan contents of the barley spaghetti were found to be greater than those of commercial samples. Furthermore, it was proved that barley spaghetti reached the FDA requirements, which could allow these pastas to deserve the health claims "good source of dietary fiber" and "may reduce the risk of heart disease". When the barley coarse fraction was used, a flavan-3-ols enrichment and an increase of antioxidant activity were reported, while commercial samples showed the absence of flavan-3-ols and a higher presence of phenolic acids and tannins. Whole semolina commercial spaghetti had a significantly higher content of phenolic acids than semolina spaghetti samples. Besides, it was observed that when vital gluten was added to the spaghetti formulation, phenolic compounds were blocked in the gluten network and were partially released during the cooking process.
The recent changes and topics in CONTRAIL project
NASA Astrophysics Data System (ADS)
Machida, Toshinobu; Umezawa, Taku; Sawa, Yousuke; Niwa, Yosuke; Matsueda, Hidekazu
2016-04-01
CONTRAIL (Comprehensive Observation Network for TRace gases by AIrLiner) project has been conducted since 2005 with Continuous CO2 Measuring Equipment (CME) and Automatic air Sampling Equipment (ASE) onboard commercial airliners for observations of atmospheric greenhouse gases. Japan Airlines (JAL) offers eight Boeing 777-200ER airplanes modified for CONTRAIL; CME and ASE can be installed on all and five of them, respectively. ASE measurements have provided the long records of greenhouse gases in the upper troposphere along the flight route between Japan and Australia. In addition, we started a new sampling program between Japan and Europe in 2012 to obtain data at higher latitudes and the UT/LS region. When the 777-200ER airplane was not operated for the observation route, we used Manual air Sampling Equipment (MSE) for taking air onboard as substitute for ASE. Since flight routes with 777-200ER have been restricted only to Asian countries and Hawaii in the last few years, additional two Boeing 777-300ERs were modified to install CME and expand area coverage of CO2 observations to Europe, Australia and the east coast of US in 2015-2016. We also present our recent data analysis for intensive CME observations over Delhi, India, which indicates a significant impact of Indian wintertime agriculture on the regional carbon budget.
40 CFR 58.13 - Monitoring network completion.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 6 2012-07-01 2012-07-01 false Monitoring network completion. 58.13 Section 58.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a...
40 CFR 58.13 - Monitoring network completion.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 6 2014-07-01 2014-07-01 false Monitoring network completion. 58.13 Section 58.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a...
40 CFR 58.13 - Monitoring network completion.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 6 2013-07-01 2013-07-01 false Monitoring network completion. 58.13 Section 58.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a...
NASA Astrophysics Data System (ADS)
Sanchez, M.; Probst, L.; Blazevic, E.; Nakao, B.; Northrup, M. A.
2011-11-01
We describe a fully automated and autonomous air-borne biothreat detection system for biosurveillance applications. The system, including the nucleic-acid-based detection assay, was designed, built and shipped by Microfluidic Systems Inc (MFSI), a new subsidiary of PositiveID Corporation (PSID). Our findings demonstrate that the system and assay unequivocally identify pathogenic strains of Bacillus anthracis, Yersinia pestis, Francisella tularensis, Burkholderia mallei, and Burkholderia pseudomallei. In order to assess the assay's ability to detect unknown samples, our team also challenged it against a series of blind samples provided by the Department of Homeland Security (DHS). These samples included natural occurring isolated strains, near-neighbor isolates, and environmental samples. Our results indicate that the multiplex assay was specific and produced no false positives when challenged with in house gDNA collections and DHS provided panels. Here we present another analytical tool for the rapid identification of nine Centers for Disease Control and Prevention category A and B biothreat organisms.
Network modeling of PM10 concentration in Malaysia
NASA Astrophysics Data System (ADS)
Supian, Muhammad Nazirul Aiman Abu; Bakar, Sakhinah Abu; Razak, Fatimah Abdul
2017-08-01
Air pollution is not a new phenomenon in Malaysia. The Department of Environment (DOE) monitors the country's ambient air quality through a network of 51 stations. The air quality is measured using the Air Pollution Index (API) which is mainly recorded based on the concentration of particulate matter, PM10 readings. The Continuous Air Quality Monitoring (CAQM) stations are located in various places across the country. In this study, a network model of air quality based on PM10 concen tration for selected CAQM stations in Malaysia has been developed. The model is built using a graph formulation, G = (V, E) where vertex, V is a set of CAQM stations and edges, E is a set of correlation values for each pair of vertices. The network measurements such as degree distributions, closeness centrality, and betweenness centrality are computed to analyse the behaviour of the network. As a result, a rank of CAQM stations has been produced based on their centrality characteristics.
Global thermal analysis of air-air cooled motor based on thermal network
NASA Astrophysics Data System (ADS)
Hu, Tian; Leng, Xue; Shen, Li; Liu, Haidong
2018-02-01
The air-air cooled motors with high efficiency, large starting torque, strong overload capacity, low noise, small vibration and other characteristics, are widely used in different department of national industry, but its cooling structure is complex, it requires the motor thermal management technology should be high. The thermal network method is a common method to calculate the temperature field of the motor, it has the advantages of small computation time and short time consuming, it can save a lot of time in the initial design phase of the motor. The domain analysis of air-air cooled motor and its cooler was based on thermal network method, the combined thermal network model was based, the main components of motor internal and external cooler temperature were calculated and analyzed, and the temperature rise test results were compared to verify the correctness of the combined thermal network model, the calculation method can satisfy the need of engineering design, and provide a reference for the initial and optimum design of the motor.
NASA Astrophysics Data System (ADS)
Lugin, IV
2018-03-01
In focus are the features of construction of the generalized design model for the network method to study air distribution in ventilation system in subway with the single-track tunnel. The generalizations, assumptions and simplifications included in the model are specified. The air distribution is calculated with regard to the influence of topology and air resistances of the ventilation network sections. The author studies two variants of the subway line: half-open and closed with dead end on the both sides. It is found that the total air exchange at a subway station depends on the station location within the line. The operating mode of fans remains unaltered in this case. The article shows that elimination of air leakage in the station ventilation room allows an increase in the air flow rate by 7–8% at the same energy consumption by fans. The influence of the stop of a train in the tunnel on the air distribution is illustrated.
Stable Encapsulated Air Nanobubbles in Water.
Wang, Yu; Liu, Guojun; Hu, Heng; Li, Terry Yantian; Johri, Amer M; Li, Xiaoyu; Wang, Jian
2015-11-23
The dispersion into water of nanocapsules bearing a highly hydrophobic fluorinated internal lining yielded encapsulated air nanobubbles. These bubbles, like their micrometer-sized counterparts (microbubbles), effectively reflected ultrasound. More importantly, the nanobubbles survived under ultrasonication 100-times longer than a commercial microbubble sample that is currently in clinical use. We justify this unprecedented stability theoretically. These nanobubbles, owing to their small size and potential ability to permeate the capillary networks of tissues, may expand the applications of microbubbles in diagnostic ultrasonography and find new applications in ultrasound-regulated drug delivery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
EPA through statutory mandates has monitored air, water, land and human health for the past several decades. The design of the ambient air monitoring networks, for the most part, has been loosely tied single-pollutant networks focused on large urban areas. These networks supply t...
Olmedo, Luis; Bejarano, Ester; Lugo, Humberto; Murillo, Eduardo; Seto, Edmund; Wong, Michelle; King, Galatea; Wilkie, Alexa; Meltzer, Dan; Carvlin, Graeme; Jerrett, Michael; Northcross, Amanda
2017-01-01
Summary: The Imperial County Community Air Monitoring Network (the Network) is a collaborative group of community, academic, nongovernmental, and government partners designed to fill the need for more detailed data on particulate matter in an area that often exceeds air quality standards. The Network employs a community-based environmental monitoring process in which the community and researchers have specific, well-defined roles as part of an equitable partnership that also includes shared decision-making to determine study direction, plan research protocols, and conduct project activities. The Network is currently producing real-time particulate matter data from 40 low-cost sensors throughout Imperial County, one of the largest community-based air networks in the United States. Establishment of a community-led air network involves engaging community members to be citizen-scientists in the monitoring, siting, and data collection process. Attention to technical issues regarding instrument calibration and validation and electronic transfer and storage of data is also essential. Finally, continued community health improvements will be predicated on facilitating community ownership and sustainability of the network after research funds have been expended. https://doi.org/10.1289/EHP1772 PMID:28886604
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
Based on Artificial Neural Network to Realize K-Parameter Analysis of Vehicle Air Spring System
NASA Astrophysics Data System (ADS)
Hung, San-Shan; Hsu, Chia-Ning; Hwang, Chang-Chou; Chen, Wen-Jan
2017-10-01
In recent years, because of the air-spring control technique is more mature, that air- spring suspension systems already can be used to replace the classical vehicle suspension system. Depend on internal pressure variation of the air-spring, thestiffnessand the damping factor can be adjusted. Because of air-spring has highly nonlinear characteristic, therefore it isn’t easy to construct the classical controller to control the air-spring effectively. The paper based on Artificial Neural Network to propose a feasible control strategy. By using offline way for the neural network design and learning to the air-spring in different initial pressures and different loads, offline method through, predict air-spring stiffness parameter to establish a model. Finally, through adjusting air-spring internal pressure to change the K-parameter of the air-spring, realize the well dynamic control performance of air-spring suspension.
Theory, Design, and Algorithms for Optimal Control of wireless Networks
2010-06-09
The implementation of network-centric warfare technologies is an abiding, critical interest of Air Force Science and Technology efforts for the Warfighter. Wireless communications, strategic signaling are areas of critical Air Force Mission need. Autonomous networks of multiple, heterogeneous Throughput enhancement and robust connectivity in communications and sensor networks are critical factors in net-centric USAF operations. This research directly supports the Air Force vision of information dominance and the development of anywhere, anytime operational readiness.
Fine particulate matter of aerodynamic diameter 2.5 m or less (PM-2.5) has been found harmful to human health, and a National Ambient Air Quality Standard for PM-2.5 was promulgated by the U.S. Environmental Protection Agency in July 1997. A national network of ambient monitorin...
Fine particulate matter of aerodynamic diameter 2.5 m or less (PM-2.5) has been found harmful to human health, and a National Ambient Air Quality Standard for PM-2.5 was promulgated by the U.S. Environmental Protection Agency in July 1997. A national network of ambient monitorin...
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.
Airborne fine particulate matter across the United States is monitored by different networks, the three prevalent ones presently being the Clean Air Status and Trend Network (CASTNet), the Interagency Monitoring of PROtected Visual Environment Network (IMPROVE) and the Speciati...
High Sensitivity Gas Detection Using a Macroscopic Three-Dimensional Graphene Foam Network
Yavari, Fazel; Chen, Zongping; Thomas, Abhay V.; Ren, Wencai; Cheng, Hui-Ming; Koratkar, Nikhil
2011-01-01
Nanostructures are known to be exquisitely sensitive to the chemical environment and offer ultra-high sensitivity for gas-sensing. However, the fabrication and operation of devices that use individual nanostructures for sensing is complex, expensive and suffers from poor reliability due to contamination and large variability from sample-to-sample. By contrast, conventional solid-state and conducting-polymer sensors offer excellent reliability but suffer from reduced sensitivity at room-temperature. Here we report a macro graphene foam-like three-dimensional network which combines the best of both worlds. The walls of the foam are comprised of few-layer graphene sheets resulting in high sensitivity; we demonstrate parts-per-million level detection of NH3 and NO2 in air at room-temperature. Further, the foam is a mechanically robust and flexible macro-scale network that is easy to contact (without Lithography) and can rival the durability and affordability of traditional sensors. Moreover, Joule-heating expels chemisorbed molecules from the foam's surface leading to fully-reversible and low-power operation. PMID:22355681
An Intercomparison of the Deposition Models Used in the CASTNET and CAPMoN Networks
To assess long-term trends in atmospheric deposition, the U.S. operates the Clean Air Status and Trends Network (CASTNET) and Canada operates the Canadian Air and Precipitation Monitoring Network (CAPMoN). Both networks use modeled dry deposition velocities and measured atmospher...
Bohlin, Pernilla; Audy, Ondřej; Škrdlíková, Lenka; Kukučka, Petr; Vojta, Šimon; Přibylová, Petra; Prokeš, Roman; Čupr, Pavel; Klánová, Jana
2014-11-01
Indoor air pollution has been recognized as an important risk factor for human health, especially in areas where people tend to spend most of their time indoors. Many semi-volatile organic compounds (SVOCs) have primarily indoor sources and are present in orders of magnitude higher concentrations indoors than outdoors. Despite this, awareness of SVOCs in indoor air and assessment of the link between indoor concentrations and human health have lagged behind those of outdoor air. This is partially related to challenges associated with indoor sampling of SVOCs. Passive air samplers (PASs), which are widely accepted in established outdoor air monitoring networks, have been used to fill the knowledge gaps on indoor SVOCs distribution. However, their applicability for indoor environments and the assessment of human health risks lack sufficient experimental data. To address this issue, we performed an indoor calibration study of polyurethane foam (PUF) PAS deployed in a double-dome chamber, covering both legacy and new SVOC classes. PUF-PAS and a continuous low-volume active air sampler (AAS) were co-deployed for a calibration period of twelve weeks. Based on the results from this evaluation, PUF-PAS in a double-bowl chamber is recommended for indoor sampling and health risk assessment of gas phase SVOCs, including novel brominated flame retardants (nBFR) providing sufficient exposure time is applied. Data for particle associated SVOCs suffered from significant uncertainties caused by low level of detection and low precision in this study. A more open chamber design for indoor studies may allow for higher sampling rates (RS) and better performance for the particle associated SVOCs.
Scale-Free Networks and Commercial Air Carrier Transportation in the United States
NASA Technical Reports Server (NTRS)
Conway, Sheila R.
2004-01-01
Network science, or the art of describing system structure, may be useful for the analysis and control of large, complex systems. For example, networks exhibiting scale-free structure have been found to be particularly well suited to deal with environmental uncertainty and large demand growth. The National Airspace System may be, at least in part, a scalable network. In fact, the hub-and-spoke structure of the commercial segment of the NAS is an often-cited example of an existing scale-free network After reviewing the nature and attributes of scale-free networks, this assertion is put to the test: is commercial air carrier transportation in the United States well explained by this model? If so, are the positive attributes of these networks, e.g. those of efficiency, flexibility and robustness, fully realized, or could we effect substantial improvement? This paper first outlines attributes of various network types, then looks more closely at the common carrier air transportation network from perspectives of the traveler, the airlines, and Air Traffic Control (ATC). Network models are applied within each paradigm, including discussion of implied strengths and weaknesses of each model. Finally, known limitations of scalable networks are discussed. With an eye towards NAS operations, utilizing the strengths and avoiding the weaknesses of scale-free networks are addressed.
Using neural networks for prediction of air pollution index in industrial city
NASA Astrophysics Data System (ADS)
Rahman, P. A.; Panchenko, A. A.; Safarov, A. M.
2017-10-01
This scientific paper is dedicated to the use of artificial neural networks for the ecological prediction of state of the atmospheric air of an industrial city for capability of the operative environmental decisions. In the paper, there is also the described development of two types of prediction models for determining of the air pollution index on the basis of neural networks: a temporal (short-term forecast of the pollutants content in the air for the nearest days) and a spatial (forecast of atmospheric pollution index in any point of city). The stages of development of the neural network models are briefly overviewed and description of their parameters is also given. The assessment of the adequacy of the prediction models, based on the calculation of the correlation coefficient between the output and reference data, is also provided. Moreover, due to the complexity of perception of the «neural network code» of the offered models by the ordinary users, the software implementations allowing practical usage of neural network models are also offered. It is established that the obtained neural network models provide sufficient reliable forecast, which means that they are an effective tool for analyzing and predicting the behavior of dynamics of the air pollution in an industrial city. Thus, this scientific work successfully develops the urgent matter of forecasting of the atmospheric air pollution index in industrial cities based on the use of neural network models.
[Restoration of microbial ammonia oxidizers in air-dried forest soils upon wetting].
Zhou, Xue; Huang, Rong; Song, Ge; Pan, Xianzhang; Jia, Zhongjun
2014-11-04
This study was aimed to investigate the abundance and community shift of ammonia-oxidizing archaea (AOA) and bacteria (AOB) in air-dried forest soils in response to water addition, to explore the applicability of air-dried soil for microbial ecology study, and to elucidate whether AOA within the marine group 1. 1a dominate ammonia oxidizers communities in the acidic forest soils in China. Soil samples were collected from 10 forest sites of the China Ecosystem Research Network (CERN) and kept under air-drying conditions in 2010. In 2013 the air-dried soil samples were adjusted to 60% of soil maximum water holding capacity for a 28-day incubation at 28 degrees C in darkness. DGGE fingerprinting, clone library construction, pyrosequencing and quantitative PCR of amoA genes were performed to assess community change of ammonia oxidizers in air-dried and re-wetted soils. After incubation for 28 days, the abundance of bacteria and archaea increased significantly, up to 3,230 and 568 times, respectively. AOA increased significantly in 8 samples, and AOB increased significantly in 5 of 10 samples. However, pyrosequencing of amoA genes reveals insignificant changes in composition of AOA and AOB communities. Phylogenetic analysis of amoA genes indicates that archaeal ammonia oxidizers were predominated by AOA within the soil group 1. 1b lineage, while the Nitrosospira-like AOB dominate bacteria ammonia oxidizer communities. There was a significantly positive correlation between AOA/AOB ratio and total nitrogen (r2 = 0.54, P < 0.05), implying that soil ammonia oxidation might be dominated by AOA in association with ammonium released from soil mineralization. Phylogenetic analysis suggest that AOA members within the soil group 1. 1b lineage were not restricted to non-acidic soils as previously thought. The abundance rather than composition of AOA and AOB changed in response to water addition. This indicates that air-dried soil could be of help for microbial biogeography study.
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.
The field campaigns of the European Tracer Experiment (ETEX). overview and results
NASA Astrophysics Data System (ADS)
Nodop, K.; Connolly, R.; Girardi, F.
As part of the European Tracer Experiment (ETEX) two successful atmospheric experiments were carried out in October and November, 1994. Perfluorocarbon (PFC) tracers were released into the atmosphere in Monterfil, Brittany, and air samples were taken at 168 stations in 17 European countries for 72 h after the release. Upper air tracer measurements were made from three aircraft. During the first experiment a westerly air flow transported the tracer plume north-eastwards across Europe. During the second release the flow was eastwards. The results from the ground sampling network allowed the determination of the cloud evolution as far as Sweden, Poland and Bulgaria. This demonstrated that the PFT technique can be successfully applied in long-range tracer experiments up to 2000 km. Typical background concentrations of the tracer used are around 5-7 fl ℓ -1 in ambient air. Concentrations in the plume ranged from 10 to above 200 fl/ℓ -1. The tracer release characteristics, the tracer concentrations at the ground and in upper air, the routine and additional meteorological observations at the ground level and in upper air, trajectories derived from constant-level balloons and the meteorological input fields for long-range transport models are assembled in the ETEX database. The ETEX database is accessible via the Internet. Here, an overview is given of the design of the experiment, the methods used and the data obtained.
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.
Airborne Network Optimization with Dynamic Network Update
2015-03-26
Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force Institute of Technology Air University...Member Dr. Barry E. Mullins Member AFIT-ENG-MS-15-M-030 Abstract Modern networks employ congestion and routing management algorithms that can perform...airborne networks. Intelligent agents can make use of Kalman filter predictions to make informed decisions to manage communication in airborne networks. The
Fawzy, Amr S
2010-01-01
The aim was to characterize the variations in the structure and surface dehydration of acid demineralized intertubular dentin collagen network with the variations in dentin depth and time of air-exposure (3, 6, 9 and 12 min). In addition, to study the effect of these variations on the tensile bond strength (TBS) to dentin. Phosphoric acid demineralized superficial and deep dentin specimens were prepared. The structure of the dentin collagen network was characterized by AFM. The surface dehydration was characterized by probing the nano-scale adhesion force (F(ad)) between AFM tip and intertubular dentin surface as a new experimental approach. The TBS to dentin was evaluated using an alcohol-based dentin self-priming adhesive. AFM images revealed a demineralized open collagen network structure in both of superficial and deep dentin at 3 and 6 min of air-exposure. However, at 9 min, superficial dentin showed more collapsed network structure compared to deep dentin that partially preserved the open network structure. Total collapsed structure was found at 12 min for both of superficial and deep dentin. The value of the F(ad) is decreased with increasing the time of air-exposure and is increased with dentin depth at the same time of air-exposure. The TBS was higher for superficial dentin at 3 and 6 min, however, no difference was found at 9 and 12 min. The ability of the demineralized dentin collagen network to resist air-dehydration and to preserve the integrity of open network structure with the increase in air-exposure time is increased with dentin depth. Although superficial dentin achieves higher bond strength values, the difference in the bond strength is decreased by increasing the time of air-exposure. The AFM probed F(ad) showed to be sensitive approach to characterize surface dehydration, however, further researches are recommended regarding the validity of such approach.
Elemental composition and size distribution of particulates in Cleveland, Ohio
NASA Technical Reports Server (NTRS)
King, R. B.; Fordyce, J. S.; Neustadter, H. E.; Leibecki, H. F.
1975-01-01
Measurements were made of the elemental particle size distribution at five contrasting urban environments with different source-type distributions in Cleveland, Ohio. Air quality conditions ranged from normal to air pollution alert levels. A parallel network of high-volume cascade impactors (5-state) were used for simultaneous sampling on glass fiber surfaces for mass determinations and on Whatman-41 surfaces for elemental analysis by neutron activation for 25 elements. The elemental data are assessed in terms of distribution functions and interrelationships and are compared between locations as a function of resultant wind direction in an attempt to relate the findings to sources.
Elemental composition and size distribution of particulates in Cleveland, Ohio
NASA Technical Reports Server (NTRS)
Leibecki, H. F.; King, R. B.; Fordyce, J. S.; Neustadter, H. E.
1975-01-01
Measurements have been made of the elemental particle size distribution at five contrasting urban environments with different source-type distributions in Cleveland, Ohio. Air quality conditions ranged from normal to air pollution alert levels. A parallel network of high-volume cascade impactors (5-stage) were used for simultaneous sampling on glass fiber surfaces for mass determinations and on Whatman-41 surfaces for elemental analysis by neutron activation for 25 elements. The elemental data are assessed in terms of distribution functions and interrelationships and are compared between locations as a function of resultant wind direction in an attempt to relate the findings to sources.
An Investigation of Synchrony in Transport Networks
NASA Technical Reports Server (NTRS)
Kincaid, Rex K.; Alexandrov, Natalia M.; Holroyd, Michael J.
2007-01-01
The cumulative degree distributions of transport networks, such as air transportation networks and respiratory neuronal networks, follow power laws. The significance of power laws with respect to other network performance measures, such as throughput and synchronization, remains an open question. Evolving methods for the analysis and design of air transportation networks must address network performance in the face of increasing demands and the need to contain and control local network disturbances, such as congestion. Toward this end, we investigate functional relationships that govern the performance of transport networks; for example, the links between the first nontrivial eigenvalue of a network's Laplacian matrix - a quantitative measure of network synchronizability - and other global network parameters. In particular, among networks with a fixed degree distribution and fixed network assortativity (a measure of a network's preference to attach nodes based on a similarity or difference), those with the small eigenvalue are shown to be poor synchronizers, to have much longer shortest paths and to have greater clustering in comparison to those with large. A simulation of a respiratory network adds data to our investigation. This study is a beginning step in developing metrics and design variables for the analysis and active design of air transport networks.
Analysis of Nitrogen Dioxide and Sulphur Dioxide in Lima, Peru: Trends and Seasonal Variations
NASA Astrophysics Data System (ADS)
Pacsi, S.; Rappenglueck, B.
2007-12-01
This research was carried out to show a general analysis of the monthly and yearly variation (1996-2002) and the tendency of the nitrogen dioxide (NO2) and sulfur dioxide (SO2) for the 5 stations of the air quality network of Lima. The SO2 and NO2 concentrations were measured by the Dirección General de Salud Ambiental (DIGESA), using the active sampling method and the chemical analysis has been determined by Turbidimetry and Colorimetry for the SO2 and NO2 respectively. The monthly average variation (1996-2001) of SO2 in the Lima Center station has a small annual range (32,4 mikrograms/m3) with maximum values in autumn (April) and minimum in winter (June). The NO2 presents a higher annual range (128,2 mikrograms/m3) and its minimum values occur in the summer and the maximum in spring. The annual averages analysis (2000-2002) of the air quality monitoring network of Lima shows that the SO2 and NO2 values are maximum in the Lima Center station and exceed the Peruvian air quality standard (ECAs) in 30% and 75% respectively. The yearly variation (1996-2001) in the Lima Center station show an increasing tendency in the SO2 (significant) and NO2 (not significant) values, which indicates the critical level of the air quality in Lima, therefore the implementation of the air pollution control programs is urgent.
NASA Technical Reports Server (NTRS)
Prud'homme, Genevieve; Dobbin, Nina A.; Sun, Liu; Burnet, Richard T.; Martin, Randall V.; Davidson, Andrew; Cakmak, Sabit; Villeneuve, Paul J.; Lamsal, Lok N.; vanDonkelaar, Aaron;
2013-01-01
Satellite remote sensing (RS) has emerged as a cutting edge approach for estimating ground level ambient air pollution. Previous studies have reported a high correlation between ground level PM2.5 and NO2 estimated by RS and measurements collected at regulatory monitoring sites. The current study examined associations between air pollution and adverse respiratory and allergic health outcomes using multi-year averages of NO2 and PM2.5 from RS and from regulatory monitoring. RS estimates were derived using satellite measurements from OMI, MODIS, and MISR instruments. Regulatory monitoring data were obtained from Canada's National Air Pollution Surveillance Network. Self-reported prevalence of doctor-diagnosed asthma, current asthma, allergies, and chronic bronchitis were obtained from the Canadian Community Health Survey (a national sample of individuals 12 years of age and older). Multi-year ambient pollutant averages were assigned to each study participant based on their six digit postal code at the time of health survey, and were used as a marker for long-term exposure to air pollution. RS derived estimates of NO2 and PM2.5 were associated with 6e10% increases in respiratory and allergic health outcomes per interquartile range (3.97 mg m3 for PM2.5 and 1.03 ppb for NO2) among adults (aged 20e64) in the national study population. Risk estimates for air pollution and respiratory/ allergic health outcomes based on RS were similar to risk estimates based on regulatory monitoring for areas where regulatory monitoring data were available (within 40 km of a regulatory monitoring station). RS derived estimates of air pollution were also associated with adverse health outcomes among participants residing outside the catchment area of the regulatory monitoring network (p < 0.05).
Cosmic veto gamma-spectrometry for Comprehensive Nuclear-Test-Ban Treaty samples
NASA Astrophysics Data System (ADS)
Burnett, J. L.; Davies, A. V.
2014-05-01
The Comprehensive Nuclear-Test-Ban Treaty (CTBT) is supported by a global network of monitoring stations that perform high-resolution gamma-spectrometry on air filter samples for the identification of 85 radionuclides. At the UK CTBT Radionuclide Laboratory (GBL15), a novel cosmic veto gamma-spectrometer has been developed to improve the sensitivity of station measurements, providing a mean background reduction of 80.8% with mean MDA improvements of 45.6%. The CTBT laboratory requirement for a 140Ba MDA is achievable after 1.5 days counting compared to 5-7 days using conventional systems. The system consists of plastic scintillation plates that detect coincident cosmic-ray interactions within an HPGe gamma-spectrometer using the Canberra LynxTM multi-channel analyser. The detector is remotely configurable using a TCP/IP interface and requires no dedicated coincidence electronics. It would be especially useful in preventing false-positives at remote station locations (e.g. Halley, Antarctica) where sample transfer to certified laboratories is logistically difficult. The improved sensitivity has been demonstrated for a CTBT air filter sample collected after the Fukushima incident.
Petrich, Nicholas T.; Spak, Scott N.; Carmichael, Gregory R.; Hu, Dingfei; Martinez, Andres; Hornbuckle, Keri C.
2013-01-01
Passive air samplers (PAS) including polyurethane foam (PUF) are widely deployed as an inexpensive and practical way to sample semi-volatile pollutants. However, concentration estimates from PAS rely on constant empirical mass transfer rates, which add unquantified uncertainties to concentrations. Here we present a method for modeling hourly sampling rates for semi-volatile compounds from hourly meteorology using first-principle chemistry, physics, and fluid dynamics, calibrated from depuration experiments. This approach quantifies and explains observed effects of meteorology on variability in compound-specific sampling rates and analyte concentrations; simulates nonlinear PUF uptake; and recovers synthetic hourly concentrations at a reference temperature. Sampling rates are evaluated for polychlorinated biphenyl congeners at a network of Harner model samplers in Chicago, Illinois during 2008, finding simulated average sampling rates within analytical uncertainty of those determined from loss of depuration compounds, and confirming quasi-linear uptake. Results indicate hourly, daily and interannual variability in sampling rates, sensitivity to temporal resolution in meteorology, and predictable volatility-based relationships between congeners. We quantify importance of each simulated process to sampling rates and mass transfer and assess uncertainty contributed by advection, molecular diffusion, volatilization, and flow regime within the PAS, finding PAS chamber temperature contributes the greatest variability to total process uncertainty (7.3%). PMID:23837599
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 ...
Near-Road Air Quality Monitoring: Factors Affecting Network Design and Interpretation of Data
The growing number of health studies identifying adverse health effects for populations spending significant amounts of time near large roadways has increased the interest in monitoring air quality in this microenvironment. Designing near-road air monitoring networks or interpret...
Ambient air monitoring plan for Ciudad Acuna and Piedra Negras, Coahuila, Mexico. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Winberry, J.; Henning, L.; Crume, R.
1998-01-01
The Cities of Ciudad Acuna and Piedras Negras and the State of Coahuila in Mexico are interested in improving ambient air quality monitoring capabilities in the two cities through the establishment of a network of ambient air monitors. The purpose of the network is to characterize population exposure to potentially harmful air contaminants, possibly including sulfur dioxide (SO{sub 2}), nitrogen oxides (NO{sub x}), ozone (O{sub 3}), carbon monoxide (CO), total suspended particulate matter (TSP), particulate matter with aerodynamic diameter less than 100 micrometers PM-10, and lead. This report presents the results of an evaluation of existing air quality monitoring equipmentmore » and facilities in Ciudad Acuna and Piedras Negras. Additionally, the report presents recommendations for developing an air quality monitoring network for PM-10, SO{sub 2}, lead, and ozone in these cities, using a combination of both new and existing equipment. The human resources currently available and ultimately needed to operate and maintain the network are also discussed.« less
Hyper-Spectral Networking Concept of Operations and Future Air Traffic Management Simulations
NASA Technical Reports Server (NTRS)
Davis, Paul; Boisvert, Benjamin
2017-01-01
The NASA sponsored Hyper-Spectral Communications and Networking for Air Traffic Management (ATM) (HSCNA) project is conducting research to improve the operational efficiency of the future National Airspace System (NAS) through diverse and secure multi-band, multi-mode, and millimeter-wave (mmWave) wireless links. Worldwide growth of air transportation and the coming of unmanned aircraft systems (UAS) will increase air traffic density and complexity. Safe coordination of aircraft will require more capable technologies for communications, navigation, and surveillance (CNS). The HSCNA project will provide a foundation for technology and operational concepts to accommodate a significantly greater number of networked aircraft. This paper describes two of the HSCNA projects technical challenges. The first technical challenge is to develop a multi-band networking concept of operations (ConOps) for use in multiple phases of flight and all communication link types. This ConOps will integrate the advanced technologies explored by the HSCNA project and future operational concepts into a harmonized vision of future NAS communications and networking. The second technical challenge discussed is to conduct simulations of future ATM operations using multi-bandmulti-mode networking and technologies. Large-scale simulations will assess the impact, compared to todays system, of the new and integrated networks and technologies under future air traffic demand.
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.
Evaluation of Data Replacement Strategies for CASTNET Dry Deposition Modeling
The U.S. Environmental Protection Agency (EPA) established the Clean Air Status and Trends Network (CASTNET) and its predecessor, the National Dry Deposition Network (NDDN), as national air quality and meteorological monitoring networks. The purpose of CASTNET is to track the pr...
NASA Astrophysics Data System (ADS)
Wentworth, Gregory R.; Aklilu, Yayne-abeba; Landis, Matthew S.; Hsu, Yu-Mei
2018-04-01
During May 2016 a very large boreal wildfire burned throughout the Athabasca Oil Sands Region (AOSR) in central Canada, and in close proximity to an extensive air quality monitoring network. This study examines speciated 24-h integrated polycyclic aromatic hydrocarbon (PAH) and volatile organic compound (VOC) measurements collected every sixth day at four and seven sites, respectively, from May to August 2016. The sum of PAHs (ΣPAH) was on average 17 times higher in fire-influenced samples (852 ng m-3, n = 8), relative to non-fire influenced samples (50 ng m-3, n = 64). Diagnostic PAH ratios in fire-influenced samples were indicative of a biomass burning source, whereas ratios in June to August samples showed additional influence from petrogenic and fossil fuel combustion. The average increase in the sum of VOCs (ΣVOC) was minor by comparison: 63 ppbv for fire-influenced samples (n = 16) versus 46 ppbv for non-fire samples (n = 90). The samples collected on August 16th and 22nd had large ΣVOC concentrations at all sites (average of 123 ppbv) that were unrelated to wildfire emissions, and composed primarily of acetaldehyde and methanol suggesting a photochemically aged air mass. Normalized excess enhancement ratios (ERs) were calculated for 20 VOCs and 23 PAHs for three fire influenced samples, and the former were generally consistent with previous observations. To our knowledge, this is the first study to report ER measurements for a number of VOCs and PAHs in fresh North American boreal wildfire plumes. During May the aged wildfire plume intercepted the cities of Edmonton (∼380 km south) or Lethbridge (∼790 km south) on four separate occasions. No enhancement in ground-level ozone (O3) was observed in these aged plumes despite an assumed increase in O3 precursors. In the AOSR, the only daily-averaged VOCs which approached or exceeded the hourly Alberta Ambient Air Quality Objectives (AAAQOs) were benzene (during the fire) and acetaldehyde (on August 16th and 22nd). Implications for local and regional air quality as well as suggestions for supplemental air monitoring during future boreal fires, are also discussed.
Ding, Weifu; Zhang, Jiangshe; Leung, Yee
2016-10-01
In this paper, we predict air pollutant concentration using a feedforward artificial neural network inspired by the mechanism of the human brain as a useful alternative to traditional statistical modeling techniques. The neural network is trained based on sparse response back-propagation in which only a small number of neurons respond to the specified stimulus simultaneously and provide a high convergence rate for the trained network, in addition to low energy consumption and greater generalization. Our method is evaluated on Hong Kong air monitoring station data and corresponding meteorological variables for which five air quality parameters were gathered at four monitoring stations in Hong Kong over 4 years (2012-2015). Our results show that our training method has more advantages in terms of the precision of the prediction, effectiveness, and generalization of traditional linear regression algorithms when compared with a feedforward artificial neural network trained using traditional back-propagation.
DESIGN OF LARGE-SCALE AIR MONITORING NETWORKS
The potential effects of air pollution on human health have received much attention in recent years. In the U.S. and other countries, there are extensive large-scale monitoring networks designed to collect data to inform the public of exposure risks to air pollution. A major crit...
Calibration of an electronic nose for poultry farm
NASA Astrophysics Data System (ADS)
Abdullah, A. H.; Shukor, S. A.; Kamis, M. S.; Shakaff, A. Y. M.; Zakaria, A.; Rahim, N. A.; Mamduh, S. M.; Kamarudin, K.; Saad, F. S. A.; Masnan, M. J.; Mustafa, H.
2017-03-01
Malodour from the poultry farms could cause air pollution and therefore potentially dangerous to humans' and animals' health. This issue also poses sustainability risk to the poultry industries due to objections from local community. The aim of this paper is to develop and calibrate a cost effective and efficient electronic nose for poultry farm air monitoring. The instrument main components include sensor chamber, array of specific sensors, microcontroller, signal conditioning circuits and wireless sensor networks. The instrument was calibrated to allow classification of different concentrations of main volatile compounds in the poultry farm malodour. The outcome of the process will also confirm the device's reliability prior to being used for poultry farm malodour assessment. The Multivariate Analysis (HCA and KNN) and Artificial Neural Network (ANN) pattern recognition technique was used to process the acquired data. The results show that the instrument is able to calibrate the samples using ANN classification model with high accuracy. The finding verifies the instrument's performance to be used as an effective poultry farm malodour monitoring.
Sarah Jovan
2009-01-01
Why Are Epiphytic Lichen Communities Important? Lichens are one of the bioindicators used by the Forest Inventory and Analysis (FIA) Program to monitor forest health. To obtain data for use in its Lichen Community Indicator Program, FIA samples a regular network of permanent field plots to determine the composition of epiphytic, i.e., tree dwelling, lichen communities...
Novel Method for Detection of Air Pollution using Cellular Communication Networks
NASA Astrophysics Data System (ADS)
David, N.; Gao, O. H.
2016-12-01
Air pollution can lead to a wide spectrum of severe and chronic health impacts. Conventional tools for monitoring the phenomenon do not provide a sufficient monitoring solution in a global scale since they are, for example, not representative of the larger space or due to limited deployment as a result of practical limitations, such as: acquisition, installation, and ongoing maintenance costs. Near ground temperature inversions are directly identified with air pollution events since they suppress vertical atmospheric movement and trap pollutants near the ground. Wireless telecommunication links that comprise the data transfer infrastructure in cellular communication networks operate at frequencies of tens of GHz and are affected by different atmospheric phenomena. These systems are deployed near ground level across the globe, including in developing countries such as India, countries in Africa, etc. Many cellular providers routinely store data regarding the received signal levels in the network for quality assurance needs. Temperature inversions cause atmospheric layering, and change the refractive index of the air when compared to standard conditions. As a result, the ducts that are formed can operate, in essence, as atmospheric wave guides, and cause interference (signal amplification / attenuation) in the microwaves measured by the wireless network. Thus, this network is in effect, an existing system of environmental sensors for monitoring temperature inversions and the episodes of air pollution identified with them. This work presents the novel idea, and demonstrates it, in operation, over several events of air pollution which were detected by a standard cellular communication network during routine operation. Reference: David, N. and Gao, H.O. Using cellular communication networks to detect air pollution, Environmental Science & Technology, 2016 (accepted).
NASA Astrophysics Data System (ADS)
Ghaderi, A. H.; Darooneh, A. H.
The behavior of nonlinear systems can be analyzed by artificial neural networks. Air temperature change is one example of the nonlinear systems. In this work, a new neural network method is proposed for forecasting maximum air temperature in two cities. In this method, the regular graph concept is used to construct some partially connected neural networks that have regular structures. The learning results of fully connected ANN and networks with proposed method are compared. In some case, the proposed method has the better result than conventional ANN. After specifying the best network, the effect of input pattern numbers on the prediction is studied and the results show that the increase of input patterns has a direct effect on the prediction accuracy.
1990 Environmental monitoring report, Tonopah Test Range, Tonopah, Nevada
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hwang, A.; Phelan, J.; Wolff, T.
1991-05-01
There is no routine radioactive emission from Sandia National Laboratories, Tonopah Test Range (SNL, TTR). However, based on the types of test activities such as air drops, gun firings, ground- launched rockets, air-launched rockets, and other explosive tests, possibilities exist that small amounts of depleted uranium (DU) (as part of weapon components) may be released to the air or to the ground because of unusual circumstances (failures) during testing. Four major monitoring programs were used in 1990 to assess radiological impact on the public. The EPA Air Surveillance Network (ASN) found that the only gamma ({gamma}) emitting radionuclide on themore » prefilters was beryllium-7 ({sup 7}Be), a naturally-occurring spallation product formed by the interaction of cosmic radiation with atmospheric oxygen and nitrogen. The weighted average results were consistent with the area background concentrations. The EPA Thermoluminescent Dosimetry (TLD) Network and Pressurized Ion Chamber (PIC) reported normal results. In the EPA Long-Term Hydrological Monitoring Program (LTHMP), analytical results for tritium ({sup 3}H) in well water were reported and were well below DOE-derived concentration guides (DCGs). In the Reynolds Electrical and Engineering Company (REECo) Drinking Water Sampling Program, analytical results for {sup 3}H, gross alpha ({alpha}), beta ({beta}), and {gamma} scan, strontium-90 ({sup 90}Sr) and plutonium-239 ({sup 239}Pu) were within the EPA's primary drinking water standards. 29 refs., 5 figs., 15 tabs.« less
The U.S. Environmental Protection Agency (U.S. EPA) established the National Dioxin Air Monitoring Network (NDAMN) in June of 1998, and operated it until November of 2004. The objective of NDAMN was to determine background air concentrations of polychlorinated dibenzo-p-dioxins (...
Armstrong, Jenna L; Fitzpatrick, Cole F; Loftus, Christine T; Yost, Michael G; Tchong-French, Maria; Karr, Catherine J
2013-09-01
This research describes the design, deployment, performance, and acceptability of a novel outdoor active air sampler to provide simultaneous measurements of multiple contaminants at timed intervals for the Aggravating Factors of Asthma in Rural Environment (AFARE) study-a longitudinal cohort of 50 children in Yakima Valley, Washington. The sampler was constructed of multiple sampling media connected to individual critical orifices and a rotary vane vacuum pump. It was connected to a timed control valve system to collect 24 hours samples every six days over 18 months. We describe a spatially representative approach with both quantitative and qualitative location criteria to deploy a network of 14 devices at participant residences in a rural region (20 × 60 km). Overall the sampler performed well, as the concurrent mean sample flow rates were within or above the ranges of recommended sampling rates for each exposure metric of interest. Acceptability was high among the study population of Hispanic farmworker participant households. The sampler design may prove useful for future urban and rural community-based studies with aims at collecting multiple contaminant data during specific time periods.
N+3 Small Commercial Efficient and Quiet Transportation for Year 2030-2035
NASA Technical Reports Server (NTRS)
DAngelo, Martin M.; Gallman, John; Johnson, Vicki; Garcia, Elena; Tai, Jimmy; Young, Russell
2010-01-01
This study develops a future scenario that enables convenient point-to-point commercial air travel via a large network of community airports and a new class of small airliners. A network demand and capacity study identifies current and future air travel demands and the capacity of this new network to satisfy these demands. A current technology small commercial airliner is defined to meet the needs of the new network, as a baseline for evaluating the improvement brought about by advanced technologies. Impact of this new mode of travel on the infrastructure and surrounding communities of the small airports in this new N+3 network are also evaluated. Year 2030-2035 small commercial airliner technologies are identified and a trade study conducted to evaluate and select those with the greatest potential for enhancing future air travel and the study metrics. The selected advanced air vehicle concept is assessed against the baseline aircraft, and an advanced, but conventional aircraft, and the study metrics. The key technologies of the selected advanced air vehicle are identified, their impact quantified, and risk assessments and roadmaps defined.
Smoke monitoring network on 2006 Northern California fires
Brenda Belongie; Suraj Ahuja
2007-01-01
Long-duration fire activity during the 2006 northern California fire season presented an excellent opportunity to create a temporary air-quality/smoke-monitoring network in the complex terrain across northwestern California. The network was established through cooperative interagency coordination of Federal officials, the California Air Resources Board (CARB), and...
Air Pollution Source/receptor Relationships in South Coast Air Basin, CA
NASA Astrophysics Data System (ADS)
Gao, Ning
This research project includes the application of some existing receptor models to study the air pollution source/receptor relationships in the South Coast Air Basin (SoCAB) of southern California, the development of a new receptor model and the testing and the modifications of some existing models. These existing receptor models used include principal component factor analysis (PCA), potential source contribution function (PSCF) analysis, Kohonen's neural network combined with Prim's minimal spanning tree (TREE-MAP), and direct trilinear decomposition followed by a matrix reconstruction. The ambient concentration measurements used in this study are a subset of the data collected during the 1987 field exercise of Southern California Air Quality Study (SCAQS). It consists of a number of gaseous and particulate pollutants analyzed from samples collected by SCAQS samplers at eight sampling sites, Anaheim, Azusa, Burbank, Claremont, Downtown Los Angeles, Hawthorne, Long Beach, and Rubidoux. Based on the information of emission inventories, meteorology and ambient concentrations, this receptor modeling study has revealed mechanisms that influence the air quality in SoCAB. Some of the mechanisms affecting the air quality in SoCAB that were revealed during this study include the following aspects. The SO_2 collected at sampling sites is mainly contributed by refineries in the coastal area and the ships equipped with oil-fired boilers off shore. Combustion of fossil fuel by automobiles dominates the emission of NO_{rm x} that is subsequently transformed and collected at sampling sites. Electric power plants also contribute HNO_3 to the sampling sites. A large feedlot in the eastern region of SoCAB has been identified as the major source of NH_3. Possible contributions from other industrial sources such as smelters and incinerators were also revealed. The results of this study also suggest the possibility of DMS (dimethylsulfide) and NH_3 emissions from off-shore sediments that have been contaminated by waste sludge disposal. The study also discovered that non-anthropogenic sources account for the observation of many chemical components being brought to the sampling sites, such as seasalt particles, soil particles, and Cl emission from Mojave Desert. The potential and limitation of the receptor models have been evaluated and some modifications have been made to improve the value of the models. A source apportionment method has been developed based on the application results of the potential source contribution function (PSCF) analysis.
ARM-LBNL-NOAA Flask Sampler for Carbon Cycle Gases
Torn, Margaret
2008-01-15
Data from ccg-flasks are sampled at the ARM SGP site and analyzed by the NOAA Earth System Research Laboratory (ESRL) as part of the NOAA Cooperative Global Air Sampling Network. Surface samples are collected from a 60m tower at the SGP Central Facility, usually once per week on one afternoon. The aircraft samples are collected approximately weekly from a chartered aircraft, and the collection flight path is centered over the tower where the surface samples are collected. Samples are collected by the ARM/LBNL Carbon Project. CO2 flask data contains measurements of CO2 concentration and CO2 stable isotope ratios (13CO2 and C18OO) from flasks collected at the SGP site. The flask samples are collected at 2m, 4m, 25m, and 60m along the 60m tower.
Indoor-Air Microbiome in an Urban Subway Network: Diversity and Dynamics
Leung, Marcus H. Y.; Wilkins, David; Li, Ellen K. T.; Kong, Fred K. F.
2014-01-01
Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on α- and β-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe. PMID:25172855
Insights into Tropospheric Ozone from the INTEX Ozonesonde Network Study (IONS)
NASA Technical Reports Server (NTRS)
Thompson, Anne M.; Witte, J. C.; Kucsera, T. L.; Merrill, J. T.; Morris, G.; Newchurch, M. J.; Oltmans, S. J.; Schmidlin, F. J.; Tarasick, D. J.
2004-01-01
Ozone profile data from soundings integrate models, aircraft and other ground-based measurements for better interpretation of atmospheric chemistry and dynamics. A well-designed network of ozonesonde stations, with consistent sampling, can answer questions not possible with short campaigns or current satellite technology. The SHADOZ (Southern Hemisphere Additional Ozonesondes) project, for example, has led to these findings about tropical ozone: definition of the zonal tropospheric wave-one pattern in equatorial ozone, characterization of the "Atlantic ozone paradox" and establishment of a link between tropical Atlantic and Indian Ocean pollution. Building on the SHADOZ concept, a short-term ozone network was formed in July-August 2004 to coordinate ozonesonde launches during the ICARTT/INTEX/NEAQS (International Consortium on Atmospheric Research on Transport and Transformation)/Intercontinental Transport Experiment/New England Air Quality Study. In IONS (INTEX Ozonesonde Network Study), more than 250 soundings, with daily frequency at half the sites, were launched from eleven North American stations and an oceanographic ship in the Gulf of Maine. Although the goal was to examine pollution influences under stable high-pressure systems and transport associated with "warm conveyor belt" flows, the INTEX study region was dominated by a series of weak frontal system that mixed aged pollution with stratospheric ozone in the middle troposphere. Deconvoluting ozone sources provides new insights into ozone in the transition between mid-latitude and polar air.
Transportation Network Topologies
NASA Technical Reports Server (NTRS)
Holmes, Bruce J.; Scott, John M.
2004-01-01
A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21PstP thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within which strategies for scalability of the topology may be enabled by technologies and policies. In particular, the effects of scalable ICNS concepts are evaluated within this proposed topology. Alternative business models are appearing on the scene as the old centralized hub-and-spoke model reaches the limits of its scalability. These models include growth of point-to-point scheduled air transportation service (e.g., the RJ phenomenon and the 'Southwest Effect'). Another is a new business model for on-demand, widely distributed, air mobility in jet taxi services. The new businesses forming around this vision are targeting personal air mobility to virtually any of the thousands of origins and destinations throughout suburban, rural, and remote communities and regions. Such advancement in air mobility has many implications for requirements for airports, airspace, and consumers. These new paradigms could support scalable alternatives for the expansion of future air mobility to more consumers in more places.
Transportation Network Topologies
NASA Technical Reports Server (NTRS)
Holmes, Bruce J.; Scott, John
2004-01-01
A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21st thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within which strategies for scalability of the topology may be enabled by technologies and policies. In particular, the effects of scalable ICNS concepts are evaluated within this proposed topology. Alternative business models are appearing on the scene as the old centralized hub-and-spoke model reaches the limits of its scalability. These models include growth of point-to-point scheduled air transportation service (e.g., the RJ phenomenon and the Southwest Effect). Another is a new business model for on-demand, widely distributed, air mobility in jet taxi services. The new businesses forming around this vision are targeting personal air mobility to virtually any of the thousands of origins and destinations throughout suburban, rural, and remote communities and regions. Such advancement in air mobility has many implications for requirements for airports, airspace, and consumers. These new paradigms could support scalable alternatives for the expansion of future air mobility to more consumers in more places.
Ongen, Atakan; Ozcan, H Kurtulus; Arayıcı, Semiha
2013-12-15
This paper reports on the calorific value of synthetic gas (syngas) produced by gasification of dewatered sludge derived from treatment of tannery wastewater. Proximate and ultimate analyses of samples were performed. Thermochemical conversion alters the chemical structure of the waste. Dried air was used as a gasification agent at varying flow rates, which allowed the feedstock to be quickly converted into gas by means of different heterogeneous reactions. A lab-scale updraft fixed-bed steel reactor was used for thermochemical conversion of sludge samples. Artificial neural network (ANN) modeling techniques were used to observe variations in the syngas related to operational conditions. Modeled outputs showed that temporal changes of model predictions were in close accordance with real values. Correlation coefficients (r) showed that the ANN used in this study gave results with high sensitivity. Copyright © 2013 Elsevier B.V. All rights reserved.
A novel hybrid approach for estimating total deposition in the United States
NASA Astrophysics Data System (ADS)
Schwede, Donna B.; Lear, Gary G.
2014-08-01
Atmospheric deposition of nitrogen and sulfur causes many deleterious effects on ecosystems including acidification and excess eutrophication. Assessments to support development of strategies to mitigate these effects require spatially and temporally continuous values of nitrogen and sulfur deposition. In the U.S., national monitoring networks exist that provide values of wet and dry deposition at discrete locations. While wet deposition can be interpolated between the monitoring locations, dry deposition cannot. Additionally, monitoring networks do not measure the complete suite of chemicals that contribute to total sulfur and nitrogen deposition. Regional air quality models provide spatially continuous values of deposition of monitored species as well as important unmeasured species. However, air quality modeling values are not generally available for an extended continuous time period. Air quality modeling results may also be biased for some chemical species. We developed a novel approach for estimating dry deposition using data from monitoring networks such as the Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition Program (NADP) Ammonia Monitoring Network (AMoN), and the Southeastern Aerosol Research and Characterization (SEARCH) network and modeled data from the Community Multiscale Air Quality (CMAQ) model. These dry deposition values estimates are then combined with wet deposition values from the NADP National Trends Network (NTN) to develop values of total deposition of sulfur and nitrogen. Data developed using this method are made available via the CASTNET website.
Some applications of remote sensing in atmospheric monitoring programs
NASA Technical Reports Server (NTRS)
Heller, A. N.; Bryson, J. C.; Vasuki, N. C.
1972-01-01
The applications of remote sensing in atmospheric monitoring programs are described. The organization, operations, and functions of an air quality monitoring network at New Castle County, Delaware is discussed. The data obtained by the air quality monitoring network ground stations and the equipment used to obtain atmospheric data are explained. It is concluded that correlation of the information obtained by the network will make it possible to anticipate air pollution problems in the Chesapeake Bay area before a crisis develops.
Lu, Wei-Zhen; Wang, Wen-Jian; Wang, Xie-Kang; Yan, Sui-Hang; Lam, Joseph C
2004-09-01
The forecasting of air pollutant trends has received much attention in recent years. It is an important and popular topic in environmental science, as concerns have been raised about the health impacts caused by unacceptable ambient air pollutant levels. Of greatest concern are metropolitan cities like Hong Kong. In Hong Kong, respirable suspended particulates (RSP), nitrogen oxides (NOx), and nitrogen dioxide (NO2) are major air pollutants due to the dominant usage of diesel fuel by commercial vehicles and buses. Hence, the study of the influence and the trends relating to these pollutants is extremely significant to the public health and the image of the city. The use of neural network techniques to predict trends relating to air pollutants is regarded as a reliable and cost-effective method for the task of prediction. The works reported here involve developing an improved neural network model that combines both the principal component analysis technique and the radial basis function network and forecasts pollutant tendencies based on a recorded database. Compared with general neural network models, the proposed model features a more simple network architecture, a faster training speed, and a more satisfactory prediction performance. The improved model was evaluated with hourly time series of RSP, NOx and NO2 concentrations monitored at the Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000 and proved to be effective. The model developed is a potential tool for forecasting air quality parameters and is superior to traditional neural network methods.
Green, Mark B; Campbell, John L; Yanai, Ruth D; Bailey, Scott W; Bailey, Amey S; Grant, Nicholas; Halm, Ian; Kelsey, Eric P; Rustad, Lindsey E
2018-01-01
The design of a precipitation monitoring network must balance the demand for accurate estimates with the resources needed to build and maintain the network. If there are changes in the objectives of the monitoring or the availability of resources, network designs should be adjusted. At the Hubbard Brook Experimental Forest in New Hampshire, USA, precipitation has been monitored with a network established in 1955 that has grown to 23 gauges distributed across nine small catchments. This high sampling intensity allowed us to simulate reduced sampling schemes and thereby evaluate the effect of decommissioning gauges on the quality of precipitation estimates. We considered all possible scenarios of sampling intensity for the catchments on the south-facing slope (2047 combinations) and the north-facing slope (4095 combinations), from the current scenario with 11 or 12 gauges to only 1 gauge remaining. Gauge scenarios differed by as much as 6.0% from the best estimate (based on all the gauges), depending on the catchment, but 95% of the scenarios gave estimates within 2% of the long-term average annual precipitation. The insensitivity of precipitation estimates and the catchment fluxes that depend on them under many reduced monitoring scenarios allowed us to base our reduction decision on other factors such as technician safety, the time required for monitoring, and co-location with other hydrometeorological measurements (snow, air temperature). At Hubbard Brook, precipitation gauges could be reduced from 23 to 10 with a change of <2% in the long-term precipitation estimates. The decision-making approach illustrated in this case study is applicable to the redesign of monitoring networks when reduction of effort seems warranted.
The U.S. EPA established a National Dioxin Air Monitoring Network (NDAMN) to determine background air concentrations of PCDDs, PCDFs, and cp-PCBs in rural and remote areas of the United States. Background is defined as average ambient air concentrations inferred from long-term a...
NASA Technical Reports Server (NTRS)
Huber, Hans
2006-01-01
Air transport forms complex networks that can be measured in order to understand its structural characteristics and functional properties. Recent models for network growth (i.e., preferential attachment, etc.) remain stochastic and do not seek to understand other network-specific mechanisms that may account for their development in a more microscopic way. Air traffic is made up of many constituent airlines that are either privately or publicly owned and that operate their own networks. They follow more or less similar business policies each. The way these airline networks organize among themselves into distinct traffic distributions reveals complex interaction among them, which in turn can be aggregated into larger (macro-) traffic distributions. Our approach allows for a more deterministic methodology that will assess the impact of airline strategies on the distinct distributions for air traffic, particularly inside Europe. One key question this paper is seeking to answer is whether there are distinct patterns of preferential attachment for given classes of airline networks to distinct types of European airports. Conclusions about the advancing degree of concentration in this industry and the airline operators that accelerate this process can be drawn.
A Hybrid Approach for Estimating Total Deposition in the ...
Atmospheric deposition of nitrogen and sulfur causes many deleterious effects on ecosystems including acidification and excess eutrophication. Assessments to support development of strategies to mitigate these effects require spatially and temporally continuous values of nitrogen and sulfur deposition. In the U.S., national monitoring networks exist that provide values of wet and dry deposition at discrete locations. While wet deposition can be interpolated between the monitoring locations, dry deposition cannot. Additionally, monitoring networks do not measure the complete suite of chemicals that contribute to total sulfur and nitrogen deposition. Regional air quality models provide spatially continuous values of deposition of monitored species as well as important unmeasured species. However, air quality modeling values are not generally available for an extended continuous time period. Air quality modeling results may also be biased for some chemical species. We developed a novel approach for estimating dry deposition using data from monitoring networks such as the Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition Program (NADP) Ammonia Monitoring Network (AMoN), and the Southeastern Aerosol Research and Characterization (SEARCH) network and modeled data from the Community Multiscale Air Quality (CMAQ) model. These dry deposition values estimates are then combined with wet deposition values from the NADP National Trends Networ
A Novel Hybrid Approach for Estimating Total Deposition in ...
Atmospheric deposition of nitrogen and sulfur causes many deleterious effects on ecosystems including acidification and excess eutrophication. Assessments to support development of strategies to mitigate these effects require spatially and temporally continuous values of nitrogen and sulfur deposition. In the U.S., national monitoring networks exist that provide values of wet and dry deposition at discrete locations. While wet deposition can be interpolated between the monitoring locations, dry deposition cannot. Additionally, monitoring networks do not measure the complete suite of chemicals that contribute to total sulfur and nitrogen deposition. Regional air quality models provide spatially continuous values of deposition of monitored species as well as important unmeasured species. However, air quality modeling values are not generally available for an extended continuous time period. Air quality modeling results may also be biased for some chemical species. We developed a novel approach for estimating dry deposition using data from monitoring networks such as the Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition Program (NADP) Ammonia Monitoring Network (AMoN), and the Southeastern Aerosol Research and Characterization (SEARCH) network and modeled data from the Community Multiscale Air Quality (CMAQ) model. These dry deposition values estimates are then combined with wet deposition values from the NADP National Trends Networ
NASA Technical Reports Server (NTRS)
Zhang, Ping; Bounoua, Lahouari; Imhoff, Marc L.; Wolfe, Robert E.; Thome, Kurtis
2014-01-01
The National Land Cover Database (NLCD) Impervious Surface Area (ISA) and MODIS Land Surface Temperature (LST) are used in a spatial analysis to assess the surface-temperature-based urban heat island's (UHIS) signature on LST amplitude over the continental USA and to make comparisons to local air temperatures. Air-temperature-based UHIs (UHIA), calculated using the Global Historical Climatology Network (GHCN) daily air temperatures, are compared with UHIS for urban areas in different biomes during different seasons. NLCD ISA is used to define urban and rural temperatures and to stratify the sampling for LST and air temperatures. We find that the MODIS LST agrees well with observed air temperature during the nighttime, but tends to overestimate it during the daytime, especially during summer and in nonforested areas. The minimum air temperature analyses show that UHIs in forests have an average UHIA of 1 C during the summer. The UHIS, calculated from nighttime LST, has similar magnitude of 1-2 C. By contrast, the LSTs show a midday summer UHIS of 3-4 C for cities in forests, whereas the average summer UHIA calculated from maximum air temperature is close to 0 C. In addition, the LSTs and air temperatures difference between 2006 and 2011 are in agreement, albeit with different magnitude.
Multiphase flow predictions from carbonate pore space images using extracted network models
NASA Astrophysics Data System (ADS)
Al-Kharusi, Anwar S.; Blunt, Martin J.
2008-06-01
A methodology to extract networks from pore space images is used to make predictions of multiphase transport properties for subsurface carbonate samples. The extraction of the network model is based on the computation of the location and sizes of pores and throats to create a topological representation of the void space of three-dimensional (3-D) rock images, using the concept of maximal balls. In this work, we follow a multistaged workflow. We start with a 2-D thin-section image; convert it statistically into a 3-D representation of the pore space; extract a network model from this image; and finally, simulate primary drainage, waterflooding, and secondary drainage flow processes using a pore-scale simulator. We test this workflow for a reservoir carbonate rock. The network-predicted absolute permeability is similar to the core plug measured value and the value computed on the 3-D void space image using the lattice Boltzmann method. The predicted capillary pressure during primary drainage agrees well with a mercury-air experiment on a core sample, indicating that we have an adequate representation of the rock's pore structure. We adjust the contact angles in the network to match the measured waterflood and secondary drainage capillary pressures. We infer a significant degree of contact angle hysteresis. We then predict relative permeabilities for primary drainage, waterflooding, and secondary drainage that agree well with laboratory measured values. This approach can be used to predict multiphase transport properties when wettability and pore structure vary in a reservoir, where experimental data is scant or missing. There are shortfalls to this approach, however. We compare results from three networks, one of which was derived from a section of the rock containing vugs. Our method fails to predict properties reliably when an unrepresentative image is processed to construct the 3-D network model. This occurs when the image volume is not sufficient to represent the geological variations observed in a core plug sample.
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.
Dynamic assessment of exposure to air pollution using mobile phone data.
Dewulf, Bart; Neutens, Tijs; Lefebvre, Wouter; Seynaeve, Gerdy; Vanpoucke, Charlotte; Beckx, Carolien; Van de Weghe, Nico
2016-04-21
Exposure to air pollution can have major health impacts, such as respiratory and cardiovascular diseases. Traditionally, only the air pollution concentration at the home location is taken into account in health impact assessments and epidemiological studies. Neglecting individual travel patterns can lead to a bias in air pollution exposure assessments. In this work, we present a novel approach to calculate the daily exposure to air pollution using mobile phone data of approximately 5 million mobile phone users living in Belgium. At present, this data is collected and stored by telecom operators mainly for management of the mobile network. Yet it represents a major source of information in the study of human mobility. We calculate the exposure to NO2 using two approaches: assuming people stay at home the entire day (traditional static approach), and incorporating individual travel patterns using their location inferred from their use of the mobile phone network (dynamic approach). The mean exposure to NO2 increases with 1.27 μg/m(3) (4.3%) during the week and with 0.12 μg/m(3) (0.4%) during the weekend when incorporating individual travel patterns. During the week, mostly people living in municipalities surrounding larger cities experience the highest increase in NO2 exposure when incorporating their travel patterns, probably because most of them work in these larger cities with higher NO2 concentrations. It is relevant for health impact assessments and epidemiological studies to incorporate individual travel patterns in estimating air pollution exposure. Mobile phone data is a promising data source to determine individual travel patterns, because of the advantages (e.g. low costs, large sample size, passive data collection) compared to travel surveys, GPS, and smartphone data (i.e. data captured by applications on smartphones).
Macey, Gregg P; Breech, Ruth; Chernaik, Mark; Cox, Caroline; Larson, Denny; Thomas, Deb; Carpenter, David O
2014-10-30
Horizontal drilling, hydraulic fracturing, and other drilling and well stimulation technologies are now used widely in the United States and increasingly in other countries. They enable increases in oil and gas production, but there has been inadequate attention to human health impacts. Air quality near oil and gas operations is an underexplored human health concern for five reasons: (1) prior focus on threats to water quality; (2) an evolving understanding of contributions of certain oil and gas production processes to air quality; (3) limited state air quality monitoring networks; (4) significant variability in air emissions and concentrations; and (5) air quality research that misses impacts important to residents. Preliminary research suggests that volatile compounds, including hazardous air pollutants, are of potential concern. This study differs from prior research in its use of a community-based process to identify sampling locations. Through this approach, we determine concentrations of volatile compounds in air near operations that reflect community concerns and point to the need for more fine-grained and frequent monitoring at points along the production life cycle. Grab and passive air samples were collected by trained volunteers at locations identified through systematic observation of industrial operations and air impacts over the course of resident daily routines. A total of 75 volatile organics were measured using EPA Method TO-15 or TO-3 by gas chromatography/mass spectrometry. Formaldehyde levels were determined using UMEx 100 Passive Samplers. Levels of eight volatile chemicals exceeded federal guidelines under several operational circumstances. Benzene, formaldehyde, and hydrogen sulfide were the most common compounds to exceed acute and other health-based risk levels. Air concentrations of potentially dangerous compounds and chemical mixtures are frequently present near oil and gas production sites. Community-based research can provide an important supplement to state air quality monitoring programs.
Journal Article: Atmospheric Measurements of CDDs, CDFs ...
The U.S. EPA established a National Dioxin Air Monitoring Network (NDAMN) to determine background air concentrations of PCDDs, PCDFs, and cp-PCBs in rural and remote areas of the United States. Background is defined as average ambient air concentrations inferred from long-term and multi-year atmospheric measurements at the same locations using identical monitoring and analytical procedures. The rural sites were chosen in order to obtain air concentrations in areas where crops and livestock are grown, and that encompassed a range of geographic locations in terms of latitudinal and longitudinal positions. Remote sites were selected on the basis that they were relatively free of human habitation and >100 km away from human dioxin sources. The locations of sampling sites covered a wide range of climate conditions from tropical sub-humid to sub-Artic climates. The idea behind the sampling configuration was to provide reasonable geographic coverage of the United States limited only by budgetary constraints. Funding was sufficient for the establishment and maintenance of 34 NDAMN stations over a period of 6 years. Results were reported as the toxic equivalent (TEQ) of the mix of PCDDs/PCDFs (TEQ-DF) and the mix of coplanar PCBs (TEQ-PCB). At the studied rural sites the mean annual TEQ-DF for each of the NDAMN sampling years was 10.43, 11.39, 10.40, and 10.47 femtograms per cubic meter (fg/cu. m) for 1999, 2000, 2001, and 2002, respectively.There was no statistical
Assessment of air pollution impacts on vegetation in South Africa
DOE Office of Scientific and Technical Information (OSTI.GOV)
Botha, A.T.
1989-01-01
Field surveys and biomonitoring network experiments were conducted in selected areas in South Africa to assess possible air pollution damage to vegetation. During field surveys, atmospheric fluoride was identified as an important pollutant that damaged vegetation in residential areas north of Cape Town. Gaseous air pollutants, including acid deposition and acidic mist, probably play a major role in the development of characteristic air pollution injury symptoms observed on pine trees in the Eastern Transvaal area. The impact of urban air pollution in the Cape Town area was evaluated by exposing bio-indicator plants in a network of eight biomonitoring network stationsmore » from June 1985 to May 1988. Sensitive Freesia and Gladiolus cultivars were used to biomonitor atmospheric fluoride, while a green bean cultivar was used as a biomonitor of atmospheric sulfur dioxide and ozone. At one location, bio-indicator plants were simultaneously exposed in a biomonitoring network station, open-top chambers, as well as in open plots. The responses of plants grown under these different conditions were compared.« less
BOREAS AFM-5 Level-1 Upper Air Network Data
NASA Technical Reports Server (NTRS)
Barr, Alan; Hrynkiw, Charmaine; Newcomer, Jeffrey A. (Editor); Hall, Forrest G. (Editor); Smith, David E. (Technical Monitor)
2000-01-01
The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-5 team collected and processed data from the numerous radiosonde flights during the project. The goals of the AFM-05 team were to provide large-scale definition of the atmosphere by supplementing the existing Atmospheric Environment Service (AES) aerological network, both temporally and spatially. This data set includes basic upper-air parameters collected from the network of upper-air stations during the 1993, 1994, and 1996 field campaigns over the entire study region. The data are contained in tabular ASCII files. The level-1 upper-air network data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files also are available on a CD-ROM (see document number 20010000884).
Grain Boundary Engineering and Air Oxidation Behavior of Alloy 690
NASA Astrophysics Data System (ADS)
Xu, Peng; Zhao, Liang Y.; Sridharan, Kumar; Allen, Todd R.
Grain boundary engineering (GBE) was performed on nickel-based alloy 690 by thermomechanical processing (TMP) to alter the grain boundary character distribution (GBCD). It was found that 5% and 35% thickness reduction in single and multiple steps followed by solution annealing and water quench yielded a high fraction of special boundaries. The total length fraction of the low ∑ CSL (coincidence site lattice) was as high as 87.2%. The grain boundary network was disrupted after the TMP treatment, and the average grain size calculated after exclusion of special twin boundaries can be as much as 5 times larger than the as-received (AR) sample. The GBE sample showed better oxidation resistance compared to the AR sample during the long term air oxidation. In the cyclic oxidation test, both AR and GBE samples showed a mass gain at the beginning of the test which was then followed by a mass loss. The mass change of GBE samples oscillated after the first couple cycles, while the AR sample became relatively stable. The oxide film most likely consists of duplex structures with one stable layer that was formed inside and one unstable layer that was formed outside. The stable inner layer was the protective layer and prevented alloy 690 from further oxidation.
The Clean Air Status and Trends Network (CASTNet) was established by EPA in response to the requirements of the 1990 Clean Air Act Amendments. To satisfy these requirements CASTNet was designed to assess and report on geographic patterns and long-term, temporal trends in ambient ...
Oblique view to south OvertheHorizon Backscatter Radar Network, Mountain ...
Oblique view to south - Over-the-Horizon Backscatter Radar Network, Mountain Home Air Force Operations Building, On Desert Street at 9th Avenue Mountain Home Air Force Base, Mountain Home, Elmore County, ID
Region 7 States Air Quality Monitoring Plans - Iowa
National Ambient Air Quality Standard (NAAQS) - Iowa, Kansas, Missouri, and Nebraska; Annual Monitoring Network Plans, Five-Year Monitoring Network Assessments, and approval documentation. Each year, states are required to submit an annual monitoring netwo
Region 7 States Air Quality Monitoring Plans - Missouri
National Ambient Air Quality Standard (NAAQS) - Iowa, Kansas, Missouri, and Nebraska; Annual Monitoring Network Plans, Five-Year Monitoring Network Assessments, and approval documentation. Each year, states are required to submit an annual monitoring netwo
Region 7 States Air Quality Monitoring Plans - Nebraska
National Ambient Air Quality Standard (NAAQS) - Iowa, Kansas, Missouri, and Nebraska; Annual Monitoring Network Plans, Five-Year Monitoring Network Assessments, and approval documentation. Each year, states are required to submit an annual monitoring netwo
Region 7 States Air Quality Monitoring Plans - Kansas
National Ambient Air Quality Standard (NAAQS) - Iowa, Kansas, Missouri, and Nebraska; Annual Monitoring Network Plans, Five-Year Monitoring Network Assessments, and approval documentation. Each year, states are required to submit an annual monitoring netwo
Long-term data sets of all-sky and clear-sky downwelling shortwave (SW) radiation, cloud cover fraction, and aerosol optical depth (AOD) were analyzed together with surface concentrations from several networks (e.g., Surface Radiation Budget Network (SURFRAD), Clean Air Status an...
Maldonado, Ivana; Arechavala, Alicia; Guelfand, Liliana; Relloso, Silvia; Garbasz, Claudia
2016-01-01
Urinary tract infections are a frequent ailment in patients in intensive care units. Candida and other yeasts cause 5-12% of these infections. The value of the finding of any yeast is controversial, and there is no consensus about which parameters are adequate for differentiating urinary infections from colonization or contamination. To analyse the epidemiological characteristics of patients with funguria, to determine potential cut-off points in cultures (to distinguish an infection from other conditions), to identify the prevalent yeast species, and to determine the value of a second urine sample. A multicentre study was conducted in intensive care units of 14 hospitals in the Buenos Aires City Mycology Network. The first and second samples of urine from every patient were cultured. The presence of white cells and yeasts in direct examination, colony counts, and the identification of the isolated species, were evaluated. Yeasts grew in 12.2% of the samples. There was no statistical correlation between the number of white cells and the fungal colony-forming units. Eighty five percent of the patients had indwelling catheters. Funguria was not prevalent in women or in patients over the age of 65. Candida albicans, followed by Candida tropicalis, were the most frequently isolated yeasts. Candida parapsilosis and Candida glabrata appeared less frequently. The same species were isolated in 70% of second samples, and in 23% of the cases the second culture was negative. It was not possible to determine a useful cut-off point for colony counts to help in the diagnosis of urinary infections. As in other publications, C. albicans, followed by C. tropicalis, were the most prevalent species. Copyright © 2015 Asociación Española de Micología. Published by Elsevier Espana. All rights reserved.
PRECP: the Department of Energy's program on the nonlinearity of acid precipitation processes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tanner, R.L.; Tichler, J.; Brown, R.
During the period of 1 April to 3 May 1985, staff from Argonne National Laboratory (ANL), Brookhaven National Laboratory (BNL), and Pacific Northwest Laboratory (PNL), participated in a multifaceted, coordinated set of field studies from an aircraft logistical base in Columbus, OH, and a surface precipitation and air chemistry network in the Philadelphia area. The general goals of these activities, conducted within the DOE-sponsored PRocessing of Emissions by Clouds and Precipitation (PRECP) program were to obtain information concerning scavenging ratios and the vertical distribution of cloud and precipitation chemistry for sulfur and nitrogen oxides and oxyacids, and for oxidant speciesmore » in the vicinity of precipitating and nonprecipitating clouds. Profiling of pollutant concentrations and phase distributions, and studies of scavenging processes were accomplished principally by airborne measurements of aerosol and gaseous species in pre-cloud and below-cloud air and of aqueous-phase species in clouds and precipitation, accompanied by documentation of meteorological and cloud physics parameters in the sampled regimes. Studies in the Midwest utilized only limited surface precipitation collection and chemical measurements, whereas a more extensive ground precipitation network was deployed in the Philadelphia area studies together with surface air chemistry measurements at a single nonurban site.« less
Contact lines on silicone elastomers promote contamination
NASA Astrophysics Data System (ADS)
Hourlier-Fargette, Aurelie; Antkowiak, Arnaud; Neukirch, Sebastien
2017-11-01
Silicone elastomers are used in contact with aqueous liquids in a large range of applications. Due to numerous advantages such as its flexibility, optical transparency, or gas permeability, polydimethylsiloxane is widely spread in rapid prototyping for microfluidics or elastocapillarity experiments. However, silicone elastomers are known to contain a small fraction of uncrosslinked low-molecular-weight oligomers, the effects of which are not completely understood. We show that in various setups involving an air-water-silicone elastomer contact line, a capillarity-induced extraction of uncrosslinked oligomers occurs, leading to a contamination of water-air interfaces. We investigate the case of a static air-water-PDMS contact line, before focusing on moving contact lines. A water droplet sliding down on a PDMS inclined plane or an air bubble rising on an immersed PDMS plane exhibits two successive speed regimes: the second regime is reached only when a monolayer of oligomers completely covers the water-air interface. These experiments involve processes occurring at the polymer network scale that have significant macroscopic consequences, and therefore provide a simple test to evaluate the presence of uncrosslinked oligomers in an elastomer sample.
Atmospheric CO2 Records from Sites in the Umweltbundesamt (UBA) Air Sampling Network (1972 - 1997)
Fricke, W. [Umweltbundesamt, Offenbach/Main, Germany; Wallasch, M. [Umweltbundesamt, Offenbach/Main, Germany; Uhse, Karin [Umweltbundesamt, Offenbach/Main, Germany; Schmidt, Martina [University of Heidelberg, Heidelberg, Germany; Levin, Ingeborg [University of Heidelberg, Heidelberg, Germany
1998-01-01
Air samples for the purpose of monitoring atmospheric CO2 were collected from five sites in the UBA air sampling network. Annual atmospheric CO2 concentrations at Brotjacklriegel rose from 331.63 parts per million by volume (ppmv) in 1972 to 353.12 ppmv in 1988. Because of the site's forest location, the monthly atmospheric CO2 record from Brotjacklriegel exhibits very large seasonal amplitude. This amplitude reached almost 40 ppmv in 1985. Minimum mixing ratios are recorded at Brotjacklriegel during July-September; maximum values, during November-March. CO2 concentrations at Deuselbach rose from 340.82 parts per million by volume (ppmv) in 1972 to 363.76 ppmv in 1989. The monthly atmospheric CO2 record from Deuselbach is influenced by local agricultural activities and photosynthetic depletion but does not exhibit the large seasonal amplitude observed at other UBA monitoring sites. Minimum monthly atmospheric CO2 mixing ratios at Deuselbach are typically observed in August but may appear as early as June. Maximum values are seen in the record for November-March. Atmospheric CO2 concentrations at Schauinsland rose from ~328 parts per million by volume (ppmv) in 1972 to ~365 ppmv in 1997. This represents a growth rate of approximately 1.5 ppmv per year. The Schauinsland site is considered the least contaminated of the UBA sites. CO2 concentrations at Waldhof rose from 346.82 parts per million by volume (ppmv) in 1972 to 372.09 ppmv in 1993. The Waldhof site is subject to pollution sources; consequently, the monthly atmospheric CO2 record exhibits a large seasonal amplitude. Atmospheric CO2 concentrations at Westerland rose from ~329 parts per million by volume (ppmv) in 1973 to ~364 ppmv in 1997. The atmospheric CO2 record from Westerland shows a seasonal pattern similar to other UBA sites; minimum values are recorded during July-September; maximum mixing ratios during November-March.
A Novel Biobjective Risk-Based Model for Stochastic Air Traffic Network Flow Optimization Problem.
Cai, Kaiquan; Jia, Yaoguang; Zhu, Yanbo; Xiao, Mingming
2015-01-01
Network-wide air traffic flow management (ATFM) is an effective way to alleviate demand-capacity imbalances globally and thereafter reduce airspace congestion and flight delays. The conventional ATFM models assume the capacities of airports or airspace sectors are all predetermined. However, the capacity uncertainties due to the dynamics of convective weather may make the deterministic ATFM measures impractical. This paper investigates the stochastic air traffic network flow optimization (SATNFO) problem, which is formulated as a weighted biobjective 0-1 integer programming model. In order to evaluate the effect of capacity uncertainties on ATFM, the operational risk is modeled via probabilistic risk assessment and introduced as an extra objective in SATNFO problem. Computation experiments using real-world air traffic network data associated with simulated weather data show that presented model has far less constraints compared to stochastic model with nonanticipative constraints, which means our proposed model reduces the computation complexity.
Jeong, Seongmin; Cho, Hyunmin; Han, Seonggeun; Won, Phillip; Lee, Habeom; Hong, Sukjoon; Yeo, Junyeob; Kwon, Jinhyeong; Ko, Seung Hwan
2017-07-12
Air quality has become a major public health issue in Asia including China, Korea, and India. Particulate matters are the major concern in air quality. We present the first environmental application demonstration of Ag nanowire percolation network for a novel, electrical type transparent, reusable, and active PM2.5 air filter although the Ag nanowire percolation network has been studied as a very promising transparent conductor in optoelectronics. Compared with previous particulate matter air filter study using relatively weaker short-range intermolecular force in polar polymeric nanofiber, Ag nanowire percolation network filters use stronger long-range electrostatic force to capture PM2.5, and they are highly efficient (>99.99%), transparent, working on an active mode, low power consumption, antibacterial, and reusable after simple washing. The proposed new particulate matter filter can be applied for a highly efficient, reusable, active and energy efficient filter for wearable electronics application.
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.
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.
Neural network and its application to CT imaging
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nikravesh, M.; Kovscek, A.R.; Patzek, T.W.
We present an integrated approach to imaging the progress of air displacement by spontaneous imbibition of oil into sandstone. We combine Computerized Tomography (CT) scanning and neural network image processing. The main aspects of our approach are (I) visualization of the distribution of oil and air saturation by CT, (II) interpretation of CT scans using neural networks, and (III) reconstruction of 3-D images of oil saturation from the CT scans with a neural network model. Excellent agreement between the actual images and the neural network predictions is found.
a Web Api and Web Application Development for Dissemination of Air Quality Information
NASA Astrophysics Data System (ADS)
Şahin, K.; Işıkdağ, U.
2017-11-01
Various studies have been carried out since 2005 under the leadership of Ministry of Environment and Urbanism of Turkey, in order to observe the quality of air in Turkey, to develop new policies and to develop a sustainable air quality management strategy. For this reason, a national air quality monitoring network has been developed providing air quality indices. By this network, the quality of the air has been continuously monitored and an important information system has been constructed in order to take precautions for preventing a dangerous situation. The biggest handicap in the network is the data access problem for instant and time series data acquisition and processing because of its proprietary structure. Currently, there is no service offered by the current air quality monitoring system for exchanging information with third party applications. Within the context of this work, a web service has been developed to enable location based querying of the current/past air quality data in Turkey. This web service is equipped with up-todate and widely preferred technologies. In other words, an architecture is chosen in which applications can easily integrate. In the second phase of the study, a web-based application was developed to test the developed web service and this testing application can perform location based acquisition of air-quality data. This makes it possible to easily carry out operations such as screening and examination of the area in the given time-frame which cannot be done with the national monitoring network.
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.
Flight control with adaptive critic neural network
NASA Astrophysics Data System (ADS)
Han, Dongchen
2001-10-01
In this dissertation, the adaptive critic neural network technique is applied to solve complex nonlinear system control problems. Based on dynamic programming, the adaptive critic neural network can embed the optimal solution into a neural network. Though trained off-line, the neural network forms a real-time feedback controller. Because of its general interpolation properties, the neurocontroller has inherit robustness. The problems solved here are an agile missile control for U.S. Air Force and a midcourse guidance law for U.S. Navy. In the first three papers, the neural network was used to control an air-to-air agile missile to implement a minimum-time heading-reverse in a vertical plane corresponding to following conditions: a system without constraint, a system with control inequality constraint, and a system with state inequality constraint. While the agile missile is a one-dimensional problem, the midcourse guidance law is the first test-bed for multiple-dimensional problem. In the fourth paper, the neurocontroller is synthesized to guide a surface-to-air missile to a fixed final condition, and to a flexible final condition from a variable initial condition. In order to evaluate the adaptive critic neural network approach, the numerical solutions for these cases are also obtained by solving two-point boundary value problem with a shooting method. All of the results showed that the adaptive critic neural network could solve complex nonlinear system control problems.
Federal Register 2010, 2011, 2012, 2013, 2014
2011-05-31
... also claims that MSS networks provide the only means to create a next generation air traffic management..., articulated their plans to offer high-speed data services, especially in connection with terrestrial networks... claimed that MSS networks provide the only means to create a next generation air traffic management (ATM...
Artificial neural networks as a useful tool to predict the risk level of Betula pollen in the air
NASA Astrophysics Data System (ADS)
Castellano-Méndez, M.; Aira, M. J.; Iglesias, I.; Jato, V.; González-Manteiga, W.
2005-05-01
An increasing percentage of the European population suffers from allergies to pollen. The study of the evolution of air pollen concentration supplies prior knowledge of the levels of pollen in the air, which can be useful for the prevention and treatment of allergic symptoms, and the management of medical resources. The symptoms of Betula pollinosis can be associated with certain levels of pollen in the air. The aim of this study was to predict the risk of the concentration of pollen exceeding a given level, using previous pollen and meteorological information, by applying neural network techniques. Neural networks are a widespread statistical tool useful for the study of problems associated with complex or poorly understood phenomena. The binary response variable associated with each level requires a careful selection of the neural network and the error function associated with the learning algorithm used during the training phase. The performance of the neural network with the validation set showed that the risk of the pollen level exceeding a certain threshold can be successfully forecasted using artificial neural networks. This prediction tool may be implemented to create an automatic system that forecasts the risk of suffering allergic symptoms.
Adams, Matthew D; Kanaroglou, Pavlos S
2016-03-01
Air pollution poses health concerns at the global scale. The challenge of managing air pollution is significant because of the many air pollutants, insufficient funds for monitoring and abatement programs, and political and social challenges in defining policy to limit emissions. Some governments provide citizens with air pollution health risk information to allow them to limit their exposure. However, many regions still have insufficient air pollution monitoring networks to provide real-time mapping. Where available, these risk mapping systems either provide absolute concentration data or the concentrations are used to derive an Air Quality Index, which provides the air pollution risk for a mix of air pollutants with a single value. When risk information is presented as a single value for an entire region it does not inform on the spatial variation within the region. Without an understanding of the local variation residents can only make a partially informed decision when choosing daily activities. The single value is typically provided because of a limited number of active monitoring units in the area. In our work, we overcome this issue by leveraging mobile air pollution monitoring techniques, meteorological information and land use information to map real-time air pollution health risks. We propose an approach that can provide improved health risk information to the public by applying neural network models within a framework that is inspired by land use regression. Mobile air pollution monitoring campaigns were conducted across Hamilton from 2005 to 2013. These mobile air pollution data were modelled with a number of predictor variables that included information on the surrounding land use characteristics, the meteorological conditions, air pollution concentrations from fixed location monitors, and traffic information during the time of collection. Fine particulate matter and nitrogen dioxide were both modelled. During the model fitting process we reserved twenty percent of the data to validate the predictions. The models' performances were measured with a coefficient of determination at 0.78 and 0.34 for PM2.5 and NO2, respectively. We apply a relative importance measure to identify the importance of each variable in the neural network to partially overcome the black box issues of neural network models. Copyright © 2015 Elsevier Ltd. All rights reserved.
Indoor-air microbiome in an urban subway network: diversity and dynamics.
Leung, Marcus H Y; Wilkins, David; Li, Ellen K T; Kong, Fred K F; Lee, Patrick K H
2014-11-01
Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on α- and β-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe. Copyright © 2014, American Society for Microbiology. All Rights Reserved.
Development and Validation of the Air Force Cyber Intruder Alert Testbed (CIAT)
2016-07-27
Validation of the Air Force Cyber Intruder Alert Testbed (CIAT) 5a. CONTRACT NUMBER FA8650-16-C-6722 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...network analysts. Therefore, a new cyber STE focused on network analysts called the Air Force Cyber Intruder Alert Testbed (CIAT) was developed. This...Prescribed by ANSI Std. Z39-18 Development and Validation of the Air Force Cyber Intruder Alert Testbed (CIAT) Gregory Funke, Gregory Dye, Brett Borghetti
NASA Astrophysics Data System (ADS)
Kotegawa, Tatsuya
Complexity in the Air Transportation System (ATS) arises from the intermingling of many independent physical resources, operational paradigms, and stakeholder interests, as well as the dynamic variation of these interactions over time. Currently, trade-offs and cost benefit analyses of new ATS concepts are carried out on system-wide evaluation simulations driven by air traffic forecasts that assume fixed airline routes. However, this does not well reflect reality as airlines regularly add and remove routes. A airline service route network evolution model that projects route addition and removal was created and combined with state-of-the-art air traffic forecast methods to better reflect the dynamic properties of the ATS in system-wide simulations. Guided by a system-of-systems framework, network theory metrics and machine learning algorithms were applied to develop the route network evolution models based on patterns extracted from historical data. Constructing the route addition section of the model posed the greatest challenge due to the large pool of new link candidates compared to the actual number of routes historically added to the network. Of the models explored, algorithms based on logistic regression, random forests, and support vector machines showed best route addition and removal forecast accuracies at approximately 20% and 40%, respectively, when validated with historical data. The combination of network evolution models and a system-wide evaluation tool quantified the impact of airline route network evolution on air traffic delay. The expected delay minutes when considering network evolution increased approximately 5% for a forecasted schedule on 3/19/2020. Performance trade-off studies between several airline route network topologies from the perspectives of passenger travel efficiency, fuel burn, and robustness were also conducted to provide bounds that could serve as targets for ATS transformation efforts. The series of analysis revealed that high robustness is achievable only in exchange of lower passenger travel and fuel burn efficiency. However, increase in the network density can mitigate this trade-off.
A Framework for Dimensioning VDL-2 Air-Ground Networks
NASA Technical Reports Server (NTRS)
Ribeiro, Leila Z.; Monticone, Leone C.; Snow, Richard E.; Box, Frank; Apaza, Rafel; Bretmersky, Steven
2014-01-01
This paper describes a framework developed at MITRE for dimensioning a Very High Frequency (VHF) Digital Link Mode 2 (VDL-2) Air-to-Ground network. This framework was developed to support the FAA's Data Communications (Data Comm) program by providing estimates of expected capacity required for the air-ground network services that will support Controller-Pilot-Data-Link Communications (CPDLC), as well as the spectrum needed to operate the system at required levels of performance. The Data Comm program is part of the FAA's NextGen initiative to implement advanced communication capabilities in the National Airspace System (NAS). The first component of the framework is the radio-frequency (RF) coverage design for the network ground stations. Then we proceed to describe the approach used to assess the aircraft geographical distribution and the data traffic demand expected in the network. The next step is the resource allocation utilizing optimization algorithms developed in MITRE's Spectrum ProspectorTM tool to propose frequency assignment solutions, and a NASA-developed VDL-2 tool to perform simulations and determine whether a proposed plan meets the desired performance requirements. The framework presented is capable of providing quantitative estimates of multiple variables related to the air-ground network, in order to satisfy established coverage, capacity and latency performance requirements. Outputs include: coverage provided at different altitudes; data capacity required in the network, aggregated or on a per ground station basis; spectrum (pool of frequencies) needed for the system to meet a target performance; optimized frequency plan for a given scenario; expected performance given spectrum available; and, estimates of throughput distributions for a given scenario. We conclude with a discussion aimed at providing insight into the tradeoffs and challenges identified with respect to radio resource management for VDL-2 air-ground networks.
Multi-load Groups Coordinated Load Control Strategy Considering Power Network Constraints
NASA Astrophysics Data System (ADS)
Liu, Meng; Zhao, Binchao; Wang, Jun; Zhang, Guohui; Wang, Xin
2017-05-01
Loads with energy storage property can actively participate in power balance for power systems, this paper takes air conditioner as a controllable load example, proposing a multi-load groups coordinated load control strategy considering power network constraints. Firstly, two load control modes considering recovery of load diversity are designed, blocking power oscillation of aggregated air conditioners. As the same time, air conditioner temperature setpoint recovery control strategy is presented to avoid power recovery peak. Considering inherent characteristics of two load control modes, an coordinated load control mode is designed by combining the both. Basing on this, a multi-load groups coordinated load control strategy is proposed. During the implementing of load control, power network constraints should be satisfied. An indice which can reflect the security of power system operating is defined. By minimizing its value through optimization, the change of air conditioning loads’ aggregated power on each load bus can be calculated. Simulations are conducted on an air conditioners group and New England 10-generator 39-bus system, verifying the effectiveness of the proposed multi-load groups coordinated load control strategy considering power network constraints.
NASA Astrophysics Data System (ADS)
Ratola, N.; Jiménez-Guerrero, P.
2015-09-01
Biomonitoring data available on levels of atmospheric polycyclic aromatic hydrocarbons (PAHs) in pine needles from the Iberian Peninsula was used to estimate air concentrations of benzo[a]pyrene (BaP) and, at the same time, fuelled the comparison with chemistry transport model representations. Simulations with the modelling system WRF + CHIMERE were validated against data from the European Monitoring and Evaluation Programme (EMEP) air sampling network and using modelled atmospheric concentrations as a consistent reference in order to compare the performance of vegetation-to-air estimating methods. A spatial and temporal resolution of 9 km and 1 h was implemented. The field-based database relied on a pine needles sampling scheme comprising 33 sites in Portugal and 37 sites in Spain complemented with the BaP measurements available from the EMEP sites. The ability of pine needles to act as biomonitoring markers for the atmospheric concentrations of BaP was estimated converting the levels obtained in pine needles into air concentrations by six different approaches, one of them presenting realistic concentrations when compared to the modelled atmospheric values. The justification for this study is the gaps still existing in the knowledge of the life cycles of semi-volatile organic compounds (SVOCs), particularly the partition processes between air and vegetation. The strategy followed in this work allows the definition of the transport patterns (e.g. dispersion) established by the model for atmospheric concentrations and the estimated values in vegetation.
NASA Astrophysics Data System (ADS)
Gromov, Sergey A.; Trifonova-Yakovleva, Alisa; Gromov, Sergey S.
2016-04-01
Recent changes in economic development tendencies and environmental protection policies in the East Asian countries raise hopes for improvement of regional air quality in this vast region populated by more than 3 billion people. To recognize anticipated changes in atmospheric pollutants levels, deposition rates and impact on the environment, the Acid Deposition Monitoring Network in East Asia (EANET, http://www.eanet.asia/) is regularly operating region-wide since 2000 in 13 countries. The network provides continuous monitoring data on the air quality and precipitation (including gas-phase and particulate chemistry) at 55 monitoring sites, including 20 remote and 14 rural sites. Observation of soil and inland water environments are performed at more than 30 monitoring sites [1]. In this study we focus on 1) the data quality assessment and preparation and 2) analysis of temporal trends of compositions observed at selected 26 non-urban EANET stations. Speciation includes gas-phase (SO2, HNO3, HCl, NH3) and particulate matter (SO42-, NO3-, Cl-, NH4+, Na+, K+, Mg2+, Ca2+) abundances analysed in samples collected using filterpack technique with sampling duration/frequency of one-two weeks. Data quality assessment (distribution test and manual inspection) allowed us to remove/repair random and operator errors. Wrong sample timing was found for 0.37% (severe) and 34% (mild inconsistency) of the total of 7630 samples regarded. Erroneous data flagging (e.g. missing or below the detection limit) was repaired for 9.3%, respectively. Some 1.8% of severely affected data were corrected (where possible) or removed. Thus refined 15-year dataset is made available for the scientific community. For convenience, we also provide data in netCDF format (per station or in an assembly). Based on this refined dataset, we performed trend analysis using several statistical approaches including quantile regression which provides robust results against outliers and better understanding of trend origins. Our calculations indicate that about half of the median trends at EANET stations are significant, derived either for the entire observational period or for a given season, however not for the same species. The proportions of decreasing and increasing trends are comparable. The latter is the case for SO2, HCl, Cl-, NO3 (except for Russia), while marked decrease in K+ abundances is prevailing at all stations. Most unsystematic trends are seen for nitrogenated compounds, particularly HNO3, which calls for deeper data quality analysis. Interestingly, about the same statistic (half of significant trends) is obtained for the upper (0.9) quantile of the dataset, suggesting that trends pertain to the upper part of the data distribution usually linked to emission dynamics (i.e. bearing winter/spring compositions). We further apply an ad hoc cluster analysis to infer spatial patterns and colocation of the trends across the East Asian region. Finally, we provide a brief comparison of results with an evaluation of changes in major acidic compounds over EMEP region for the 1990-2012 provided by EMEP in its trend assessment for the UN ECE CLRTAP earlier this year [2]. References: 1. EANET: Data Report 2014. Network Center for EANET (ACAP), November 2015, 314 p. (http://www.eanet.asia/product/datarep/datarep14/datarep14.pdf) 2. EMEP: Air Pollution Trends in the EMEP region between 1990 and 2012. WMO/EMEP TFMM Trend Assessment Report. UN ECE Convention on LRTAP, 2016, 54 p.
Urban air pollution in megacities of the world
NASA Astrophysics Data System (ADS)
Mage, David; Ozolins, Guntis; Peterson, Peter; Webster, Anthony; Orthofer, Rudi; Vandeweerd, Veerle; Gwynne, Michael
Urban air pollution is a major environmental problem in the developing countries of the world. WHO and UNEP created an air pollution monitoring network as part of the Global Environment Monitoring System. This network now covers over 50 cities in 35 developing and developed countries throughout the world. The analyses of the data reported by the network over the past 15-20 yr indicate that the lessons of the prior experiences in the developed countries (U.S.A., U.K.) have not been learned. A study of air pollution in 20 of the 24 megacities of the world (over 10 million people by year 2000) shows that ambient air pollution concentrations are at levels where serious health effects are reported. The expected rise of population in the next century, mainly in the developing countries with a lack of capital for air pollution control, means that there is a great potential that conditions will worsen in many more cities that will reach megacity status. This paper maps the potential for air pollution that cities will experience in the future unless control strategies are developed and implemented during the next several decades.
Lu, Wei-Zhen; Wang, Wen-Jian
2005-04-01
Monitoring and forecasting of air quality parameters are popular and important topics of atmospheric and environmental research today due to the health impact caused by exposing to air pollutants existing in urban air. The accurate models for air pollutant prediction are needed because such models would allow forecasting and diagnosing potential compliance or non-compliance in both short- and long-term aspects. Artificial neural networks (ANN) are regarded as reliable and cost-effective method to achieve such tasks and have produced some promising results to date. Although ANN has addressed more attentions to environmental researchers, its inherent drawbacks, e.g., local minima, over-fitting training, poor generalization performance, determination of the appropriate network architecture, etc., impede the practical application of ANN. Support vector machine (SVM), a novel type of learning machine based on statistical learning theory, can be used for regression and time series prediction and have been reported to perform well by some promising results. The work presented in this paper aims to examine the feasibility of applying SVM to predict air pollutant levels in advancing time series based on the monitored air pollutant database in Hong Kong downtown area. At the same time, the functional characteristics of SVM are investigated in the study. The experimental comparisons between the SVM model and the classical radial basis function (RBF) network demonstrate that the SVM is superior to the conventional RBF network in predicting air quality parameters with different time series and of better generalization performance than the RBF model.
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.
Forecasting PM10 in metropolitan areas: Efficacy of neural networks.
Fernando, H J S; Mammarella, M C; Grandoni, G; Fedele, P; Di Marco, R; Dimitrova, R; Hyde, P
2012-04-01
Deterministic photochemical air quality models are commonly used for regulatory management and planning of urban airsheds. These models are complex, computer intensive, and hence are prohibitively expensive for routine air quality predictions. Stochastic methods are becoming increasingly popular as an alternative, which relegate decision making to artificial intelligence based on Neural Networks that are made of artificial neurons or 'nodes' capable of 'learning through training' via historic data. A Neural Network was used to predict particulate matter concentration at a regulatory monitoring site in Phoenix, Arizona; its development, efficacy as a predictive tool and performance vis-à-vis a commonly used regulatory photochemical model are described in this paper. It is concluded that Neural Networks are much easier, quicker and economical to implement without compromising the accuracy of predictions. Neural Networks can be used to develop rapid air quality warning systems based on a network of automated monitoring stations. Copyright © 2011 Elsevier Ltd. All rights reserved.
U.S. EPA's National Dioxin Air Monitoring Network: Analytical Issues
The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric chlorinated dibenzo-p-dioxins (CDDs), furans (CDFs), and coplanar polychlorinated biphenyls (PCBs) at rural and non-impacted locatio...
[Performance evaluation of Rapid™ Yeast Plus (Remel) system from two different culture media].
Romeo, Ana M; Snitman, Gabriela V; Marucco, Andrea P; Ponce, Graciela Del V; Cataldi, Silvana P; Guelfand, Liliana I; Arechavala, Alicia
Within the genus Candida, Candida albicans is the most commonly isolated species from clinical samples. Due to the emergence of other species which can show a higher index of antifungal resistance, a fast identification of these species is necessary. The aim of this work was to evaluate the performance of the RapID Yeast Plus system from two different subculture media formulations: Sabouraud dextrose agar adjusted by Emmons (the medium is indicated in the equipment insert) and Sabouraud glucose agar, which is the most frequently used in Buenos Aires City laboratories. One hundred and sixty-six clinical sample strains coming from different hospitals belonging to the Mycology Network of Buenos Aires City were studied. From the obtained results, we conclude that the conditions and culture medium indicated by the manufacturer should be followed. Copyright © 2016 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.
NASA Astrophysics Data System (ADS)
Pahlavani, Parham; Sheikhian, Hossein; Bigdeli, Behnaz
2017-10-01
Air pollution assessment is an imperative part of megacities planning and control. Hence, a new comprehensive approach for air pollution monitoring and assessment was introduced in this research. It comprises of three main sections: optimizing the existing air pollutant monitoring network, locating new stations to complete the coverage of the existing network, and finally, generating an air pollution map. In the first section, Shannon information index was used to find less informative stations to be candidate for removal. Then, a methodology was proposed to determine the areas which are not sufficiently covered by the current network. These areas are candidates for establishing new monitoring stations. The current air pollution monitoring network of Tehran was used as a case study, where the air pollution issue has been worsened due to the huge population, considerable commuters' absorption and topographic barriers. In this regard, O3, NO, NO2, NOx, CO, PM10, and PM2.5 were considered as the main pollutants of Tehran. Optimization step concluded that all the 16 active monitoring stations should be preserved. Analysis showed that about 35% of the Tehran's area is not properly covered by monitoring stations and about 30% of the area needs additional stations. The winter period in Tehran always faces the most severe air pollution in the year. Hence, to produce the air pollution map of Tehran, three-month of winter measurements of the mentioned pollutants, repeated for five years in the same period, were selected and extended to the entire area using the kriging method. Experts specified the contribution of each pollutant in overall air pollution. Experts' rankings aggregated by a fuzzy-overlay process. Resulted maps characterized the study area with crucial air pollution situation. According to the maps, more than 45% of the city area faced high pollution in the study period, while only less than 10% of the area showed low pollution. This situation confirms the need for effective plans to mitigate the severity of the problem. In addition, an effort made to investigate the rationality of the acquired air pollution map respect to the urban, cultural, and environmental characteristics of Tehran, which also confirmed the results.
NETWORK DESIGN FOR OZONE MONITORING
The potential effects of air pollution on human health have received much attention in recent years. In the U.S. and other countries, there are extensive large-scale monitoring networks designed to collect data to inform the public of exposure risks from air pollution. A major cr...
2014-03-22
consideration for enlisted airmen, has largely become a non factor due to over-inflated scores, with other factors such as specialty knowledge test scores, time...appraisal. Secondly, an Artificial Neural Network (ANN) classifier will be applied to the large sample data to confirm that the values solicited to...jobs, employees make themselves vulnerable to the organization when they expend effort. If extra effort is expended to reduce errors or defects, or
An Evaluation of a Networked Radiation Detection System
2010-03-01
conducted at the site using RAT (Cooper, 2008a): “Beginning in the 1940’ s , widespread mining and milling of uranium ore for national defense and energy...contamination…” in order to determine future sampling points (Cooper, 2007). 2. 4 May 2005, conducted mobile air monitoring during the removal of 30...provide site-wide estimates of emissions…” at Warren (OH) Recycling Inc.®’ s 85 acre landfill emitting hydrogen sulfide (H2S) (Cooper, 2007). 4. 7 July
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rood, Arthur S.; Sondrup, A. Jeffrey; Ritter, Paul D.
A methodology to quantify the performance of an air monitoring network in terms of frequency of detection has been developed. The methodology utilizes an atmospheric transport model to predict air concentrations of radionuclides at the samplers for a given release time and duration. Frequency of detection is defined as the fraction of “events” that result in a detection at either a single sampler or network of samplers. An “event” is defined as a release of finite duration that begins on a given day and hour of the year from a facility with the potential to emit airborne radionuclides. Another metricmore » of interest is the network intensity, which is defined as the fraction of samplers in the network that have a positive detection for a given event. The frequency of detection methodology allows for evaluation of short-term releases that include effects of short-term variability in meteorological conditions. The methodology was tested using the U.S. Department of Energy Idaho National Laboratory (INL) Site ambient air monitoring network consisting of 37 low-volume air samplers in 31 different locations covering a 17,630 km 2 region. Releases from six major INL facilities distributed over an area of 1,435 km 2 were modeled and included three stack sources and eight ground-level sources. A Lagrangian Puff air dispersion model (CALPUFF) was used to model atmospheric transport. The model was validated using historical 125Sb releases and measurements. Relevant one-week release quantities from each emission source were calculated based on a dose of 1.9 × 10 –4 mSv at a public receptor (0.01 mSv assuming release persists over a year). Important radionuclides considered include 241Am, 137Cs, 238Pu, 239Pu, 90Sr, and tritium. Results show the detection frequency is over 97.5% for the entire network considering all sources and radionuclides. Network intensities ranged from 3.75% to 62.7%. Evaluation of individual samplers indicated some samplers were poorly situated and add little to the overall effectiveness of the network. As a result, using the frequency of detection methods, optimum sampler placements were simulated that could substantially improve the performance and efficiency of the network.« less
Rood, Arthur S.; Sondrup, A. Jeffrey; Ritter, Paul D.
2016-04-01
A methodology to quantify the performance of an air monitoring network in terms of frequency of detection has been developed. The methodology utilizes an atmospheric transport model to predict air concentrations of radionuclides at the samplers for a given release time and duration. Frequency of detection is defined as the fraction of “events” that result in a detection at either a single sampler or network of samplers. An “event” is defined as a release of finite duration that begins on a given day and hour of the year from a facility with the potential to emit airborne radionuclides. Another metricmore » of interest is the network intensity, which is defined as the fraction of samplers in the network that have a positive detection for a given event. The frequency of detection methodology allows for evaluation of short-term releases that include effects of short-term variability in meteorological conditions. The methodology was tested using the U.S. Department of Energy Idaho National Laboratory (INL) Site ambient air monitoring network consisting of 37 low-volume air samplers in 31 different locations covering a 17,630 km 2 region. Releases from six major INL facilities distributed over an area of 1,435 km 2 were modeled and included three stack sources and eight ground-level sources. A Lagrangian Puff air dispersion model (CALPUFF) was used to model atmospheric transport. The model was validated using historical 125Sb releases and measurements. Relevant one-week release quantities from each emission source were calculated based on a dose of 1.9 × 10 –4 mSv at a public receptor (0.01 mSv assuming release persists over a year). Important radionuclides considered include 241Am, 137Cs, 238Pu, 239Pu, 90Sr, and tritium. Results show the detection frequency is over 97.5% for the entire network considering all sources and radionuclides. Network intensities ranged from 3.75% to 62.7%. Evaluation of individual samplers indicated some samplers were poorly situated and add little to the overall effectiveness of the network. As a result, using the frequency of detection methods, optimum sampler placements were simulated that could substantially improve the performance and efficiency of the network.« less
From trees to forest: relational complexity network and workload of air traffic controllers.
Zhang, Jingyu; Yang, Jiazhong; Wu, Changxu
2015-01-01
In this paper, we propose a relational complexity (RC) network framework based on RC metric and network theory to model controllers' workload in conflict detection and resolution. We suggest that, at the sector level, air traffic showing a centralised network pattern can provide cognitive benefits in visual search and resolution decision which will in turn result in lower workload. We found that the network centralisation index can account for more variance in predicting perceived workload and task completion time in both a static conflict detection task (Study 1) and a dynamic one (Study 2) in addition to other aircraft-level and pair-level factors. This finding suggests that linear combination of aircraft-level or dyad-level information may not be adequate and the global-pattern-based index is necessary. Theoretical and practical implications of using this framework to improve future workload modelling and management are discussed. We propose a RC network framework to model the workload of air traffic controllers. The effect of network centralisation was examined in both a static conflict detection task and a dynamic one. Network centralisation was predictive of perceived workload and task completion time over and above other control variables.
An Open-Access Modeled Passenger Flow Matrix for the Global Air Network in 2010
Huang, Zhuojie; Wu, Xiao; Garcia, Andres J.; Fik, Timothy J.; Tatem, Andrew J.
2013-01-01
The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data. PMID:23691194
An open-access modeled passenger flow matrix for the global air network in 2010.
Huang, Zhuojie; Wu, Xiao; Garcia, Andres J; Fik, Timothy J; Tatem, Andrew J
2013-01-01
The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data.
Steele, L. P. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, Victoria, Australia; Krummel, P. B. [Commonwealth Scientific and Industrial Research Organization (CSIRO),; Langenfelds, R. L. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale, Victoria, Australia
2008-01-01
Individual measurements have been obtained from flask air samples returned to the CSIRO GASLAB. Typical sample storage times range from days to weeks for some sites (e.g. Cape Grim, Aircraft over Tasmania and Bass Strait) to as much as one year for Macquarie Island and the Antarctic sites. Experiments carried out to test for changes in sample CO2 mixing ratio during storage have shown significant drifts in some flask types over test periods of several months to years (Cooper et al., 1999). Corrections derived from the test results are applied to network data according to flask type. These measurements indicate a rise in annual average atmospheric CO2 concentration from 357.72 parts per million by volume (ppmv) in 1992 to 383.05 ppmv in 2006, or an increase in annual average of about 1.81 ppmv/year. These flask data may be compared with other flask measurements from the Scripps Institution of Oceanography, available through 2004 in TRENDS; both indicate an annual average increase of 1.72 ppmv/year throuth 2004. Differences may be attributed to different sampling times or days, different numbers of samples, and different curve-fitting techniques used to obtain monthly and annual average numbers from flask data. Measurement error in flask data is believed to be small (Masarie et al., 2001).
Inmarsat aeronautical mobile satellite system: Internetworking issues
NASA Technical Reports Server (NTRS)
Sengupta, Jay R.
1990-01-01
The Inmarsat Aeronautical Mobile Satellite System (AMSS) provides air-ground and air-air communications services to aero-mobile users on a global basis. Communicating parties may be connected either directly, or more commonly, via interconnecting networks to the Inmarsat AMSS, in order to construct end-to-end communications circuits. The aircraft earth station (AES) and the aeronautical ground earth station (GES) are the points of interconnection of the Inmarsat AMSS to users, as well as to interconnecting networks. This paper reviews the internetworking aspects of the Inmarsat AMSS, by introducing the Inmarsat AMSS network architecture and services concepts and then discussing the internetwork address/numbering and routing techniques.
Definition of air quality measurements for monitoring space shuttle launches
NASA Technical Reports Server (NTRS)
Thorpe, R. D.
1978-01-01
A description of a recommended air quality monitoring network to characterize the impact on ambient air quality in the Kennedy Space Center (KSC) (area) of space shuttle launch operations is given. Analysis of ground cloud processes and prevalent meteorological conditions indicates that transient HCl depositions can be a cause for concern. The system designed to monitor HCl employs an extensive network of inexpensive detectors combined with a central analysis device. An acid rain network is also recommended. A quantitative measure of projected minimal long-term impact involves the limited monitoring of NOx and particulates. All recommended monitoring is confined ti KSC property.
Schröder, Winfried; Pesch, Roland; Schmidt, Gunther
2006-03-01
In Germany, environmental monitoring is intended to provide a holistic view of the environmental condition. To this end the monitoring operated by the federal states must use harmonized, resp., standardized methods. In addition, the monitoring sites should cover the ecoregions without any geographical gaps, the monitoring design should have no gaps in terms of ecologically relevant measurement parameters, and the sample data should be spatially without any gaps. This article outlines the extent to which the Rhoen Biosphere Reserve, occupying a part of the German federal states of Bavaria, Hesse and Thuringia, fulfills the listed requirements. The investigation considered collection, data banking and analysis of monitoring data and metadata, ecological regionalization and geostatistics. Metadata on the monitoring networks were collected by questionnaires and provided a complete inventory and description of the monitoring activities in the reserve and its surroundings. The analysis of these metadata reveals that most of the monitoring methods are harmonized across the boundaries of the three federal states the Rhoen is part of. The monitoring networks that measure precipitation, surface water levels, and groundwater quality are particularly overrepresented in the central ecoregions of the biosphere reserve. Soil monitoring sites are more equally distributed within the ecoregions of the Rhoen. The number of sites for the monitoring of air pollutants is not sufficient to draw spatially valid conclusions. To fill these spatial gaps, additional data on the annual average values of the concentrations of air pollutants from monitoring sites outside of the biosphere reserve had therefore been subject to geostatistical analysis and estimation. This yields valid information on the spatial patterns and temporal trends of air quality. The approach illustrated is applicable to similar cases, as, for example, the harmonization of international monitoring networks.
Group Centric Networking: Large Scale Over the Air Testing of Group Centric Networking
2016-11-01
protocol designed to support groups of devices in a local region [4]. It attempts to use the wireless medium to broadcast minimal control information...1) Group Discovery: The goal of the group discovery algo- rithm is to find group nodes without globally flooding control messages. To facilitate this...Large Scale Over-the-Air Testing of Group Centric Networking Logan Mercer, Greg Kuperman, Andrew Hunter, Brian Proulx MIT Lincoln Laboratory
Automobile gross emitter screening with remote sensing data using objective-oriented neural network.
Chen, Ho-Wen; Yang, Hsi-Hsien; Wang, Yu-Sheng
2009-11-01
One of the costs of Taiwan's massive economic development has been severe air pollution problems in many parts of the island. Since vehicle emissions are the major source of air pollution in most of Taiwan's urban areas, Taiwan's government has implemented policies to rectify the degrading air quality, especially in areas with high population density. To reduce vehicle pollution emissions an on-road remote sensing and monitoring system is used to check the exhaust emissions from gasoline engine automobiles. By identifying individual vehicles with excessive emissions for follow-up inspection and testing, air quality in the urban environment is expected to improve greatly. Because remote sensing is capable of measuring a large number of moving vehicles in a short period, it has been considered as an assessment technique in place of the stationary emission-sampling techniques. However, inherent measurement uncertainty of remote sensing instrumentation, compounded by the indeterminacy of monitoring site selection, plus the vagaries of weather, causes large errors in pollution discrimination and limits the application of the remote sensing. Many governments are still waiting for a novel data analysis methodology to clamp down on heavily emitting vehicles by using remote sensing data. This paper proposes an artificial neural network (ANN), with vehicle attributes embedded, that can be trained by genetic algorithm (GA) based on different strategies to predict vehicle emission violation. Results show that the accuracy of predicting emission violation is as high as 92%. False determinations tend to occur for vehicles aged 7-13 years, peaking at 10 years of age.
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
Keeping warm with fur in cold water: entrainment of air in hairy surfaces
NASA Astrophysics Data System (ADS)
Nasto, Alice; Regli, Marianne; Brun, Pierre-Thomas; Clanet, Christophe; Hosoi, Anette
2015-11-01
Instead of relying on a thick layer of body fat for insulation as many aquatic mammals do, fur seals and otters trap air in their dense fur for insulation in cold water. Using a combination of model experiments and theory, we rationalize this mechanism of air trapping underwater for thermoregulation. For the model experiments, hairy surfaces are fabricated using laser cut molds and casting samples with PDMS. Modeling the hairy texture as a network of capillary tubes, the imbibition speed of water into the hairs is obtained through a balance of hydrostatic pressure and viscous stress. In this scenario, the bending of the hairs and capillary forces are negligible. The maximum diving depth that can be achieved before the hairs are wetted to the roots is predicted from a comparison of the diving speed and imbibition speed. The amount of air that is entrained in hairy surfaces is greater than what is expected for classic Landau-Levich-Derjaguin plate plunging. A phase diagram with the parameters from experiments and biological data allows a comparison of the model system and animals.
ZoroufchiBenis, Khaled; Fatehifar, Esmaeil; Ahmadi, Javad; Rouhi, Alireza
2015-01-01
Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availability of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. A multi-pollutant method (implemented as a MATLAB program) was explored for configur-ing an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids) according to their ability to represent the ambient concentration. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a sta-tion's dosage to the total dosage in the network. Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network efficiency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health.
ZoroufchiBenis, Khaled; Fatehifar, Esmaeil; Ahmadi, Javad; Rouhi, Alireza
2015-01-01
Background: Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availability of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. Methods: A multi-pollutant method (implemented as a MATLAB program) was explored for configuring an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids) according to their ability to represent the ambient concentration. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a station’s dosage to the total dosage in the network. Results: Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network efficiency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. Conclusion: The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health. PMID:26933646
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.
First results from the oil sands passive air monitoring network for polycyclic aromatic compounds.
Schuster, Jasmin K; Harner, Tom; Su, Ky; Mihele, Cristian; Eng, Anita
2015-03-03
Results are reported from an ongoing passive air monitoring study for polycyclic aromatic compounds (PACs) in the Athabasca oil sands region in Alberta, Canada. Polyurethane foam (PUF) disk passive air samplers were deployed for consecutive 2-month periods from November 2010 to June 2012 at 17 sites. Samples were analyzed for polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs, dibenzothiophene and its alkylated derivatives (DBTs). Relative to parent PAHs, alkylated PAHs and DBTs are enriched in bitumen and therefore considered to be petrogenic markers. Concentrations in air were in the range 0.03-210 ng/m(3), 0.15-230 ng/m(3) and 0.01-61 ng/m(3) for ∑PAHs, ∑alkylated PAHs and ΣDBTs, respectively. An exponential decline of the PAC concentrations in air with distance from mining areas and related petrogenic sources was observed. The most significant exponential declines were for the alkylated PAHs and DBTs and attributed to their association with mining-related emissions and near-source deposition, due to their lower volatility and greater association with depositing particles. Seasonal trends in concentrations in air for PACs were not observed for any of the compound classes. However, a forest fire episode during April to July 2011 resulted in greatly elevated PAH levels at all passive sampling locations. Alkylated PAHs and DBTs were not elevated during the forest fire period, supporting their association with petrogenic sources. Based on the results of this study, an "Athabasca PAC profile" is proposed as a potential source marker for the oil sands region. The profile is characterized by ∑PAHs/∑Alkylated PAHs = ∼0.2 and ∑PAHs/∑DBTs = ∼5.
NASA Astrophysics Data System (ADS)
Sweeney, Colm; Karion, Anna; Wolter, Sonja; Newberger, Timothy; Guenther, Doug; Higgs, Jack A.; Andrews, Arlyn Elyzabeth; Lang, Patricia M.; Neff, Don; Dlugokencky, Edward; Miller, John B.; Montzka, Stephen A.; Miller, Ben R.; Masarie, Ken Alan; Biraud, Sebastien Christophe; Novelli, Paul C.; Crotwell, Molly; Crotwell, Andrew M.; Thoning, Kirk; Tans, Pieter P.
2015-05-01
Seasonal spatial and temporal gradients for the CO2 mole fraction over North America are examined by creating a climatology from data collected 2004-2013 by the NOAA/ESRL Global Greenhouse Gas Reference Network Aircraft Program relative to trends observed for CO2 at the Mauna Loa Observatory. The data analyzed are from measurements of air samples collected in specially fabricated flask packages at frequencies of days to months at 22 sites over continental North America and shipped back to Boulder, Colorado, for analysis. These measurements are calibrated relative to the CO2 World Meteorological Organization mole fraction scale. The climatologies of CO2 are compared to climatologies of CO, CH4, SF6, N2O (which are also measured from this sampling program), and winds to understand the dominant transport and chemical and biological processes driving changes in the spatial and temporal mole fractions of CO2 as air passes over continental North America. The measurements show that air masses coming off the Pacific on the west coast of North America are relatively homogeneous with altitude. As air masses flow eastward, the lower section from the surface to 4000 m above sea level (masl) becomes distinctly different from the 4000-8000 masl section of the column. This is due in part to the extent of the planetary boundary layer, which is directly impacted by continental sources and sinks, and to the vertical gradient in west-to-east wind speeds. The slowdown and southerly shift in winds at most sites during summer months amplify the summertime drawdown relative to what might be expected from local fluxes. This influence counteracts the dilution of summer time CO2 drawdown (known as the "rectifier effect") as well as changes the surface influence "footprint" for each site. An early start to the summertime drawdown, a pronounced seasonal cycle in the column mean (500 to 8000 masl), and small vertical gradients in CO2, CO, CH4, SF6, and N2O at high-latitude western sites such as Poker Flat, Alaska, suggest recent influence of transport from southern latitudes and not local processes. This transport pathway provides a significant contribution to the large seasonal cycle observed in the high latitudes at all altitudes sampled. A sampling analysis of the NOAA/ESRL CarbonTracker model suggests that the average sampling resolution of 22 days is sufficient to get a robust estimate of mean seasonal cycle of CO2 during this 10 year period but insufficient to detect interannual variability in emissions over North America.
Langman, Jeff B.; Gebhardt, Fredrick E.; Falk, Sarah E.
2004-01-01
In cooperation with the U.S. Air Force, the U.S. Geological Survey characterized the ground-water hydrology and water quality at Melrose Air Force Range in east-central New Mexico. The purpose of the study was to provide baseline data to Cannon Air Force Base resource managers to make informed decisions concerning actions that may affect the ground-water system. Five periods of water-level measurements and four periods of water-quality sample collection were completed at Melrose Air Force Range during 2002 and 2003. The water-level measurements and water-quality samples were collected from a 29-well monitoring network that included wells in the Impact Area and leased lands of Melrose Air Force Range managed by Cannon Air Force Base personnel. The purpose of this report is to provide a broad overview of ground-water flow and ground-water quality in the Southern High Plains aquifer in the Ogallala Formation at Melrose Air Force Range. Results of the ground-water characterization of the Southern High Plains aquifer indicated a local flow system in the unconfined aquifer flowing northeastward from a topographic high, the Mesa (located in the southwestern part of the Range), toward a regional flow system in the unconfined aquifer that flows southeastward through the Portales Valley. Ground water was less than 55 years old across the Range; ground water was younger (less than 25 years) near the Mesa and ephemeral channels and older (25 years to 55 years) in the Portales Valley. Results of water-quality analysis indicated three areas of different water types: near the Mesa and ephemeral channels, in the Impact Area of the Range, and in the Portales Valley. Within the Southern High Plains aquifer, a sodium/chloride-dominated ground water was found in the center of the Impact Area of the Range with water-quality characteristics similar to ground water from the underlying Chinle Formation. This sodium/chloride-dominated ground water of the unconfined aquifer in the Impact Area indicates a likely connection with the deeper water-producing zone. No pesticides, explosives, volatile organic compounds, semivolatile organic compounds, organic halogens, or perchlorate were found in water samples from the Southern High Plains aquifer at the Range.
Verifying the operational set-up of a radionuclide air-monitoring station.
Werzi, R; Padoani, F
2007-05-01
A worldwide radionuclide network of 80 stations, part of the International Monitoring System, was designed to monitor compliance with the Comprehensive Nuclear-Test-Ban Treaty. After installation, the stations are certified to comply with the minimum requirements laid down by the Preparatory Commission of the Comprehensive Nuclear-Test-Ban Treaty Organization. Among the several certification tests carried out at each station, the verification of the radionuclide activity concentrations is a crucial one and is based on an independent testing of the airflow rate measurement system and of the gamma detector system, as well as on the assessment of the samples collected during parallel sampling and measured at radionuclide laboratories.
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.
Brown, Andrew S; Brown, Richard J C; Coleman, Peter J; Conolly, Christopher; Sweetman, Andrew J; Jones, Kevin C; Butterfield, David M; Sarantaridis, Dimitris; Donovan, Brian J; Roberts, Ian
2013-06-01
The impact of human activities on the health of the population and of the wider environment has prompted action to monitor the presence of toxic compounds in the atmosphere. Toxic organic micropollutants (TOMPs) are some of the most insidious and persistent of these pollutants. Since 1991 the United Kingdom has operated nationwide air quality networks to assess the presence of TOMPs, including polycyclic aromatic hydrocarbons (PAHs), in ambient air. The data produced in 2010 marked 20 years of nationwide PAH monitoring. This paper marks this milestone by providing a novel and critical review of the data produced since nationwide monitoring began up to the end of 2011 (the latest year for which published data is available), discussing how the networks performing this monitoring has evolved, and elucidating trends in the concentrations of the PAHs measured. The current challenges in the area and a forward look to the future of air quality monitoring for PAHs are also discussed briefly.
Evaluation of Urban Air Quality By Passive Sampling Technique
NASA Astrophysics Data System (ADS)
Nunes, T. V.; Miranda, A. I.; Duarte, S.; Lima, M. J.
Aveiro is a flat small city in the centre of Portugal, close to the Atlantic coast. In the last two decades an intensive development of demographic, traffic and industry growth in the region was observed which was reflected on the air quality degrada- tion. In order to evaluate the urban air quality in Aveiro, a field-monitoring network by passive sampling with high space resolution was implemented. Twenty-four field places were distributed in a area of 3x3 Km2 and ozone and NO2 concentrations were measured. The site distribution density was higher in the centre, 250x250 m2 than in periphery where a 500x500 m2 grid was used. The selection of field places took into consideration the choice criteria recommendation by United Kingdom environmental authorities, and three tubes and a blank tube for each pollutant were used at each site. The sampling system was mounted at 3m from the ground usually profiting the street lampposts. Concerning NO2 acrylic tubes were used with 85 mm of length and an in- ternal diameter of 12mm, where in one of the extremities three steel grids impregnated with a solution of TEA were placed and fixed with a polyethylene end cup (Heal et al., 1999); PFA Teflon tube with 53 mm of length and 9 mm of internal diameter and three impregnated glass filters impregnated with DPE solution fixed by a teflon end cup was used for ozone sampling (Monn and Hargartner, 1990). The passive sampling method for ozone and nitrogen dioxide was compared with continuous measurements, but the amount of measurements wasnSt enough for an accurate calibration and validation of the method. Although this constraint the field observations (June to August 2001) for these two pollutants assign interesting information about the air quality in the urban area. A krigger method of interpolation (Surfer- Golden Software-2000) was applied to field data to obtain isolines distribution of NO2 and ozone concentration for the studied area. Even the used passive sampling method has many limitations it is possi- ble to say that the NO2 concentrations were strictly related with traffic intensity and in the centre 3 to 10 times higher values were observed than the incoming air to the city; on the contrary the ozone seems to be consumed where we observe the highest NO2 concentrations. Heal, M. R.; O'Donoghue, M. A. and Cape, J. N., Overestimation of Urban Nitrogen Dioxide by Passive Sampling Tubes: a comparative exposure and model study, Atmo- spheric Environment, Vol 33, pp 513-524, 1999 Monn, Ch., Hangartner, M., Passive Sampling for Ozone, J. of Air and Waste Management Association, Vol. 40, Nz 3, 1990
Monitoring air quality in mountains: Designing an effective network
Peterson, D.L.
2000-01-01
A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.
RadNet Air Data From Honolulu, HI
This page presents radiation air monitoring and air filter analysis data for Honolulu, HI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Birmingham, AL
This page presents radiation air monitoring and air filter analysis data for Birmingham, AL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Dallas, TX
This page presents radiation air monitoring and air filter analysis data for Dallas, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Omaha, NE
This page presents radiation air monitoring and air filter analysis data for Omaha, NE from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Montgomery, AL
This page presents radiation air monitoring and air filter analysis data for Montgomery, AL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Burlington, VT
This page presents radiation air monitoring and air filter analysis data for Burlington, VT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Washington, DC
This page presents radiation air monitoring and air filter analysis data for Washington, DC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Rochester, NY
This page presents radiation air monitoring and air filter analysis data for Rochester, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Tampa, FL
This page presents radiation air monitoring and air filter analysis data for Tampa, FL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Cincinnati, OH
This page presents radiation air monitoring and air filter analysis data for Cincinnati, OH from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Fairbanks, AK
This page presents radiation air monitoring and air filter analysis data for Fairbanks, AL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
This page presents radiation air monitoring and air filter analysis data for Yuma, AZ from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Kalispell, MT
This page presents radiation air monitoring and air filter analysis data for Kalispell, MT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Kearney, NE
This page presents radiation air monitoring and air filter analysis data for Kearney, NE from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Phoenix, AZ
This page presents radiation air monitoring and air filter analysis data for Phoenix, AZ from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Pierre, SD
This page presents radiation air monitoring and air filter analysis data for Pierre, SD from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Augusta, GA
This page presents radiation air monitoring and air filter analysis data for Augusta, GA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Syracuse, NY
This page presents radiation air monitoring and air filter analysis data for Syracuse, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Albany, NY
This page presents radiation air monitoring and air filter analysis data for Albany, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Anchorage, AK
This page presents radiation air monitoring and air filter analysis data for Anchorage, AK from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Philadelphia, PA
This page presents radiation air monitoring and air filter analysis data for Philadelphia, PA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Houston, TX
This page presents radiation air monitoring and air filter analysis data for Houston, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Duluth, MN
This page presents radiation air monitoring and air filter analysis data for Duluth, MN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Raleigh, NC
This page presents radiation air monitoring and air filter analysis data for Raleigh, NC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Louisville, KY
This page presents radiation air monitoring and air filter analysis data for Louisville, KY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Cleveland, OH
This page presents radiation air monitoring and air filter analysis data for Cleveland, OH from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Carlsbad, NM
This page presents radiation air monitoring and air filter analysis data for Carlsbad, NM from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Corvallis, OR
This page presents radiation air monitoring and air filter analysis data for Corvallis, OR from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Orono, ME
This page presents radiation air monitoring and air filter analysis data for Orono, ME from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
This page presents radiation air monitoring and air filter analysis data for Reno, NV from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Nashville, TN
This page presents radiation air monitoring and air filter analysis data for Nashville, TN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Concord, NH
This page presents radiation air monitoring and air filter analysis data for Concord, NH from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Paducah, KY
This page presents radiation air monitoring and air filter analysis data for Paducah, KY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Edison, NJ
This page presents radiation air monitoring and air filter analysis data for Edison, NJ from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Wilmington, NC
This page presents radiation air monitoring and air filter analysis data for Wilmington, NC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Boise, ID
This page presents radiation air monitoring and air filter analysis data for Boise, ID from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Albuquerque, NM
This page presents radiation air monitoring and air filter analysis data for Albuquerque, NM from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Fresno, CA
This page presents radiation air monitoring and air filter analysis data for Fresno, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Amarillo, TX
This page presents radiation air monitoring and air filter analysis data for Amarillo, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Portland, OR
This page presents radiation air monitoring and air filter analysis data for Portland, OR from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Jacksonville, FL
This page presents radiation air monitoring and air filter analysis data for Jacksonville, FL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Dover, DE
This page presents radiation air monitoring and air filter analysis data for Dover, DE from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Baltimore, MD
This page presents radiation air monitoring and air filter analysis data for Baltimore, MD from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Miami, FL
This page presents radiation air monitoring and air filter analysis data for Miami, FL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Billings, MT
This page presents radiation air monitoring and air filter analysis data for Billings, MT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Providence, RI
This page presents radiation air monitoring and air filter analysis data for Providence, RI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Knoxville, TN
This page presents radiation air monitoring and air filter analysis data for Knoxville, TN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Columbus, OH
This page presents radiation air monitoring and air filter analysis data for Columbus, OH from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Bloomsburg, PA
This page presents radiation air monitoring and air filter analysis data for Bloomsburg, PA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Shreveport, LA
This page presents radiation air monitoring and air filter analysis data for Shreveport, LA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Laredo, TX
This page presents radiation air monitoring and air filter analysis data for Laredo, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Bakersfield, CA
This page presents radiation air monitoring and air filter analysis data for Bakersfield, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Portland, ME
This page presents radiation air monitoring and air filter analysis data for Portland, ME from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Champaign, IL
This page presents radiation air monitoring and air filter analysis data for Champaign, IL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Tucson, AZ
This page presents radiation air monitoring and air filter analysis data for Tucson, AZ from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Juneau, AK
This page presents radiation air monitoring and air filter analysis data for Juneau, AK from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Toledo, OH
This page presents radiation air monitoring and air filter analysis data for Toledo, OH from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Boston, MA
This page presents radiation air monitoring and air filter analysis data for Boston, MA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Indianapolis, IN
This page presents radiation air monitoring and air filter analysis data for Indianapolis, IN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Yaphank, NY
This page presents radiation air monitoring and air filter analysis data for Yaphank, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Anaheim, CA
This page presents radiation air monitoring and air filter analysis data for Anaheim, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Riverside, CA
This page presents radiation air monitoring and air filter analysis data for Riverside, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Detroit, MI
This page presents radiation air monitoring and air filter analysis data for Detroit, MI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Wichita, KS
This page presents radiation air monitoring and air filter analysis data for Wichita, KS from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Columbia, SC
This page presents radiation air monitoring and air filter analysis data for Columbia, SC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Milwaukee, WI
This page presents radiation air monitoring and air filter analysis data for Milwaukee, WI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Richmond, VA
This page presents radiation air monitoring and air filter analysis data for Richmond, VA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Tulsa, OK
This page presents radiation air monitoring and air filter analysis data for Tulsa, OK from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Aurora, IL
This page presents radiation air monitoring and air filter analysis data for Aurora, IL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Hartford, CT
This page presents radiation air monitoring and air filter analysis data for Hartford. CT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Charleston, WV
This page presents radiation air monitoring and air filter analysis data for Charleston, WV from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Shawano, WI
This page presents radiation air monitoring and air filter analysis data for Shawano, WI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Harlingen, TX
This page presents radiation air monitoring and air filter analysis data for Harlingen, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation
RadNet Air Data From Springfield, MO
This page presents radiation air monitoring and air filter analysis data for Springfield, MO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Olympia, WA
This page presents radiation air monitoring and air filter analysis data for Olympia, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Memphis, TN
This page presents radiation air monitoring and air filter analysis data for Memphis, TN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Lubbock, TX
This page presents radiation air monitoring and air filter analysis data for Lubbock, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Sacramento, CA
This page presents radiation air monitoring and air filter analysis data for Sacramento, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Lockport, NY
This page presents radiation air monitoring and air filter analysis data for Lockport, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Jackson, MS
This page presents radiation air monitoring and air filter analysis data for Jackson, MS from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Seattle, WA
This page presents radiation air monitoring and air filter analysis data for Seattle, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Pittsburgh, PA
This page presents radiation air monitoring and air filter analysis data for Pittsburgh, PA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Madison, WI
This page presents radiation air monitoring and air filter analysis data for Madison, WI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Ellensburg, WA
This page presents radiation air monitoring and air filter analysis data for Ellensburg, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Harrisonburg, VA
This page presents radiation air monitoring and air filter analysis data for Harrisonburg, VA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Bismarck, ND
This page presents radiation air monitoring and air filter analysis data for Bismarck, ND from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Denver, CO
This page presents radiation air monitoring and air filter analysis data for Denver, CO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Charlotte, NC
This page presents radiation air monitoring and air filter analysis data for Charlotte, NC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Lexington, KY
This page presents radiation air monitoring and air filter analysis data for Lexington, KY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Casper, WY
This page presents radiation air monitoring and air filter analysis data for Casper, WY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Eureka, CA
This page presents radiation air monitoring and air filter analysis data for Eureka, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Lincoln, NE
This page presents radiation air monitoring and air filter analysis data for Lincoln, NE from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Orlando, FL
This page presents radiation air monitoring and air filter analysis data for Orlando, FL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Mobile, AL
This page presents radiation air monitoring and air filter analysis data for Mobile, AL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Spokane, WA
This page presents radiation air monitoring and air filter analysis data for Spokane, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Atlanta, GA
This page presents radiation air monitoring and air filter analysis data for Atlanta, GA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Greensboro, NC
This page presents radiation air monitoring and air filter analysis data for Greensboro, NC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Chicago, IL
This page presents radiation air monitoring and air filter analysis data for Chicago, IL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Worcester, MA
This page presents radiation air monitoring and air filter analysis data for Worcester, MA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Austin, TX
This page presents radiation air monitoring and air filter analysis data for Austin, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
NASA Technical Reports Server (NTRS)
Trosin, J.
1985-01-01
Use of the Display AButments (DAB) which plots PAN AIR geometries is presented. The DAB program creates hidden line displays of PAN AIR geometries and labels specified geometry components, such as abutments, networks, and network edges. It is used to alleviate the very time consuming and error prone abutment list checking phase of developing a valid PAN AIR geometry, and therefore represents a valuable tool for debugging complex PAN AIR geometry definitions. DAB is written in FORTRAN 77 and runs on a Digital Equipment Corporation VAX 11/780 under VMS. It utilizes a special color version of the SKETCH hidden line analysis routine.
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.
Network Theory: A Primer and Questions for Air Transportation Systems Applications
NASA Technical Reports Server (NTRS)
Holmes, Bruce J.
2004-01-01
A new understanding (with potential applications to air transportation systems) has emerged in the past five years in the scientific field of networks. This development emerges in large part because we now have a new laboratory for developing theories about complex networks: The Internet. The premise of this new understanding is that most complex networks of interest, both of nature and of human contrivance, exhibit a fundamentally different behavior than thought for over two hundred years under classical graph theory. Classical theory held that networks exhibited random behavior, characterized by normal, (e.g., Gaussian or Poisson) degree distributions of the connectivity between nodes by links. The new understanding turns this idea on its head: networks of interest exhibit scale-free (or small world) degree distributions of connectivity, characterized by power law distributions. The implications of scale-free behavior for air transportation systems include the potential that some behaviors of complex system architectures might be analyzed through relatively simple approximations of local elements of the system. For air transportation applications, this presentation proposes a framework for constructing topologies (architectures) that represent the relationships between mobility, flight operations, aircraft requirements, and airspace capacity, and the related externalities in airspace procedures and architectures. The proposed architectures or topologies may serve as a framework for posing comparative and combinative analyses of performance, cost, security, environmental, and related metrics.
The international fine aerosol networks
NASA Astrophysics Data System (ADS)
Cahill, Thomas A.
1993-04-01
The adoption by the United States of a PIXE-based protocol for its fine aerosol network, after open competitions involving numerous laboratories and methods, has encouraged cooperation with other countries possessing similar capabilities and similar needs. These informal cooperative programs, involving about a dozen countries at the end of 1991, almost all use PIXE as a major component of the analytical protocols. The University of California, Davis, Air Quality Group assisted such programs through indefinite loans of a quality assurance sampler, the IMPROVE Channel A, and analyses at no cost of a small fraction of the samples taken in a side-by-side configuration. In December 1991, the World Meteorological Organization chose a protocol essentially identical to IMPROVE for the Global Atmospheric Watch (GAW) network and began deploying units, the IMPROVE Channel A, to sites around the world. Preferred analyses include fine (less than about 2.5 μm) mass, ions by ion chromatography and elements by PIXE + PESA (or, lacking that, XRF). This paper will describe progress in both programs, giving examples of the utility of the data and projecting the future expansion of the network to about 20 GAW sites by 1994.
NASA Astrophysics Data System (ADS)
Prud'homme, Genevieve; Dobbin, Nina A.; Sun, Liu; Burnett, Richard T.; Martin, Randall V.; Davidson, Andrew; Cakmak, Sabit; Villeneuve, Paul J.; Lamsal, Lok N.; van Donkelaar, Aaron; Peters, Paul A.; Johnson, Markey
2013-12-01
Satellite remote sensing (RS) has emerged as a cutting edge approach for estimating ground level ambient air pollution. Previous studies have reported a high correlation between ground level PM2.5 and NO2 estimated by RS and measurements collected at regulatory monitoring sites. The current study examined associations between air pollution and adverse respiratory and allergic health outcomes using multi-year averages of NO2 and PM2.5 from RS and from regulatory monitoring. RS estimates were derived using satellite measurements from OMI, MODIS, and MISR instruments. Regulatory monitoring data were obtained from Canada's National Air Pollution Surveillance Network. Self-reported prevalence of doctor-diagnosed asthma, current asthma, allergies, and chronic bronchitis were obtained from the Canadian Community Health Survey (a national sample of individuals 12 years of age and older). Multi-year ambient pollutant averages were assigned to each study participant based on their six digit postal code at the time of health survey, and were used as a marker for long-term exposure to air pollution. RS derived estimates of NO2 and PM2.5 were associated with 6-10% increases in respiratory and allergic health outcomes per interquartile range (3.97 μg m-3 for PM2.5 and 1.03 ppb for NO2) among adults (aged 20-64) in the national study population. Risk estimates for air pollution and respiratory/allergic health outcomes based on RS were similar to risk estimates based on regulatory monitoring for areas where regulatory monitoring data were available (within 40 km of a regulatory monitoring station). RS derived estimates of air pollution were also associated with adverse health outcomes among participants residing outside the catchment area of the regulatory monitoring network (p < 0.05). The consistency between risk estimates based on RS and regulatory monitoring as well as the associations between air pollution and health among participants living outside the catchment area for regulatory monitoring suggest that RS can provide useful estimates of long-term ambient air pollution in epidemiologic studies. This is particularly important in rural communities and other areas where monitoring and modeled air pollution data are limited or unavailable.
ERIC Educational Resources Information Center
Environmental Science and Technology, 1972
1972-01-01
State plans for implementing air quality standards are evaluated together with problems in modeling procedures and enforcement. Monitoring networks, standards, air quality regions, and industrial problems are also discussed. (BL)
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".
MEASUREMENT OF RURAL SULFUR DIOXIDE AND PARTICLE SULFATE: ANALYSIS OF CASTNET DATA, 1987 - 1996
The Clean Sir Status and Trends Network (CASTNet) was implemented by the U.S. Environmental Protection Agency (EPA) in 1991 in response to Title IX of the Clean Air Amendments of 1990, which mandated the deployment of a national ambient air monitoring network to track progress of...
RadNet Air Quality (Fixed Station) Data
RadNet is a national network of monitoring stations that regularly collect air for analysis of radioactivity. The RadNet network, which has stations in each State, has been used to track environmental releases of radioactivity from nuclear weapons tests and nuclear accidents. RadNet also documents the status and trends of environmental radioactivity
RadNet Air Data From San Juan, PR
This page presents radiation air monitoring and air filter analysis data for San Juan, PR from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Grand Rapids, MI
This page presents radiation air monitoring and air filter analysis data for Grand Rapids, MI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Corpus Christi, TX
This page presents radiation air monitoring and air filter analysis data for Corpus Christi, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Little Rock, AR
This page presents radiation air monitoring and air filter analysis data for Little Rock, AR from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Des Moines, IA
This page presents radiation air monitoring and air filter analysis data for Des Moines, IA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Fort Madison, IA
This page presents radiation air monitoring and air filter analysis data for Fort Madison, IA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Fort Wayne, IN
This page presents radiation air monitoring and air filter analysis data for Fort Wayne, IN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Navajo Lake, NM
This page presents radiation air monitoring and air filter analysis data for Navajo Lake, NM from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Las Vegas, NV
This page presents radiation air monitoring and air filter analysis data for Las Vegas, NV from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From St. George, UT
This page presents radiation air monitoring and air filter analysis data for St. George, UT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Jefferson City, MO
This page presents radiation air monitoring and air filter analysis data for Jefferson City, MO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Fort Worth, TX
This page presents radiation air monitoring and air filter analysis data for Fort Worth, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Kansas City, KS
This page presents radiation air monitoring and air filter analysis data for Kansas City, KS from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From San Angelo, TX
This page presents radiation air monitoring and air filter analysis data for San Angelo, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From San Francisco, CA
This page presents radiation air monitoring and air filter analysis data for San Francisco, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Oklahoma City, OK
This page presents radiation air monitoring and air filter analysis data for Oklahoma City, OK from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From San Bernardino, CA
This page presents radiation air monitoring and air filter analysis data for San Bernardino, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Idaho Falls, ID
This page presents radiation air monitoring and air filter analysis data for Idaho Falls, ID from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Los Angeles, CA
This page presents radiation air monitoring and air filter analysis data for Los Angeles, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From El Paso, TX
This page presents radiation air monitoring and air filter analysis data for El Paso, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Grand Junction, CO
This page presents radiation air monitoring and air filter analysis data for Grand Junction, CO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From St. Paul, MN
This page presents radiation air monitoring and air filter analysis data for St. Paul, MN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Virginia Beach, VA
This page presents radiation air monitoring and air filter analysis data for Virginia Beach, VA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From La Crosse, WI
This page presents radiation air monitoring and air filter analysis data for La Crosse, WI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From San Diego, CA
This page presents radiation air monitoring and air filter analysis data for San Diego, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From San Jose, CA
This page presents radiation air monitoring and air filter analysis data for San Jose, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From San Antonio, TX
This page presents radiation air monitoring and air filter analysis data for San Antonio, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Rapid City, SD
This page presents radiation air monitoring and air filter analysis data for Rapid City, SD from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Dodge City, KS
This page presents radiation air monitoring and air filter analysis data for Dodge City, KS from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Colorado Springs, CO
This page presents radiation air monitoring and air filter analysis data for Colorado Springs, CO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From St. Louis, MO
This page presents radiation air monitoring and air filter analysis data for St. Louis, MO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Bay City, MI
This page presents radiation air monitoring and air filter analysis data for Bay City, MI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From Mason City, IA
This page presents radiation air monitoring and air filter analysis data for Mason City, IA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
Air Quality System (AQS) Metadata
The U.S. Environmental Protection Agency compiles air quality monitoring data in the Air Quality System (AQS). Ambient air concentrations are measured at a national network of more than 4,000 monitoring stations and are reported by state, local, and tribal
RadNet Air Data From Fort Smith, AR
This page presents radiation air monitoring and air filter analysis data for Fort Smith, AR from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
Sakai, Koh; Kobayashi, Yuri; Saito, Tsuguyuki; Isogai, Akira
2016-01-01
High porosity solids, such as plastic foams and aerogels, are thermally insulating. Their insulation performance strongly depends on their pore structure, which dictates the heat transfer process in the material. Understanding such a relationship is essential to realizing highly efficient thermal insulators. Herein, we compare the heat transfer properties of foams and aerogels that have very high porosities (97.3–99.7%) and an identical composition (nanocellulose). The foams feature rather closed, microscale pores formed with a thin film-like solid phase, whereas the aerogels feature nanoscale open pores formed with a nanofibrous network-like solid skeleton. Unlike the aerogel samples, the thermal diffusivity of the foam decreases considerably with a slight increase in the solid fraction. The results indicate that for suppressing the thermal diffusion of air within high porosity solids, creating microscale spaces with distinct partitions is more effective than directly blocking the free path of air molecules at the nanoscale. PMID:26830144
40 CFR 58.15 - Annual air monitoring data certification.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Annual air monitoring data certification. 58.15 Section 58.15 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.15 Annual air monitoring data...
40 CFR 58.15 - Annual air monitoring data certification.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Annual air monitoring data certification. 58.15 Section 58.15 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.15 Annual air monitoring data...
Air Pollution Data for Model Evaluation and Application
One objective of designing an air pollution monitoring network is to obtain data for evaluating air quality models that are used in the air quality management process and scientific discovery.1.2 A common use is to relate emissions to air quality, including assessing ...
GuMNet - A high altitude monitoring network in the Sierra de Guadarrama (Madrid, Spain)
NASA Astrophysics Data System (ADS)
Santolaria-Canales, Edmundo
2016-04-01
The Guadarrama Monitoring Network (GuMNet) is an observational infrastructure focused on monitoring the state of the atmosphere and the ground in the Sierra de Guadarrama, 50 km NW of the city of Madrid. The network is composed of10 stations ranging from low altitude (900 m a.s.l.) to high mountain climate (2400 m a.s.l.). The atmospheric instrumentation includes sensors for air temperature, air humidity, 4-component net radiation, precipitation, snow height and wind speed and direction. The surface and subsurface infrastructure includes temperature and humidity sensors distributed in 9 trenches up to a maximum of 1 m depth and additionally temperature sensors in 15 PVC cased boreholes down to 20 m and 2 m with a higher vertical resolution close to the surface. All stations are located in exposed open areas except for one site that is in a forested area for measuring air-ground fluxes under forest conditions. High altitude sites are focused on periglacial areas and lower altitude sites have emphasis on pastures. One of the low altitude sites is equipped with a 10 m high tower with 3D sonic anemometers and a CO2/H2O analyzer that will allow the sampling of wind profiles and H2O and CO2 eddy covariance fluxes, important for estimation of CO2 and energy exchanges over complex vegetated surfaces. The network is connected via general packet radio service to the central lab in the Campus of Excellence of Moncloa and management software has been developed to handle the operation of the infrastructure. The data provided by GuMNet will help to improve the characterization of atmospheric variability from turbulent scales to meteorology and climate at high mountain areas, as well as land-atmosphere interactions. The network information aims at meeting the needs of accuracy to be used for biological, agricultural, hydrological, meteorological and climatic investigations in this area with relevance for ecosystem oriented studies. This setup will complement the broader network of meteorological stations of the Spanish National Meteorological Agency(AEMET), mostly distributed in the lower latitude range. This initiative is supported and developed by research groups integrating the GuMNet Consortium from the Complutense and Polytechnical Universities of Madrid (UCM and UPM), the Energetic Environmental and Technological Research Centre (CIEMAT), AEMET, and the National Park Sierra de Guadarrama (PNSG) which provided the initial foundations of this network. GuMNet will be operational in 2016. Web: http://www.ucm.es/gumnet/ Contact: edmundo.santolaria@ucm.es
NASA Astrophysics Data System (ADS)
Spencer, S.; Ogle, S.; Borch, T.; Rock, B.
2008-12-01
Monitoring soil C stocks is critical to assess the impact of future climate and land use change on carbon sinks and sources in agricultural lands. A benchmark network for soil carbon monitoring of stock changes is being designed for US agricultural lands with 3000-5000 sites anticipated and re-sampling on a 5- to10-year basis. Approximately 1000 sites would be sampled per year producing around 15,000 soil samples to be processed for total, organic, and inorganic carbon, as well as bulk density and nitrogen. Laboratory processing of soil samples is cost and time intensive, therefore we are testing the efficacy of using near-infrared (NIR) and mid-infrared (MIR) spectral methods for estimating soil carbon. As part of an initial implementation of national soil carbon monitoring, we collected over 1800 soil samples from 45 cropland sites in the mid-continental region of the U.S. Samples were processed using standard laboratory methods to determine the variables above. Carbon and nitrogen were determined by dry combustion and inorganic carbon was estimated with an acid-pressure test. 600 samples are being scanned using a bench- top NIR reflectance spectrometer (30 g of 2 mm oven-dried soil and 30 g of 8 mm air-dried soil) and 500 samples using a MIR Fourier-Transform Infrared Spectrometer (FTIR) with a DRIFT reflectance accessory (0.2 g oven-dried ground soil). Lab-measured carbon will be compared to spectrally-estimated carbon contents using Partial Least Squares (PLS) multivariate statistical approach. PLS attempts to develop a soil C predictive model that can then be used to estimate C in soil samples not lab-processed. The spectral analysis of soil samples either whole or partially processed can potentially save both funding resources and time to process samples. This is particularly relevant for the implementation of a national monitoring network for soil carbon. This poster will discuss our methods, initial results and potential for using NIR and MIR spectral approaches to either replace or augment traditional lab-based carbon analyses of soils.
NASA Astrophysics Data System (ADS)
Lowry, D.; Fisher, R. E.; Lanoisellé, M.; Nisbet, E. G.
2011-12-01
Large networks of cavity ring-down spectroscopy (CRDS) instruments to measure mixing ratios of greenhouse gases are currently being developed in wealthier populated regions. However, many major natural source regions are remote from wealthy nations, and there are often great logistical obstacles to setting up and maintaining continuous monitoring of these sources. Thus flux assessments in many regions of the world rely on a few unequally spaced 'background' stations, plus satellite interpolation. This limited network can be supplemented to great effect by methane isotope data to identify emissions from different sources and their region of emission. Ideally both carbon and hydrogen isotope signatures are needed for maximum separation of source groups. However the more complex analytical procedure and larger sample requirements for D/H measurement mean that resources are currently better utilized for high-precision carbon isotope (δ13C) measurement of methane. In particular, NOAA maintains an invaluable isotopic measurement network. Since 2008 the greenhouse gas group at Royal Holloway and partners have been measuring methane in and around the Atlantic region, currently measuring mixing ratios by CRDS at Barra (Scotland), Ascension, and E. Falklands. In addition, regular flask sampling for δ13C of CH4 is underway at these sites, plus Cape Point, South Africa, and Ny-Alesund, Spitzbergen, supplemented by collection at Sable Island, Canada, and sampling campaigns on-board the British Antarctic Survey ship, RRS James Clark Ross, between 50°S and 80°N. Methane mixing ratio and δ13C, when combined with back trajectory analysis, help to identify sources over which the air masses have passed. While the South Atlantic shows little N-S variation in δ13C (predominantly -47.2 to -46.8%) it is punctuated by emission plumes from sources in South America and Africa, and although infrequently sampled, they can in some instances be compared with the isotopic characteristics from source studies and monthly emission maps from satellite products. North Atlantic sites have a seasonal cycle (up to 0.7 to 0.8%) that increases polewards, reaching -48% in Arctic summer. Emissions contributing to this seasonal cycle and inter-annual anomalies in the cycle are wetlands (-70 to -55%, but generally more 13C-depleted with increasing latitude) and biomass burning (-30 to -25%). Added to these, and mostly with isotopic signatures between those of the two main natural sources, are anthropogenic fossil fuel (gas, coal), landfill, ruminant and vehicle emissions. The δ13C of the source mix that dominated the North Atlantic from 8 to 53°N in late September 2010 was -56.5%. This is lower than expected if anthropogenic emissions were dominant (eg. London -52 to -49%), but corresponds to the period when maximum influence of high latitude wetland (around -68%) is expected. Methane in air leaving the Eastern seaboard of Canada (Sable Island) allows regional contributions to the Atlantic mix to be assessed. These samples indicate a δ13C source mix of -52 ±2% for air leaving the NE USA and -60 ±2% for air leaving Southern Canada during summer 2010. Further north a wetland emission signal (-70 to -66%) has predominated during recent summers.
Atmospheric Model Evaluation Tool for meteorological and air quality simulations
The Atmospheric Model Evaluation Tool compares model predictions to observed data from various meteorological and air quality observation networks to help evaluate meteorological and air quality simulations.
A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates.
Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne
2014-09-01
The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NO x in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R 2 of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.
NASA Astrophysics Data System (ADS)
Pope, Ronald L.
Air pollution is a serious problem in most urban areas around the world, which has a number of negative ecological and human health impacts. As a result, it's vitally important to detect and characterize air pollutants to protect the health of the urban environment and our citizens. An important early step in this process is ensuring that the air pollution monitoring network is properly designed to capture the patterns of pollution and that all social demographics in the urban population are represented. An important aspect in characterizing air pollution patterns is scale in space and time which, along with pattern and process relationships, is a key subject in the field of landscape ecology. Thus, using multiple landscape ecological methods, this dissertation research begins by characterizing and quantifying the multi-scalar patterns of ozone (O3) and particulate matter (PM10) in the Phoenix, Arizona, metropolitan region. Results showed that pollution patterns are scale-dependent, O3 is a regionally-scaled pollutant at longer temporal scales, and PM10 is a locally-scaled pollutant with patterns sensitive to season. Next, this dissertation examines the monitoring network within Maricopa County. Using a novel multiscale indicator-based approach, the adequacy of the network was quantified by integrating inputs from various academic and government stakeholders. Furthermore, deficiencies were spatially defined and recommendations were made on how to strengthen the design of the network. A sustainability ranking system also provided new insight into the strengths and weaknesses of the network. Lastly, the study addresses the question of whether distinct social groups were experiencing inequitable exposure to pollutants - a key issue of distributive environmental injustice. A novel interdisciplinary method using multi-scalar ambient pollution data and hierarchical multiple regression models revealed environmental inequities between air pollutants and race, ethnicity, age, and socioeconomic classes. The results indicate that changing the scale of the analysis can change the equitable relationship between pollution and demographics. The scientific findings of the scale-dependent relationships among air pollution patterns, network design, and population demographics, brought to light through this study, can help policymakers make informed decisions for protecting the human health and the urban environment in the Phoenix metropolitan region and beyond.
Graphene-based battery electrodes having continuous flow paths
Zhang, Jiguang; Xiao, Jie; Liu, Jun; Xu, Wu; Li, Xiaolin; Wang, Deyu
2014-05-24
Some batteries can exhibit greatly improved performance by utilizing electrodes having randomly arranged graphene nanosheets forming a network of channels defining continuous flow paths through the electrode. The network of channels can provide a diffusion pathway for the liquid electrolyte and/or for reactant gases. Metal-air batteries can benefit from such electrodes. In particular Li-air batteries show extremely high capacities, wherein the network of channels allow oxygen to diffuse through the electrode and mesopores in the electrode can store discharge products.
1985-12-01
RELATIONAL TO NETWORK QUERY TRANSLATOR FOR A DISTRIBUTED DATABASE MANAGEMENT SYSTEM TH ESI S .L Kevin H. Mahoney -- Captain, USAF AFIT/GCS/ENG/85D-7...NETWORK QUERY TRANSLATOR FOR A DISTRIBUTED DATABASE MANAGEMENT SYSTEM - THESIS Presented to the Faculty of the School of Engineering of the Air Force...Institute of Technology Air University In Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Systems - Kevin H. Mahoney
Kerchich, Yacine; Kerbachi, Rabah
2012-12-01
The study presents the levels of air pollution by aromatic organic compounds BTEX (benzene, toluene, ethylbenzene, o-, m-, and p-xylenes) in the city of Algiers. The sampling was carried out using Radiello passive sampler. Three sampling campaigns were carried out in roadside, tunnel, urban background, and semirural sites in Algiers. In order to determine the diurnal mean levels of air pollution by BTEX to which people are exposed, a modified passive sampler was used for the first time. In addition, monitoring of pollution inside vehicles was also made. In the spring of 2009, more than 27 samplings were carried out. In the background and road traffic sites the Radiello sampler was exposed for 7 days, whereas the time exposure was reduced to 1 day in the case of the vehicle as well as the tunnel. The results indicate that average benzene concentrations in the roadside and inside vehicle exceed largely the limit value of 5 microg m(-3) established by the European Community (EC). On the other hand, it has been noticed that the concentration levels of other BTEX are relatively high. Also, in order to identify the origin of emission sources, ratios and correlations between the BTEX species have been highlighted. This study shows that road traffic remains the main source of many local emission in Algiers. The vehicle fleet in Algeria is growing rapidly since the 1990s following economic growth and is responsible for the increasing air pollution in large cities. Because there are no data collection of BTEX carried out by national air quality network, all environmental and transportation policies are based on European emissions standards, but national emission standards are currently not in place. This work will contribute to the analysis of real emissions of BTEX in Algiers, for the development of management and for assessment of population exposure variation depending on the location in the city of Algiers.
RadNet Air Data From Salt Lake City, UT
This page presents radiation air monitoring and air filter analysis data for Salt Lake City, UT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
RadNet Air Data From New York City, NY
This page presents radiation air monitoring and air filter analysis data for New York City, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.
Pope, Ronald; Wu, Jianguo
2014-06-01
In the United States, air pollution is primarily measured by Air Quality Monitoring Networks (AQMN). These AQMNs have multiple objectives, including characterizing pollution patterns, protecting the public health, and determining compliance with air quality standards. In 2006, the U.S. Environmental Protection Agency issued a directive that air pollution agencies assess the performance of their AQMNs. Although various methods to design and assess AQMNs exist, here we demonstrate a geographic information system (GIS)-based approach that combines environmental, economic, and social indicators through the assessment of the ozone (O3) and particulate matter (PM10) networks in Maricopa County, Arizona. The assessment was conducted in three phases: (1) to evaluate the performance of the existing networks, (2) to identify areas that would benefit from the addition of new monitoring stations, and (3) to recommend changes to the AQMN. A comprehensive set of indicators was created for evaluating differing aspects of the AQMNs' objectives, and weights were applied to emphasize important indicators. Indicators were also classified according to their sustainable development goal. Our results showed that O3 was well represented in the county with some redundancy in terms of the urban monitors. The addition of weights to the indicators only had a minimal effect on the results. For O3, urban monitors had greater social scores, while rural monitors had greater environmental scores. The results did not suggest a need for adding more O3 monitoring sites. For PM10, clustered urban monitors were redundant, and weights also had a minimal effect on the results. The clustered urban monitors had overall low scores; sites near point sources had high environmental scores. Several areas were identified as needing additional PM10 monitors. This study demonstrates the usefulness of a multi-indicator approach to assess AQMNs. Network managers and planners may use this method to assess the performance of air quality monitoring networks in urban regions. The U.S. Environmental Protection Agency issued a directive in 2006 that air pollution agencies assess the performance of their AQMNs; as a result, we developed a GIS-based, multi-objective assessment approach that integrates environmental, economic, and social indicators, and demonstrates its use through assessing the O3 and PM10 monitoring networks in the Phoenix metropolitan area. We exhibit a method of assessing network performance and identifying areas that would benefit from new monitoring stations; also, we demonstrate the effect of adding weights to the indicators. Our study shows that using a multi-indicator approach gave detailed assessment results for the Phoenix AQMN.
NASA Astrophysics Data System (ADS)
Hao, Yufang; Xie, Shaodong
2018-03-01
Air quality monitoring networks play a significant role in identifying the spatiotemporal patterns of air pollution, and they need to be deployed efficiently, with a minimum number of sites. The revision and optimal adjustment of existing monitoring networks is crucial for cities that have undergone rapid urban expansion and experience temporal variations in pollution patterns. The approach based on the Weather Research and Forecasting-California PUFF (WRF-CALPUFF) model and genetic algorithm (GA) was developed to design an optimal monitoring network. The maximization of coverage with minimum overlap and the ability to detect violations of standards were developed as the design objectives for redistributed networks. The non-dominated sorting genetic algorithm was applied to optimize the network size and site locations simultaneously for Shijiazhuang city, one of the most polluted cities in China. The assessment on the current network identified the insufficient spatial coverage of SO2 and NO2 monitoring for the expanding city. The optimization results showed that significant improvements were achieved in multiple objectives by redistributing the original network. Efficient coverage of the resulting designs improved to 60.99% and 76.06% of the urban area for SO2 and NO2, respectively. The redistributing design for multi-pollutant including 8 sites was also proposed, with the spatial representation covered 52.30% of the urban area and the overlapped areas decreased by 85.87% compared with the original network. The abilities to detect violations of standards were not improved as much as the other two objectives due to the conflicting nature between the multiple objectives. Additionally, the results demonstrated that the algorithm was slightly sensitive to the parameter settings, with the number of generations presented the most significant effect. Overall, our study presents an effective and feasible procedure for air quality network optimization at a city scale.
Localisation of an Unknown Number of Land Mines Using a Network of Vapour Detectors
Chhadé, Hiba Haj; Abdallah, Fahed; Mougharbel, Imad; Gning, Amadou; Julier, Simon; Mihaylova, Lyudmila
2014-01-01
We consider the problem of localising an unknown number of land mines using concentration information provided by a wireless sensor network. A number of vapour sensors/detectors, deployed in the region of interest, are able to detect the concentration of the explosive vapours, emanating from buried land mines. The collected data is communicated to a fusion centre. Using a model for the transport of the explosive chemicals in the air, we determine the unknown number of sources using a Principal Component Analysis (PCA)-based technique. We also formulate the inverse problem of determining the positions and emission rates of the land mines using concentration measurements provided by the wireless sensor network. We present a solution for this problem based on a probabilistic Bayesian technique using a Markov chain Monte Carlo sampling scheme, and we compare it to the least squares optimisation approach. Experiments conducted on simulated data show the effectiveness of the proposed approach. PMID:25384008
Jang, Hong-Seok; Xing, Shuli; Lee, Malrey; Lee, Young-Keun; So, Seung-Young
2016-05-01
In this study, an artificial neural networks study was carried out to predict the quantity of radon of Granulated Blast Furnace Slag (GBFS) cement mortar. A data set of a laboratory work, in which a total of 3 mortars were produced, was utilized in the Artificial Neural Networks (ANNs) study. The mortar mixture parameters were three different GBFS ratios (0%, 20%, 40%). Measurement radon of moist cured specimens was measured at 3, 10, 30, 100, 365 days by sensing technology for continuous monitoring of indoor air quality (IAQ). ANN model is constructed, trained and tested using these data. The data used in the ANN model are arranged in a format of two input parameters that cover the cement, GBFS and age of samples and, an output parameter which is concentrations of radon emission of mortar. The results showed that ANN can be an alternative approach for the predicting the radon concentration of GBFS mortar using mortar ingredients as input parameters.
NASA Astrophysics Data System (ADS)
Nooruddin, Hasan A.; Anifowose, Fatai; Abdulraheem, Abdulazeez
2014-03-01
Soft computing techniques are recently becoming very popular in the oil industry. A number of computational intelligence-based predictive methods have been widely applied in the industry with high prediction capabilities. Some of the popular methods include feed-forward neural networks, radial basis function network, generalized regression neural network, functional networks, support vector regression and adaptive network fuzzy inference system. A comparative study among most popular soft computing techniques is presented using a large dataset published in literature describing multimodal pore systems in the Arab D formation. The inputs to the models are air porosity, grain density, and Thomeer parameters obtained using mercury injection capillary pressure profiles. Corrected air permeability is the target variable. Applying developed permeability models in recent reservoir characterization workflow ensures consistency between micro and macro scale information represented mainly by Thomeer parameters and absolute permeability. The dataset was divided into two parts with 80% of data used for training and 20% for testing. The target permeability variable was transformed to the logarithmic scale as a pre-processing step and to show better correlations with the input variables. Statistical and graphical analysis of the results including permeability cross-plots and detailed error measures were created. In general, the comparative study showed very close results among the developed models. The feed-forward neural network permeability model showed the lowest average relative error, average absolute relative error, standard deviations of error and root means squares making it the best model for such problems. Adaptive network fuzzy inference system also showed very good results.
40 CFR 58.13 - Monitoring network completion.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Monitoring network completion. 58.13... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a) The network of NCore multipollutant sites must be physically established no later than January 1, 2011...
40 CFR 58.13 - Monitoring network completion.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Monitoring network completion. 58.13... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a) The network of NCore multipollutant sites must be physically established no later than January 1, 2011...
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.
Estimation of indoor and outdoor ratios of selected volatile organic compounds in Canada
NASA Astrophysics Data System (ADS)
Xu, Jing; Szyszkowicz, Mieczyslaw; Jovic, Branka; Cakmak, Sabit; Austin, Claire C.; Zhu, Jiping
2016-09-01
Indoor air and outdoor air concentration (I/O) ratio can be used to identify the origins of volatile organic compounds (VOCs). I/O ratios of 25 VOCs in Canada were estimated based on the data collected in various areas in Canada between September 2009 and December 2011. The indoor VOC data were extracted from the Canadian Health Measures Survey (CHMS). Outdoor VOC data were obtained from Canada's National Air Pollution Surveillance (NAPS) Network. The sampling locations covered nine areas in six provinces in Canada. Indoor air concentrations were found higher than outdoor air for all studied VOCs, except for carbon tetrachloride. Two different approaches were employed to estimate the I/O ratios; both approaches produced similar I/O values. The I/O ratios obtained from this study were similar to two other Canadian studies where indoor air and outdoor air of individual dwellings were measured. However, the I/O ratios found in Canada were higher than those in European cities and in two large USA cities, possibly due to the fact that the outdoor air concentrations recorded in the Canadian studies were lower. Possible source origins identified for the studied VOCs based on their I/O ratios were similar to those reported by others. In general, chlorinated hydrocarbons, short-chain (C5, C6) n-alkanes and benzene had significant outdoor sources, while long-chain (C10sbnd C12) n-alkanes, terpenes, naphthalene and styrene had significant indoor sources. The remaining VOCs had mixed indoor and outdoor sources.
Optimal Control for Aperiodic Dual-Rate Systems With Time-Varying Delays
Salt, Julián; Guinaldo, María; Chacón, Jesús
2018-01-01
In this work, we consider a dual-rate scenario with slow input and fast output. Our objective is the maximization of the decay rate of the system through the suitable choice of the n-input signals between two measures (periodic sampling) and their times of application. The optimization algorithm is extended for time-varying delays in order to make possible its implementation in networked control systems. We provide experimental results in an air levitation system to verify the validity of the algorithm in a real plant. PMID:29747441
Neural Networks and Their Application to Air Force Personnel Modeling
1991-11-01
specifications of the error function ( Chauvin , 1990; Hanson & Pratt, 1989) and found that out-of-sample performance can be improved by this modification...X X Black X X X X Hispanic X X - White & female X Black & male X Female X X X X Xŕ] Single or married indicator X X X X X X Age less than or equal 17...administration, female in unknown specialty, and black male in support and administration. 7Five dummies: TOE 4 and YOS 2. TOE 6 and YOS 1. TOE 6 and
Optimal Control for Aperiodic Dual-Rate Systems With Time-Varying Delays.
Aranda-Escolástico, Ernesto; Salt, Julián; Guinaldo, María; Chacón, Jesús; Dormido, Sebastián
2018-05-09
In this work, we consider a dual-rate scenario with slow input and fast output. Our objective is the maximization of the decay rate of the system through the suitable choice of the n -input signals between two measures (periodic sampling) and their times of application. The optimization algorithm is extended for time-varying delays in order to make possible its implementation in networked control systems. We provide experimental results in an air levitation system to verify the validity of the algorithm in a real plant.
Transformations in Air Transportation Systems For the 21st Century
NASA Technical Reports Server (NTRS)
Holmes, Bruce J.
2004-01-01
Globally, our transportation systems face increasingly discomforting realities: certain of the legacy air and ground infrastructures of the 20th century will not satisfy our 21st century mobility needs. The consequence of inaction is diminished quality of life and economic opportunity for those nations unable to transform from the 20th to 21st century systems. Clearly, new thinking is required regarding business models that cater to consumers value of time, airspace architectures that enable those new business models, and technology strategies for innovating at the system-of-networks level. This lecture proposes a structured way of thinking about transformation from the legacy systems of the 20th century toward new systems for the 21st century. The comparison and contrast between the legacy systems of the 20th century and the transformed systems of the 21st century provides insights into the structure of transformation of air transportation. Where the legacy systems tend to be analog (versus digital), centralized (versus distributed), and scheduled (versus on-demand) for example, transformed 21st century systems become capable of scalability through technological, business, and policy innovations. Where air mobility in our legacy systems of the 20th century brought economic opportunity and quality of life to large service markets, transformed air mobility of the 21st century becomes more equitable available to ever-thinner and widely distributed populations. Several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems create new foundations for 21st thinking about air transportation. One of the technological developments of importance arises from complexity science and modern network theory. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of robustness, resilience, and other metrics. The lecture offers an air transportation system topology and a scale-free network linkage graphic as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system topologies, and airspace architectures and procedural concepts. These new paradigms could support scalable alternatives for the expansion of future air mobility to more consumers in more parts of the world.
NASA Astrophysics Data System (ADS)
Martien, P. T.; Guha, A.; Bower, J.; Perkins, I.; Randall, S.; Young, A.; Hilken, H.; Stevenson, E.
2016-12-01
The Bay Area Air Quality Management District is the greater San Francisco Bay metropolitan area's chief air quality regulatory agency. Aligning itself with the Governor's Executive Order S-3-05, the Air District has set a goal to reduce the region's GHG emissions by 80% below 1990 levels by the year 2050. The Air District's 2016 Clean Air Plan will lay out the agency's vision and actions to put the region on a path forward towards achieving the 2050 goal while also reducing air pollution and related health impacts. The 2016 Plan has three overarching objectives: 1) develop a multi-pollutant emissions control strategy, (2) reduce population exposure to harmful air pollutants, especially in vulnerable communities, and (3) protect climate through a comprehensive Regional Climate Protection Strategy. To accomplish one of 2016 Plan's control measures (SL3 - Greenhouse Gas Monitoring and Measurement Network), the Air District has set up a long-term, ambient GHG monitoring network at four sites. The first site is located north and upwind of the urban core at Bodega Bay by the Pacific Coast. It mostly receives clean marine inflow and serves as the regional background site. The other three sites are strategically located at regional exit points for Bay Area plumes that presumably contain well-mixed GHG enhancements from local sources. CO2 and CH4are being measured continuously at the fixed-sites, along with combustion tracer CO and other air pollutants. In the longer term, the network will allow the Air District to monitor ambient concentrations of GHGs and thus evaluate the effectiveness of its policy, regulation and enforcement efforts. We present data trends from the first year of operation of the fixed-site monitoring network including monthly and seasonal patterns, diurnal variations and regional enhancements at individual sites above background concentrations. We also locate an isotopic methane instrument (Picarro, G132-i) for a short duration (a week) at each of the four fixed sites. A comparison of 13C/12C content of ambient CH4 at the downwind sites with the regional background isotopic methane signal at the coastal site provides a valuable top-down assessment of the relative distribution of biogenic versus fossil-fuel based sources of CH4 in the region.
The EPA Clean Air Status and Trends Network (CASTNET) utilizes an open face filter pack system to measure concentrations of atmospheric sulfur and nitrogen species. The purpose of this study was to estimate the uncertainty in seasonal and annual concentrations of HNO3, NO3 - , ...
BOREAS AFM-5 Level-2 Upper Air Network Standard Pressure Level Data
NASA Technical Reports Server (NTRS)
Barr, Alan; Hrynkiw, Charmaine; Hall, Forrest G. (Editor); Newcomer, Jeffrey A. (Editor); Smith, David E. (Technical Monitor)
2000-01-01
The BOREAS AFM-5 team collected and processed data from the numerous radiosonde flights during the project. The goals of the AFM-05 team were to provide large-scale definition of the atmosphere by supplementing the existing AES aerological network, both temporally and spatially. This data set includes basic upper-air parameters interpolated at 0.5 kiloPascal increments of atmospheric pressure from data collected from the network of upper-air stations during the 1993, 1994, and 1996 field campaigns over the entire study region. The data are contained in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
Maximizing algebraic connectivity in air transportation networks
NASA Astrophysics Data System (ADS)
Wei, Peng
In air transportation networks the robustness of a network regarding node and link failures is a key factor for its design. An experiment based on the real air transportation network is performed to show that the algebraic connectivity is a good measure for network robustness. Three optimization problems of algebraic connectivity maximization are then formulated in order to find the most robust network design under different constraints. The algebraic connectivity maximization problem with flight routes addition or deletion is first formulated. Three methods to optimize and analyze the network algebraic connectivity are proposed. The Modified Greedy Perturbation Algorithm (MGP) provides a sub-optimal solution in a fast iterative manner. The Weighted Tabu Search (WTS) is designed to offer a near optimal solution with longer running time. The relaxed semi-definite programming (SDP) is used to set a performance upper bound and three rounding techniques are discussed to find the feasible solution. The simulation results present the trade-off among the three methods. The case study on two air transportation networks of Virgin America and Southwest Airlines show that the developed methods can be applied in real world large scale networks. The algebraic connectivity maximization problem is extended by adding the leg number constraint, which considers the traveler's tolerance for the total connecting stops. The Binary Semi-Definite Programming (BSDP) with cutting plane method provides the optimal solution. The tabu search and 2-opt search heuristics can find the optimal solution in small scale networks and the near optimal solution in large scale networks. The third algebraic connectivity maximization problem with operating cost constraint is formulated. When the total operating cost budget is given, the number of the edges to be added is not fixed. Each edge weight needs to be calculated instead of being pre-determined. It is illustrated that the edge addition and the weight assignment can not be studied separately for the problem with operating cost constraint. Therefore a relaxed SDP method with golden section search is developed to solve both at the same time. The cluster decomposition is utilized to solve large scale networks.
Banana peel extract mediated synthesis of gold nanoparticles.
Bankar, Ashok; Joshi, Bhagyashree; Kumar, Ameeta Ravi; Zinjarde, Smita
2010-10-01
Gold nanoparticles were synthesized by using banana peel extract (BPE) as a simple, non-toxic, eco-friendly 'green material'. The boiled, crushed, acetone precipitated, air-dried peel powder was used to reduce chloroauric acid. A variety of nanoparticles were formed when the reaction conditions were altered with respect to pH, BPE content, chloroauric acid concentration and temperature of incubation. The reaction mixtures displayed vivid colors and UV-vis spectra characteristic of gold nanoparticles. Dynamic light scattering (DLS) studies revealed that the average size of the nanoparticles under standard synthetic conditions was around 300nm. Scanning electron microscopy and energy dispersive spectrometry (EDS) confirmed these results. A coffee ring phenomenon, led to the aggregation of the nanoparticles into microcubes and microwire networks towards the periphery of the air-dried samples. X-ray diffraction studies of the samples revealed spectra that were characteristic for gold. Fourier transform infra red (FTIR) spectroscopy indicated the involvement of carboxyl, amine and hydroxyl groups in the synthetic process. The BPE mediated nanoparticles displayed efficient antimicrobial activity towards most of the tested fungal and bacterial cultures.
Enhanced data validation strategy of air quality monitoring network.
Harkat, Mohamed-Faouzi; Mansouri, Majdi; Nounou, Mohamed; Nounou, Hazem
2018-01-01
Quick validation and detection of faults in measured air quality data is a crucial step towards achieving the objectives of air quality networks. Therefore, the objectives of this paper are threefold: (i) to develop a modeling technique that can be used to predict the normal behavior of air quality variables and help provide accurate reference for monitoring purposes; (ii) to develop fault detection method that can effectively and quickly detect any anomalies in measured air quality data. For this purpose, a new fault detection method that is based on the combination of generalized likelihood ratio test (GLRT) and exponentially weighted moving average (EWMA) will be developed. GLRT is a well-known statistical fault detection method that relies on maximizing the detection probability for a given false alarm rate. In this paper, we propose to develop GLRT-based EWMA fault detection method that will be able to detect the changes in the values of certain air quality variables; (iii) to develop fault isolation and identification method that allows defining the fault source(s) in order to properly apply appropriate corrective actions. In this paper, reconstruction approach that is based on Midpoint-Radii Principal Component Analysis (MRPCA) model will be developed to handle the types of data and models associated with air quality monitoring networks. All air quality modeling, fault detection, fault isolation and reconstruction methods developed in this paper will be validated using real air quality data (such as particulate matter, ozone, nitrogen and carbon oxides measurement). Copyright © 2017 Elsevier Inc. All rights reserved.
Sun, Gang; Hoff, Steven J; Zelle, Brian C; Nelson, Minda A
2008-12-01
It is vital to forecast gas and particle matter concentrations and emission rates (GPCER) from livestock production facilities to assess the impact of airborne pollutants on human health, ecological environment, and global warming. Modeling source air quality is a complex process because of abundant nonlinear interactions between GPCER and other factors. The objective of this study was to introduce statistical methods and radial basis function (RBF) neural network to predict daily source air quality in Iowa swine deep-pit finishing buildings. The results show that four variables (outdoor and indoor temperature, animal units, and ventilation rates) were identified as relative important model inputs using statistical methods. It can be further demonstrated that only two factors, the environment factor and the animal factor, were capable of explaining more than 94% of the total variability after performing principal component analysis. The introduction of fewer uncorrelated variables to the neural network would result in the reduction of the model structure complexity, minimize computation cost, and eliminate model overfitting problems. The obtained results of RBF network prediction were in good agreement with the actual measurements, with values of the correlation coefficient between 0.741 and 0.995 and very low values of systemic performance indexes for all the models. The good results indicated the RBF network could be trained to model these highly nonlinear relationships. Thus, the RBF neural network technology combined with multivariate statistical methods is a promising tool for air pollutant emissions modeling.
40 CFR 58.11 - Network technical requirements.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Network technical requirements. 58.11... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.11 Network technical requirements. (a)(1... A to this part when operating the SLAMS networks. (2) Beginning January 1, 2009, State and local...
40 CFR 58.11 - Network technical requirements.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Network technical requirements. 58.11... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.11 Network technical requirements. (a)(1... A to this part when operating the SLAMS networks. (2) Beginning January 1, 2009, State and local...
Web-based GIS: the vector-borne disease airline importation risk (VBD-AIR) tool
2012-01-01
Background Over the past century, the size and complexity of the air travel network has increased dramatically. Nowadays, there are 29.6 million scheduled flights per year and around 2.7 billion passengers are transported annually. The rapid expansion of the network increasingly connects regions of endemic vector-borne disease with the rest of the world, resulting in challenges to health systems worldwide in terms of vector-borne pathogen importation and disease vector invasion events. Here we describe the development of a user-friendly Web-based GIS tool: the Vector-Borne Disease Airline Importation Risk Tool (VBD-AIR), to help better define the roles of airports and airlines in the transmission and spread of vector-borne diseases. Methods Spatial datasets on modeled global disease and vector distributions, as well as climatic and air network traffic data were assembled. These were combined to derive relative risk metrics via air travel for imported infections, imported vectors and onward transmission, and incorporated into a three-tier server architecture in a Model-View-Controller framework with distributed GIS components. A user-friendly web-portal was built that enables dynamic querying of the spatial databases to provide relevant information. Results The VBD-AIR tool constructed enables the user to explore the interrelationships among modeled global distributions of vector-borne infectious diseases (malaria. dengue, yellow fever and chikungunya) and international air service routes to quantify seasonally changing risks of vector and vector-borne disease importation and spread by air travel, forming an evidence base to help plan mitigation strategies. The VBD-AIR tool is available at http://www.vbd-air.com. Conclusions VBD-AIR supports a data flow that generates analytical results from disparate but complementary datasets into an organized cartographical presentation on a web map for the assessment of vector-borne disease movements on the air travel network. The framework built provides a flexible and robust informatics infrastructure by separating the modules of functionality through an ontological model for vector-borne disease. The VBD‒AIR tool is designed as an evidence base for visualizing the risks of vector-borne disease by air travel for a wide range of users, including planners and decisions makers based in state and local government, and in particular, those at international and domestic airports tasked with planning for health risks and allocating limited resources. PMID:22892045
Web-based GIS: the vector-borne disease airline importation risk (VBD-AIR) tool.
Huang, Zhuojie; Das, Anirrudha; Qiu, Youliang; Tatem, Andrew J
2012-08-14
Over the past century, the size and complexity of the air travel network has increased dramatically. Nowadays, there are 29.6 million scheduled flights per year and around 2.7 billion passengers are transported annually. The rapid expansion of the network increasingly connects regions of endemic vector-borne disease with the rest of the world, resulting in challenges to health systems worldwide in terms of vector-borne pathogen importation and disease vector invasion events. Here we describe the development of a user-friendly Web-based GIS tool: the Vector-Borne Disease Airline Importation Risk Tool (VBD-AIR), to help better define the roles of airports and airlines in the transmission and spread of vector-borne diseases. Spatial datasets on modeled global disease and vector distributions, as well as climatic and air network traffic data were assembled. These were combined to derive relative risk metrics via air travel for imported infections, imported vectors and onward transmission, and incorporated into a three-tier server architecture in a Model-View-Controller framework with distributed GIS components. A user-friendly web-portal was built that enables dynamic querying of the spatial databases to provide relevant information. The VBD-AIR tool constructed enables the user to explore the interrelationships among modeled global distributions of vector-borne infectious diseases (malaria. dengue, yellow fever and chikungunya) and international air service routes to quantify seasonally changing risks of vector and vector-borne disease importation and spread by air travel, forming an evidence base to help plan mitigation strategies. The VBD-AIR tool is available at http://www.vbd-air.com. VBD-AIR supports a data flow that generates analytical results from disparate but complementary datasets into an organized cartographical presentation on a web map for the assessment of vector-borne disease movements on the air travel network. The framework built provides a flexible and robust informatics infrastructure by separating the modules of functionality through an ontological model for vector-borne disease. The VBD‒AIR tool is designed as an evidence base for visualizing the risks of vector-borne disease by air travel for a wide range of users, including planners and decisions makers based in state and local government, and in particular, those at international and domestic airports tasked with planning for health risks and allocating limited resources.
NASA Technical Reports Server (NTRS)
Walker, James L.; Russell, Samuel S.; Suits, Michael W.
2003-01-01
Intra-ply microcracking in unlined composite pressure vessels can be very troublesome to detect and when linked through the thickness can provide leak paths that may hinder mission success. The leaks may lead to loss of pressure/propellant, increased risk of explosion and possible cryo-pumping into air pockets within the laminate. Ultrasonic techniques have been shown capable of detecting the presence of microcracking and in this work they are used to quantify the level of microcracking. Resonance ultrasound methods are utilized with artificial neural networks to build a microcrack prediction/measurement tool. Two networks are presented, one unsupervised to provide a qualitative measure of microcracking and one supervised which provides a quantitative assessment of the level of microcracking. The resonant ultrasound spectroscopic method is made sensitive to microcracking by tuning the input spectrum to the higher frequency (shorter wavelength) components allowing more significant interaction with the defects. This interaction causes the spectral characteristics to shift toward lower amplitudes at the higher frequencies. As the density of the defects increases more interactions occur and more drastic amplitude changes are observed. Preliminary experiments to quantify the level of microcracking induced in graphite/epoxy composite samples through a combination of tensile loading and cryogenic temperatures are presented. Both unsupervised (Kohonen) and supervised (radial basis function) artificial neural networks are presented to determine the measurable effect on the resonance spectrum of the ultrasonic data taken from the samples.
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.
Mateos, A C; Amarillo, A C; Carreras, H A; González, C M
2018-02-01
Particle matter (PM) and its associated compounds are a serious problem for urban air quality and a threat to human health. In the present study, we assessed the intraurban variation of PM, and characterized the human health risk associated to the inhalation of particles measured on PM filters, considering different land use areas in the urban area of Cordoba city (Argentina) and different age groups. To assess the intraurban variation of PM, a biomonitoring network of T. capillaris was established in 15 sampling sites with different land use and the bioaccumulation of Co, Cu, Fe, Mn, Ni, Pb and Zn was quantified. After that, particles were collected by instrumental monitors placed at the most representative sampling sites of each land use category and an inhalation risk was calculated. A remarkable intraurban difference in the heavy metals content measured in the biomonitors was observed, in relation with the sampling site land use. The higher content was detected at industrial areas as well as in sites with intense vehicular traffic. Mean PM 10 levels exceeded the standard suggested by the U.S. EPA in all land use areas, except for the downtown. Hazard Index values were below EPA's safe limit in all land use areas and in the different age groups. In contrast, the carcinogenic risk analysis showed that all urban areas exceeded the acceptable limit (1 × 10 -6 ), while the industrial sampling sites and the elder group presented a carcinogenic risk higher that the unacceptable limit. These findings validate the use of T. capillaris to assess intraurban air quality and also show there is an important intraurban variation in human health risk associated to different land use. Copyright © 2017 Elsevier Inc. All rights reserved.
ESTABLISHING A NATIONAL ENVIRONMENTAL PUBLIC HEALTH TRACKING NETWORK
This paper describes the CDC's efforts to develop a National Environmental Public Health Tracking Network Tracking Network) with particular focus on air related issues and collaboration with EPA. A Tracking Network is needed in the United States to improve the health of communit...
NASA Astrophysics Data System (ADS)
Grenard, P.
2009-04-01
The International Monitoring System (IMS) for the Comprehensive Nuclear Test-ban-Treaty Organization is a global Network of stations for detecting and providing evidence of possible nuclear explosions. Upon completion, the IMS will consist of 321 monitoring facilities and 16 radionuclide laboratories distributed worldwide in locations designated by the Treaty. Many of these sites are located in areas that are remote and difficult to access, posing major engineering and logistical challenges. The IMS uses seismic, hydroacoustic and infrasound monitoring waveform technologies to detect signals released from an explosion or a naturally occurring event (e.g. earthquakes) in the underground, underwater and atmospheric environments. The radionuclide technology as an integral part of the IMS uses air samples to collect particular matter from the atmosphere. Samples are then analyzed for evidence of physical products created by a nuclear explosion and carried through the atmosphere. The certification process of the IMS stations assures their compliance with the IMS technical requirements. In 2008 significant progress was made towards the completion of the IMS Network. So far 75% of the IMS stations have been built and certified.
NASA Astrophysics Data System (ADS)
Redfern, Andrew; Koplow, Michael; Wright, Paul
2007-01-01
Most residential heating, ventilating, and air-conditioning (HVAC) systems utilize a single zone for conditioning air throughout the entire house. While inexpensive, these systems lead to wide temperature distributions and inefficient cooling due to the difference in thermal loads in different rooms. The end result is additional cost to the end user because the house is over conditioned. To reduce the total amount of energy used in a home and to increase occupant comfort there is a need for a better control system using multiple temperature zones. Typical multi-zone systems are costly and require extensive infrastructure to function. Recent advances in wireless sensor networks (WSNs) have enabled a low cost drop-in wireless vent register control system. The register control system is controlled by a master controller unit, which collects sensor data from a distributed wireless sensor network. Each sensor node samples local settings (occupancy, light, humidity and temperature) and reports the data back to the master control unit. The master control unit compiles the incoming data and then actuates the vent resisters to control the airflow throughout the house. The control system also utilizes a smart thermostat with a movable set point to enable the user to define their given comfort levels. The new system can reduce the run time of the HVAC system and thus decreasing the amount of energy used and increasing the comfort of the home occupations.
NASA Astrophysics Data System (ADS)
Vardoulakis, Sotiris; Solazzo, Efisio; Lumbreras, Julio
2011-09-01
Automatic monitoring networks have the ability of capturing air pollution episodes, as well as short- and long-term air quality trends in urban areas that can be used in epidemiological studies. However, due to practical constraints (e.g. cost and bulk of equipment), the use of automatic analysers is restricted to a limited number of roadside and background locations within a city. As a result, certain localised air pollution hotspots may be overlooked or overemphasised, especially near heavily trafficked street canyons and intersections. This has implications for compliance with regulatory standards and may cause exposure misclassification in epidemiological studies. Apart from automatic analysers, low cost passive diffusion tubes can be used to characterise the spatial variability of air pollution in urban areas. In this study, BTEX, NO 2 and O 3 data from a one-year passive sampling survey were used to characterise the intra-urban and street scale spatial variability of traffic-related pollutants in Birmingham (UK). In addition, continuous monitoring of NO 2, NO x, O 3, CO, SO 2, PM 10 and PM 2.5 from three permanent monitoring sites was used to identify seasonal and annual pollution patterns. The passive sampling measurements allowed us to evaluate the representativeness of a permanent roadside monitoring site that has recorded some of the highest NO 2 and PM 10 concentrations in Birmingham in recent years. Dispersion modelling was also used to gain further insight into pollutant sources and dispersion characteristics at this location. The strong spatial concentration gradients observed in busy streets, as well as the differences between roadside and urban background levels highlight the importance of appropriate positioning of air quality monitoring equipment in cities.
SPECIAL PURPOSE IT DERAILED: UNINTENDED CONSEQUENCES OF UNIVERSAL IT LAWS AND POLICIES
2017-10-26
Information Services Division ........................ 3 Figure 2: iNET Instrumentation Telemetry Ground Station...consolidate local Information Technology (IT) networks into an enterprise architecture to reduce costs and to increase security. Leadership coined this...IT network was established to link Air Force and contractor sites to seamlessly share program information . So when Air Force IT leadership tried to
Cognitive Radio Cloud Networks: Assured Access In The Future Electromagnetic Operating Environment
2017-04-04
AIR COMMAND AND STAFF COLLEGE AIR UNIVERSITY COGNITIVE RADIO CLOUD NETWORKS: ASSURED ACCESS IN THE FUTURE ELECTROMAGNETIC OPERATING...3 Abstract The electromagnetic spectrum is a finite resource that is critical to the United States military’s...ability to gain superiority in the other five warfighting domains. The Department of Defense’s electromagnetic strategy is spectrum access when and
Polar azimuth diversity HF propagation experiment
NASA Astrophysics Data System (ADS)
Baker, Kurt A.; Haines, D. M.; Weijers, Bertus
1986-03-01
Presented are the results of an HF Azimuth Diversity Propagation Experiment conducted by RADC over several paths, transauroral and polar, separated in azimuth by 30, 70, and 100 degrees, as part of the RADC Adaptive HF Propagation Program. The data presented give the occurrence of several ionospheric characteristics important to the operation of HF networks in a disturbed environment. The analysis was performed on data collected during the four seasonal periods to obtain statistical samples representative of each season under slightly disturbed as well as quiet conditions. The system used to collect the data was a network of three chirpsounder transmitters and one receiver, each sweeping over a frequency range of 2 to 30 MHz, once every five minutes. The transmitters were located at Ava, N.Y., Grand Forks, N. Dak., and Barter Island, Alaska. The receiving system was located at Thule Air Base, Greenland.
Smooth information flow in temperature climate network reflects mass transport
NASA Astrophysics Data System (ADS)
Hlinka, Jaroslav; Jajcay, Nikola; Hartman, David; Paluš, Milan
2017-03-01
A directed climate network is constructed by Granger causality analysis of air temperature time series from a regular grid covering the whole Earth. Using winner-takes-all network thresholding approach, a structure of a smooth information flow is revealed, hidden to previous studies. The relevance of this observation is confirmed by comparison with the air mass transfer defined by the wind field. Their close relation illustrates that although the information transferred due to the causal influence is not a physical quantity, the information transfer is tied to the transfer of mass and energy.
Design of a monitoring network over France in case of a radiological accidental release
NASA Astrophysics Data System (ADS)
Abida, Rachid; Bocquet, Marc; Vercauteren, Nikki; Isnard, Olivier
The Institute of Radiation Protection and Nuclear Safety (France) is planning the set-up of an automatic nuclear aerosol monitoring network over the French territory. Each of the stations will be able to automatically sample the air aerosol content and provide activity concentration measurements on several radionuclides. This should help monitor the French and neighbouring countries nuclear power plants set. It would help evaluate the impact of a radiological incident occurring at one of these nuclear facilities. This paper is devoted to the spatial design of such a network. Here, any potential network is judged on its ability to extrapolate activity concentrations measured on the network stations over the whole domain. The performance of a network is quantitatively assessed through a cost function that measures the discrepancy between the extrapolation and the true concentration fields. These true fields are obtained through the computation of a database of dispersion accidents over one year of meteorology and originating from 20 French nuclear sites. A close to optimal network is then looked for using a simulated annealing optimisation. The results emphasise the importance of the cost function in the design of a network aimed at monitoring an accidental dispersion. Several choices of norm used in the cost function are studied and give way to different designs. The influence of the number of stations is discussed. A comparison with a purely geometric approach which does not involve simulations with a chemistry-transport model is performed.
Measurement results obtained from air quality monitoring system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Turzanski, P.K.; Beres, R.
1995-12-31
An automatic system of air pollution monitoring operates in Cracow since 1991. The organization, assembling and start-up of the network is a result of joint efforts of the US Environmental Protection Agency and the Cracow environmental protection service. At present the automatic monitoring network is operated by the Provincial Inspection of Environmental Protection. There are in total seven stationary stations situated in Cracow to measure air pollution. These stations are supported continuously by one semi-mobile (transportable) station. It allows to modify periodically the area under investigation and therefore the 3-dimensional picture of creation and distribution of air pollutants within Cracowmore » area could be more intelligible.« less
Mura, Maria Chiara; De Felice, Marco; Morlino, Roberta; Fuselli, Sergio
2010-01-01
In step with the need to develop statistical procedures to manage small-size environmental samples, in this work we have used concentration values of benzene (C6H6), concurrently detected by seven outdoor and indoor monitoring stations over 12 000 minutes, in order to assess the representativeness of collected data and the impact of the pollutant on indoor environment. Clearly, the former issue is strictly connected to sampling-site geometry, which proves critical to correctly retrieving information from analysis of pollutants of sanitary interest. Therefore, according to current criteria for network-planning, single stations have been interpreted as nodes of a set of adjoining triangles; then, a) node pairs have been taken into account in order to estimate pollutant stationarity on triangle sides, as well as b) node triplets, to statistically associate data from air-monitoring with the corresponding territory area, and c) node sextuplets, to assess the impact probability of the outdoor pollutant on indoor environment for each area. Distributions from the various node combinations are all non-Gaussian, in the consequently, Kruskal-Wallis (KW) non-parametric statistics has been exploited to test variability on continuous density function from each pair, triplet and sextuplet. Results from the above-mentioned statistical analysis have shown randomness of site selection, which has not allowed a reliable generalization of monitoring data to the entire selected territory, except for a single "forced" case (70%); most important, they suggest a possible procedure to optimize network design.
Using Google Location History to track personal exposure to air pollution
NASA Astrophysics Data System (ADS)
Marais, E. A.; Wiedinmyer, C.
2017-12-01
Big data is increasingly used in air pollution research to monitor air quality and develop mitigation strategies. Google Location History provides an archive of geolocation and time information from mobile devices that can be used to track personal exposure to air pollution. Here we demonstrate the utility of Google Location History for assessing true exposure of individuals to air pollution hazardous to human health in an increasingly mobile world. We use the GEOS-Chem chemical transport model at coarse resolution (2° × 2.5°; latitude × longitude) to calculate and sample surface concentrations of fine particle mass (PM2.5) and ozone concentrations at the same time and location of each of six volunteers for 2 years (June 2015 to May 2017) and compare this to annual mean PM2.5 and ozone estimated at their postal addresses. The latter is synonymous with Global Burden of Disease studies that use a static population distribution map. We find that mobile PM2.5 is higher than static PM2.5 for most (five out of six) volunteers and can lead to a 10% increase in the risk for ischemic heart disease and stroke mortality. The difference may be more if instead a high resolution CTM or an abundant air quality monitoring network is used. There is tremendous potential to exploit geolocation and time data from mobile devices for cohort health studies and to determine best practices for limiting personal exposure to air pollution.
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.
NASA Astrophysics Data System (ADS)
Langford, A. O.; Alvarez, R. J.; Brioude, J.; Evan, S.; Iraci, L. T.; Kirgis, G.; Kuang, S.; Leblanc, T.; Newchurch, M. J.; Pierce, R. B.; Senff, C. J.; Yates, E. L.
2018-02-01
Ground-based lidars and ozonesondes belonging to the NASA-supported Tropospheric Ozone Lidar Network (TOLNet) are used in conjunction with the NASA Alpha Jet Atmospheric eXperiment (AJAX) to investigate the transport of stratospheric ozone and entrained pollution into the lower troposphere above the United States on May 24-25, 2013. TOLNet and AJAX measurements made in California, Nevada, and Alabama are compared to tropospheric ozone retrievals from the Atmospheric Infrared Sounder (AIRS), to back trajectories from the NOAA Air Resources Laboratory (ARL) Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, and to analyses from the NOAA/NESDIS Real-time Air Quality Modeling System (RAQMS) and FLEXPART particle dispersion model. The measurements and model analyses show much deeper descent of ozone-rich upper tropospheric/lower stratospheric air above the Desert Southwest than above the Southeast, and comparisons to surface measurements from regulatory monitors reporting to the U.S. EPA Air Quality System (AQS) suggest that there was a much greater surface impact in the Southwest including exceedances of the 2008 National Ambient Air Quality Standard (NAAQS) of 0.075 ppm in both Southern California and Nevada. Our analysis demonstrates the potential benefits to be gained by supplementing the existing surface ozone network with coordinated upper air observations by TOLNet.
INTEGRATION OF SATELLITE-DERIVED AEROSOL DATA INTO THE AIR QUALITY APPLICATIONS
Historically, the only source of aerosol air quality data available on an ongoing and systematic basis at national levels was generated by ambient air monitoring networks put in place for the US EPA's Air Quality Programs. Over the past several years, the remote sensing of aeros...
... Clean Air Status and Trends Network (CASTNET) Surface Water Monitoring National Atmospheric Deposition Program (NADP) Exit Interstate Air Pollution Transport Contact Us to ask a question, provide ...
Microbiological contamination of compressed air used in dentistry: an investigation.
Conte, M; Lynch, R M; Robson, M G
2001-11-01
The purpose of this preliminary investigation was twofold: 1) to examine the possibility of cross-contamination between a dental-evacuation system and the compressed air used in dental operatories and 2) to capture and identify the most common microflora in the compressed-air supply. The investigation used swab, water, and air sampling that was designed to track microorganisms from the evacuation system, through the air of the mechanical room, into the compressed-air system, and back to the patient. Samples taken in the vacuum system, the air space in the mechanical room, and the compressed-air storage tank had significantly higher total concentrations of bacteria than the outside air sampled. Samples of the compressed air returning to the operatory were found to match the outside air sample in total bacteria. It was concluded that the air dryer may have played a significant role in the elimination of microorganisms from the dental compressed-air supply.
Multifunctional Mesoscale Observing Networks.
NASA Astrophysics Data System (ADS)
Dabberdt, Walter F.; Schlatter, Thomas W.; Carr, Frederick H.; Friday, Elbert W. Joe; Jorgensen, David; Koch, Steven; Pirone, Maria; Ralph, F. Martin; Sun, Juanzhen; Welsh, Patrick; Wilson, James W.; Zou, Xiaolei
2005-07-01
More than 120 scientists, engineers, administrators, and users met on 8 10 December 2003 in a workshop format to discuss the needs for enhanced three-dimensional mesoscale observing networks. Improved networks are seen as being critical to advancing numerical and empirical modeling for a variety of mesoscale applications, including severe weather warnings and forecasts, hydrology, air-quality forecasting, chemical emergency response, transportation safety, energy management, and others. The participants shared a clear and common vision for the observing requirements: existing two-dimensional mesoscale measurement networks do not provide observations of the type, frequency, and density that are required to optimize mesoscale prediction and nowcasts. To be viable, mesoscale observing networks must serve multiple applications, and the public, private, and academic sectors must all actively participate in their design and implementation, as well as in the creation and delivery of value-added products. The mesoscale measurement challenge can best be met by an integrated approach that considers all elements of an end-to-end solution—identifying end users and their needs, designing an optimal mix of observations, defining the balance between static and dynamic (targeted or adaptive) sampling strategies, establishing long-term test beds, and developing effective implementation strategies. Detailed recommendations are provided pertaining to nowcasting, numerical prediction and data assimilation, test beds, and implementation strategies.
NASA Astrophysics Data System (ADS)
Sousa, J. T.; Pinto, J.; Martins, R.; Costa, M.; Ferreira, F.; Gomes, R.
2014-12-01
The problem of developing mobile oceanographic and atmospheric observation networks (MOAO) with coordinated air and ocean vehicles is discussed in the framework of the communications and control software tool chain developed at Underwater Systems and Technologies Laboratory (LSTS) from Porto University. This is done with reference to field experiments to illustrate key capabilities and to assess future MOAO operations. First, the motivation for building MOAO by "composition" of air and ocean vehicles, communication networks, and planning and execution control frameworks is discussed - in networked vehicle systems information and commands are exchanged among multiple vehicles and operators, and the roles, relative positions, and dependencies of these vehicles and operators change during operations. Second, the planning and execution control framework developed at LSTS for multi-vehicle systems is discussed with reference to key concepts such as autonomy, mixed-initiative interactions, and layered organization. Third, the LSTS tool software tool chain is presented to show how to develop MOAO by composition. The tool chain comprises the Neptus command and control framework for mixed initiative interactions, the underlying IMC messaging protocol, and the DUNE on-board software. Fourth, selected LSTS operational deployments illustrate MOAO capability building. In 2012 we demonstrated the use of UAS to "ferry" data from UUVs located beyond line of sight (BLOS). In 2013 we demonstrated coordinated observations of coastal fronts with small UAS and UUVs, "bent" BLOS through the use of UAS as communication relays, and UAS tracking of juvenile hammer-head sharks. In 2014 we demonstrated UUV adaptive sampling with the closed loop controller of the UUV residing on a UAS; this was done with the help of a Wave Glider ASV with a communications gateway. The results from these experiments provide a background for assessing potential future UAS operations in a compositional MOAO.
An online air pollution forecasting system using neural networks.
Kurt, Atakan; Gulbagci, Betul; Karaca, Ferhat; Alagha, Omar
2008-07-01
In this work, an online air pollution forecasting system for Greater Istanbul Area is developed. The system predicts three air pollution indicator (SO(2), PM(10) and CO) levels for the next three days (+1, +2, and +3 days) using neural networks. AirPolTool, a user-friendly website (http://airpol.fatih.edu.tr), publishes +1, +2, and +3 days predictions of air pollutants updated twice a day. Experiments presented in this paper show that quite accurate predictions of air pollutant indicator levels are possible with a simple neural network. It is shown that further optimizations of the model can be achieved using different input parameters and different experimental setups. Firstly, +1, +2, and +3 days' pollution levels are predicted independently using same training data, then +2 and +3 days are predicted cumulatively using previously days predicted values. Better prediction results are obtained in the cumulative method. Secondly, the size of training data base used in the model is optimized. The best modeling performance with minimum error rate is achieved using 3-15 past days in the training data set. Finally, the effect of the day of week as an input parameter is investigated. Better forecasts with higher accuracy are observed using the day of week as an input parameter.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rood, Arthur S.; Sondrup, A. Jeffrey
This report presents an evaluation of a hypothetical INL Site monitoring network and the existing INL air monitoring network using frequency of detection methods. The hypothetical network was designed to address the requirement in 40 CFR Part 61, Subpart H (2006) that “emissions of radionuclides to ambient air from U.S. DOE facilities shall not exceed those amounts that would cause any member of the public to receive in any year an effective dose equivalent exceeding 10 mrem/year.” To meet the requirement for monitoring only, “radionuclide releases that would result in an effective dose of 10% of the standard shall bemore » readily detectable and distinguishable from background.” Thus, the hypothetical network consists of air samplers placed at residence locations that surround INL and at other locations where onsite livestock grazing takes place. Two exposure scenarios were used in this evaluation: a resident scenario and a shepherd/rancher scenario. The resident was assumed to be continuously present at their residence while the shepherd/rancher was assumed to be present 24-hours at a fixed location on the grazing allotment. Important radionuclides were identified from annual INL radionuclide National Emission Standards for Hazardous Pollutants reports. Important radionuclides were defined as those that potentially contribute 1% or greater to the annual total dose at the radionuclide National Emission Standards for Hazardous Pollutants maximally exposed individual location and include H-3, Am-241, Pu-238, Pu 239, Cs-137, Sr-90, and I-131. For this evaluation, the network performance objective was set at achieving a frequency of detection greater than or equal to 95%. Results indicated that the hypothetical network for the resident scenario met all performance objectives for H-3 and I-131 and most performance objectives for Cs-137 and Sr-90. However, all actinides failed to meet the performance objectives for most sources. The shepherd/rancher scenario showed that air samplers placed around the facilities every 22.5 degrees were very effective in detecting releases, but this arrangement is not practical or cost effective. However, it was shown that a few air samplers placed in the prevailing wind direction around each facility could achieve the performance objective of a frequency of detection greater than or equal to 95% for the shepherd/rancher scenario. The results also indicate some of the current sampler locations have little or no impact on the network frequency of detection and could be removed from the network with no appreciable deterioration of performance. Results show that with some slight modifications to the existing network (i.e., additional samplers added north and south of the Materials and Fuels Complex and ineffective samplers removed), the network would achieve performance objectives for all sources for both the resident and shepherd/rancher scenario.« less
In 1998, the U.S. Environmental Protection Agency (U.S. EPA) established the National Dioxin Air Monitoring Network (NDAMN) to help characterize the ubiquitous presence of dioxins in the environment. This final report represents the 2013 update to NDAMN.
Expanding the NATO Movement Control Network
2016-05-17
nations and abide by their governing rules for highway, air, rail, and vessel movements . The “Strong Europe” movement network extends operational access...national movement coordi- nation centers (NMCCs). The in- teroperability and relationships that are developed there enhance the early entry of forces...by air, ground, sea, and rail. In January 2015, Operation At- lantic Resolve provided the 624th Movement Control Team (MCT), which was forward
The U.S. EPA established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric CDDs, CDFs and coplanar PCBs throughout the United States. Currently operating at 33 stations, NDAMN has, as one of its tasks, the dete...
Configuration development for ROMENET
NASA Astrophysics Data System (ADS)
Rhue, Lawrence
1989-10-01
A plan prepared by RJO Enterprises and BBN Communications Corporation (BBNCC) for the design of ROMENET, a DDN-like testbed for the Rome Air Development Center (RADC) Wide Area Networks (WAN) laboratory is presented. The ROMENET is intended to provide RADC with the ability to test and evaluate the performance and vulnerability of the Defense Data Network (DDN) technologies in support of specific Major Command programs and activities at RADC. It will also support experimentation with packet switched network technologies and includes facilities to analytically evaluate the performance of the network and its associated equipment and media. In addition, ROMENET will provide a simulation vehicle for controlled interference or jamming into the media for vulnerability assessment. Through interfaces with the RADC Battle Management Laboratory (BML), ROMENET will allow the Air Force to assess the restorative and performance characteristics of the network under stressed conditions. The closed environment of ROMENET makes it ideal for creating and testing routing algorithms and network control protocols.
Observational Needs for Four-Dimensional Air Quality Characterization
Surface-based monitoring programs provide the foundation for associating air pollution and causal effects in human health studies, and they support the development of air quality standards and the preparation of emission reduction strategies. While surface oriented networks remai...
NASA Astrophysics Data System (ADS)
Kalkisim, A. T.; Hasiloglu, A. S.; Bilen, K.
2016-04-01
Due to the refrigerant gas R134a which is used in automobile air conditioning systems and has greater global warming impact will be phased out gradually, an alternative gas is being desired to be used without much change on existing air conditioning systems. It is aimed to obtain the easier solution for intermediate values on the performance by creating a Neural Network Model in case of using a fluid (R152a) in automobile air conditioning systems that has the thermodynamic properties close to each other and near-zero global warming impact. In this instance, a network structure giving the most accurate result has been established by identifying which model provides the best education with which network structure and makes the most accurate predictions in the light of the data obtained after five different ANN models was trained with three different network structures. During training of Artificial Neural Network, Quick Propagation, Quasi-Newton, Levenberg-Marquardt and Conjugate Gradient Descent Batch Back Propagation methodsincluding five inputs and one output were trained with various network structures. Over 1500 iterations have been evaluated and the most appropriate model was identified by determining minimum error rates. The accuracy of the determined ANN model was revealed by comparing with estimates made by the Multi-Regression method.
Diagnosing AIRS Sampling with CloudSat Cloud Classes
NASA Technical Reports Server (NTRS)
Fetzer, Eric; Yue, Qing; Guillaume, Alexandre; Kahn, Brian
2011-01-01
AIRS yield and sampling vary with cloud state. Careful utilization of collocated multiple satellite sensors is necessary. Profile differences between AIRS and ECMWF model analyses indicate that AIRS has high sampling and excellent accuracy for certain meteorological conditions. Cloud-dependent sampling biases may have large impact on AIRS L2 and L3 data in climate research. MBL clouds / lower tropospheric stability relationship is one example. AIRS and CloudSat reveal a reasonable climatology in the MBL cloud regime despite limited sampling in stratocumulus. Thermodynamic parameters such as EIS derived from AIRS data map these cloud conditions successfully. We are working on characterizing AIRS scenes with mixed cloud types.
NASA Astrophysics Data System (ADS)
Calderone, G. M.
2006-12-01
A long-term monitoring program was initiated in 1995 at 6 sites at NAS Brunswick, including 3 National Priorities List (Superfund) sites. Primary contaminants of concern include chlorinated volatile organic compounds, including tetrachloroethane, trichloroethene, and vinyl chloride, in addition to metals. More than 80 submersible pumping systems were installed to facilitate sample collection utilizing the low-flow sampling technique. Long-term monitoring of the groundwater is conducted to assess the effectiveness of remedial measures, and monitor changes in contaminant concentrations in the Eastern Plume Operable Unit. Long-term monitoring program activities include quarterly groundwater sampling and analysis at more than 90 wells across 6 sites; surface water, sediment, seep, and leachate sampling and analysis at 3 sites; landfill gas monitoring; well maintenance; engineering inspections of landfill covers and other sites or evidence of stressed vegetation; water level gauging; and treatment plant sampling and analysis. Significant cost savings were achieved by optimizing the sampling network and reducing sampling frequency from quarterly to semi- annual or annual sampling. As part of an ongoing optimization effort, a geostatistical assessment of the Eastern Plume was conducted at the Naval Air Station, Brunswick, Maine. The geostatistical assessment used 40 monitoring points and analytical data collected over 3 years. For this geostatistical assessment, EA developed and utilized a database of analytical results generated during 3 years of long-term monitoring which was linked to a Geographic Information System to enhance data visualization capacity. The Geographic Information System included themes for groundwater volatile organic compound concentration, groundwater flow directions, shallow and deep wells, and immediate access to point-specific analytical results. This statistical analysis has been used by the site decision-maker and its conclusions supported a significant reduction in the Long-Term Monitoring Program.
NASA Astrophysics Data System (ADS)
Gilge, Stefan; Plass-Dülmer, Christian; Weyrauch, Dietmar; Rohrer, Franz
2013-04-01
The European ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) project, Work Package 4, aims at harmonization and improvement of the measurement of volatile organic carbon and nitrogen oxides. Central tools to assess and compare the performance of European NOx monitoring stations and labs within ACTRIS are a round robin experiment (2012) and side-by-side intercomparisons (Nov 2012). While the first checked the used laboratories' scales versus a common scale, the latter investigated weather same samples are identically and artefact-free analyzed by collocated instruments. The ACTRIS-NOx-side-by-side intercomparison was realised by instruments sampling from a common manifold which was fed by zero gas, synthetic air mixtures, ambient air, and spiked ambient air. Thus, the side-by-side experiments enabled a full characterization of the detection limit, the linear range, the span, and of potential artefacts due to interfering species for each of the contributing instruments. Generally, CLD type NOx instruments were used in the comparisons supplemented by four new optical techniques, comprising LIF and cavity enhanced techniques. In the round robin exercise, some 20 monitoring sites participated, and 14 instruments were running side-by-side in the one week Nov comparison. The results of both experiments will be presented and discussed with respect to the data quality objectives of GAW and ACTRIS.
NASA Technical Reports Server (NTRS)
Decker, Ryan K.; Walker, John R.; Barbre, Robert E., Jr.; Leach, Richard D.
2015-01-01
Atmospheric wind data are required by space launch vehicles in order to assess flight vehicle loads and performance on day-of-launch. Space launch ranges at NASA's Kennedy Space Center co-located with the United States Air Force's (USAF) Eastern Range (ER) at Cape Canaveral Air Force Station and USAF's Western Range (WR) at Vandenberg Air Force Base have extensive networks of in-situ and remote sensing instrumentation to measure atmospheric winds. Each instrument's technique to measure winds has advantages and disadvantages in regards to use within vehicle trajectory analyses. Balloons measure wind at all altitudes necessary for vehicle assessments, but two primary disadvantages exist when applying balloon output. First, balloons require approximately one hour to reach required altitudes. Second, balloons are steered by atmospheric winds down range of the launch site that could significantly differ from those winds along the vehicle ascent trajectory. These issues are mitigated by use of vertically pointing Doppler Radar Wind Profilers (DRWPs). However, multiple DRWP instruments are required to provide wind data over altitude ranges necessary for vehicle trajectory assessments. The various DRWP systems have different operating configurations resulting in different temporal and spatial sampling intervals. Therefore, software was developed to combine data from both DRWP-generated profiles into a single profile for use in vehicle trajectory analyses. This paper will present details of the splicing software algorithms and will provide sample output.
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.
Montagna, Maria Teresa; De Giglio, Osvalda; Cristina, Maria Luisa; Napoli, Christian; Pacifico, Claudia; Agodi, Antonella; Baldovin, Tatjana; Casini, Beatrice; Coniglio, Maria Anna; D'Errico, Marcello Mario; Delia, Santi Antonino; Deriu, Maria Grazia; Guida, Marco; Laganà, Pasqualina; Liguori, Giorgio; Moro, Matteo; Mura, Ida; Pennino, Francesca; Privitera, Gaetano; Romano Spica, Vincenzo; Sembeni, Silvia; Spagnolo, Anna Maria; Tardivo, Stefano; Torre, Ida; Valeriani, Federica; Albertini, Roberto; Pasquarella, Cesira
2017-06-22
Healthcare facilities (HF) represent an at-risk environment for legionellosis transmission occurring after inhalation of contaminated aerosols. In general, the control of water is preferred to that of air because, to date, there are no standardized sampling protocols. Legionella air contamination was investigated in the bathrooms of 11 HF by active sampling (Surface Air System and Coriolis ® μ) and passive sampling using settling plates. During the 8-hour sampling, hot tap water was sampled three times. All air samples were evaluated using culture-based methods, whereas liquid samples collected using the Coriolis ® μ were also analyzed by real-time PCR. Legionella presence in the air and water was then compared by sequence-based typing (SBT) methods. Air contamination was found in four HF (36.4%) by at least one of the culturable methods. The culturable investigation by Coriolis ® μ did not yield Legionella in any enrolled HF. However, molecular investigation using Coriolis ® μ resulted in eight HF testing positive for Legionella in the air. Comparison of Legionella air and water contamination indicated that Legionella water concentration could be predictive of its presence in the air. Furthermore, a molecular study of 12 L. pneumophila strains confirmed a match between the Legionella strains from air and water samples by SBT for three out of four HF that tested positive for Legionella by at least one of the culturable methods. Overall, our study shows that Legionella air detection cannot replace water sampling because the absence of microorganisms from the air does not necessarily represent their absence from water; nevertheless, air sampling may provide useful information for risk assessment. The liquid impingement technique appears to have the greatest capacity for collecting airborne Legionella if combined with molecular investigations.
Montagna, Maria Teresa; De Giglio, Osvalda; Cristina, Maria Luisa; Napoli, Christian; Pacifico, Claudia; Agodi, Antonella; Baldovin, Tatjana; Casini, Beatrice; Coniglio, Maria Anna; D’Errico, Marcello Mario; Delia, Santi Antonino; Deriu, Maria Grazia; Guida, Marco; Laganà, Pasqualina; Liguori, Giorgio; Moro, Matteo; Mura, Ida; Pennino, Francesca; Privitera, Gaetano; Romano Spica, Vincenzo; Sembeni, Silvia; Spagnolo, Anna Maria; Tardivo, Stefano; Torre, Ida; Valeriani, Federica; Albertini, Roberto; Pasquarella, Cesira
2017-01-01
Healthcare facilities (HF) represent an at-risk environment for legionellosis transmission occurring after inhalation of contaminated aerosols. In general, the control of water is preferred to that of air because, to date, there are no standardized sampling protocols. Legionella air contamination was investigated in the bathrooms of 11 HF by active sampling (Surface Air System and Coriolis®μ) and passive sampling using settling plates. During the 8-hour sampling, hot tap water was sampled three times. All air samples were evaluated using culture-based methods, whereas liquid samples collected using the Coriolis®μ were also analyzed by real-time PCR. Legionella presence in the air and water was then compared by sequence-based typing (SBT) methods. Air contamination was found in four HF (36.4%) by at least one of the culturable methods. The culturable investigation by Coriolis®μ did not yield Legionella in any enrolled HF. However, molecular investigation using Coriolis®μ resulted in eight HF testing positive for Legionella in the air. Comparison of Legionella air and water contamination indicated that Legionella water concentration could be predictive of its presence in the air. Furthermore, a molecular study of 12 L. pneumophila strains confirmed a match between the Legionella strains from air and water samples by SBT for three out of four HF that tested positive for Legionella by at least one of the culturable methods. Overall, our study shows that Legionella air detection cannot replace water sampling because the absence of microorganisms from the air does not necessarily represent their absence from water; nevertheless, air sampling may provide useful information for risk assessment. The liquid impingement technique appears to have the greatest capacity for collecting airborne Legionella if combined with molecular investigations. PMID:28640202
Trends in atmospheric heavy metals abundances over the Russian part of EMEP region in 1990-2012
NASA Astrophysics Data System (ADS)
Gromov, Sergey A.; Konkova, Elizaveta S.
2016-04-01
The European part of Russia is covered by two atmospheric environment monitoring networks established in the 1970s-1980s to monitor and evaluate anthropogenic pollution of regional/background natural environment. These are EMEP - European Monitoring and Evaluation Program of transboundary atmospheric pollutant transmission (under the UN ECE Convention on Long-Range Transboundary Air Pollution) and IBMoN - Integrated Background Monitoring Network of environmental toxic pollution (prior to 1990 under the UNEP/GEMS supervision, mostly for East European countries). IGCE laboratories operate as analytical centers for both networks. Historically, IBMoN was partly implemented at EMEP sites to support this international program with additional (optional) data. IBMoN datasets were selected for analysis of atmospheric heavy metal trends in the Russian territory of EMEP region for the last twenty three years due to more intensive operation up to now [1, 2]. Atmospheric heavy metals are collected at the remote sites with the air samples of atmospheric aerosols deposited on Petryanov's cellulose acetate filters through high-volume pumping during 24 hours. To measure lead and cadmium content, filters are transferred into the solution to determine total amounts by the Atomic Absorption Spectroscopy (AAS) with flameless atomization. Precipitation samples (collected monthly with acidic preserving) are directly injected into the AAS detection module after filtering. The sampling procedure, special processing and analytical techniques allow us to measure concentrations at substantially low levels [3, 2]. In this study we investigate the long term trends of lead and cadmium in air and precipitation at two stations, viz. Astrakhan Biosphere Reserve (46°N, 49°E) and Danki (Oka-Terrace Biosphere Reserve, 54.9°N, 37.8°E). Following the EMEP general recommendations, the evaluation was done for two continuous periods covering 1990-2001 and 2002-2012, respectively. We apply the common methodology recommended by WMO/EMEP Task Force for trend evaluation, implemented in software developed and distributed by EMEP [4]. This methodology allows approximation of apparent trends using the superposition of the exponential (main) and residual components obtained using the ad hoc trend regression model. We further use so-called reduction parameters to investigate quantitatively the nature of trends: The total over the period (Rtot) and annual average (Rave), with the latter corresponding to increasing trend at negative values. Overall, temporal tendencies of airborne cadmium and lead demonstrate similar behaviour, however on top of different average concentration levels. For both species our analysis confirms the increase in air and precipitation abundances at the regional and remote sites over the European part of Russia for the period of 2002-2012. References: 1. Gromov S.A., and S.G. Paramonov, 2015. Current status and prospects for the development of integrated background monitoring of environmental pollution. Problems of Ecological Monitoring and Ecosystem Modelling, v. XXVI, N 1, p. 205-221. 2. Rovinsky F.Ya. (Ed.), 1989. Analytical review of environmental pollution with heavy metals in background areas of the CMEA member countries (1982-1989). Moscow, Gidrometeoizdat, 88 p. 3. Izrael Yu.A., and F.Ya. Rovinsky, 1991. Integrated background monitoring of environmental pollution in mid-latitude Eurasia. WMO Global Atmospheric Watch No 72, WMO/TD No. 434, 104 p. 4. MSC-East, 2015. Methodology of trend analysis of air quality data (http://www.msceast.org/documents/ Methodology_of_trend_analysis.pdf).
Influence of Applying Additional Forcing Fans for the Air Distribution in Ventilation Network
NASA Astrophysics Data System (ADS)
Szlązak, Nikodem; Obracaj, Dariusz; Korzec, Marek
2016-09-01
Mining progress in underground mines cause the ongoing movement of working areas. Consequently, it becomes necessary to adapt the ventilation network of a mine to direct airflow into newly-opened districts. For economic reasons, opening new fields is often achieved via underground workings. Length of primary intake and return routes increases and also increases the total resistance of a complex ventilation network. The development of a subsurface structure can make it necessary to change the air distribution in a ventilation network. Increasing airflow into newly-opened districts is necessary. In mines where extraction does not entail gas-related hazards, there is possibility of implementing a push-pull ventilation system in order to supplement airflows to newly developed mining fields. This is achieved by installing subsurface fan stations with forcing fans at the bottom of downcast shaft. In push-pull systems with multiple main fans, it is vital to select forcing fans with characteristic curves matching those of the existing exhaust fans to prevent undesirable mutual interaction. In complex ventilation networks it is necessary to calculate distribution of airflow (especially in networks with a large number of installed fans). In the article the influence of applying additional forcing fans for the air distribution in ventilation network for underground mine were considered. There are also analysed the extent of overpressure caused by the additional forcing fan in branches of the ventilation network (the operating range of additional forcing fan). Possibilities of increasing airflow rate in working areas were conducted.
Vulnerability of network of networks
NASA Astrophysics Data System (ADS)
Havlin, S.; Kenett, D. Y.; Bashan, A.; Gao, J.; Stanley, H. E.
2014-10-01
Our dependence on networks - be they infrastructure, economic, social or others - leaves us prone to crises caused by the vulnerabilities of these networks. There is a great need to develop new methods to protect infrastructure networks and prevent cascade of failures (especially in cases of coupled networks). Terrorist attacks on transportation networks have traumatized modern societies. With a single blast, it has become possible to paralyze airline traffic, electric power supply, ground transportation or Internet communication. How, and at which cost can one restructure the network such that it will become more robust against malicious attacks? The gradual increase in attacks on the networks society depends on - Internet, mobile phone, transportation, air travel, banking, etc. - emphasize the need to develop new strategies to protect and defend these crucial networks of communication and infrastructure networks. One example is the threat of liquid explosives a few years ago, which completely shut down air travel for days, and has created extreme changes in regulations. Such threats and dangers warrant the need for new tools and strategies to defend critical infrastructure. In this paper we review recent advances in the theoretical understanding of the vulnerabilities of interdependent networks with and without spatial embedding, attack strategies and their affect on such networks of networks as well as recently developed strategies to optimize and repair failures caused by such attacks.
Biobriefcase aerosol collector
Bell, Perry M [Tracy, CA; Christian, Allen T [Madison, WI; Bailey, Christopher G [Pleasanton, CA; Willis, Ladona [Manteca, CA; Masquelier, Donald A [Tracy, CA; Nasarabadi, Shanavaz L [Livermore, CA
2009-09-22
A system for sampling air and collecting particles entrained in the air that potentially include bioagents. The system comprises providing a receiving surface, directing a liquid to the receiving surface and producing a liquid surface. Collecting samples of the air and directing the samples of air so that the samples of air with particles entrained in the air impact the liquid surface. The particles potentially including bioagents become captured in the liquid. The air with particles entrained in the air impacts the liquid surface with sufficient velocity to entrain the particles into the liquid but cause minor turbulence. The liquid surface has a surface tension and the collector samples the air and directs the air to the liquid surface so that the air with particles entrained in the air impacts the liquid surface with sufficient velocity to entrain the particles into the liquid, but cause minor turbulence on the surface resulting in insignificant evaporation of the liquid.
40 CFR 58.14 - System modification.
Code of Federal Regulations, 2010 CFR
2010-07-01
...) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.14 System modification. (a) The State, or where... monitoring network that complies with the findings of the network assessments required every 5 years by § 58... schedule with respect to the SLAMS network are subject to the approval of the EPA Regional Administrator...
40 CFR 58.14 - System modification.
Code of Federal Regulations, 2011 CFR
2011-07-01
...) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.14 System modification. (a) The State, or where... monitoring network that complies with the findings of the network assessments required every 5 years by § 58... schedule with respect to the SLAMS network are subject to the approval of the EPA Regional Administrator...
Development and testing of a portable wind sensitive directional air sampler
NASA Technical Reports Server (NTRS)
Deyo, J.; Toma, J.; King, R. B.
1975-01-01
A portable wind sensitive directional air sampler was developed as part of an air pollution source identification system. The system is designed to identify sources of air pollution based on the directional collection of field air samples and their analysis for TSP and trace element characteristics. Sources can be identified by analyzing the data on the basis of pattern recognition concepts. The unit, designated Air Scout, receives wind direction signals from an associated wind vane. Air samples are collected on filter slides using a standard high volume air sampler drawing air through a porting arrangement which tracks the wind direction and permits collection of discrete samples. A preset timer controls the length of time each filter is in the sampling position. At the conclusion of the sampling period a new filter is automatically moved into sampling position displacing the previous filter to a storage compartment. Thus the Air Scout may be set up at a field location, loaded with up to 12 filter slides, and left to acquire air samples automatically, according to the wind, at any timer interval desired from 1 to 30 hours.
Fiber-Optic Network Architectures for Onboard Avionics Applications Investigated
NASA Technical Reports Server (NTRS)
Nguyen, Hung D.; Ngo, Duc H.
2003-01-01
This project is part of a study within the Advanced Air Transportation Technologies program undertaken at the NASA Glenn Research Center. The main focus of the program is the improvement of air transportation, with particular emphasis on air transportation safety. Current and future advances in digital data communications between an aircraft and the outside world will require high-bandwidth onboard communication networks. Radiofrequency (RF) systems, with their interconnection network based on coaxial cables and waveguides, increase the complexity of communication systems onboard modern civil and military aircraft with respect to weight, power consumption, and safety. In addition, safety and reliability concerns from electromagnetic interference between the RF components embedded in these communication systems exist. A simple, reliable, and lightweight network that is free from the effects of electromagnetic interference and capable of supporting the broadband communications needs of future onboard digital avionics systems cannot be easily implemented using existing coaxial cable-based systems. Fiber-optical communication systems can meet all these challenges of modern avionics applications in an efficient, cost-effective manner. The objective of this project is to present a number of optical network architectures for onboard RF signal distribution. Because of the emergence of a number of digital avionics devices requiring high-bandwidth connectivity, fiber-optic RF networks onboard modern aircraft will play a vital role in ensuring a low-noise, highly reliable RF communication system. Two approaches are being used for network architectures for aircraft onboard fiber-optic distribution systems: a hybrid RF-optical network and an all-optical wavelength division multiplexing (WDM) network.
Predicting vehicle fuel consumption patterns using floating vehicle data.
Du, Yiman; Wu, Jianping; Yang, Senyan; Zhou, Liutong
2017-09-01
The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers' information and vehicles' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model. Copyright © 2017. Published by Elsevier B.V.
Support surfaces for pressure ulcer prevention: A network meta-analysis
Dumville, Jo C.; Cullum, Nicky
2018-01-01
Background Pressure ulcers are a prevalent and global issue and support surfaces are widely used for preventing ulceration. However, the diversity of available support surfaces and the lack of direct comparisons in RCTs make decision-making difficult. Objectives To determine, using network meta-analysis, the relative effects of different support surfaces in reducing pressure ulcer incidence and comfort and to rank these support surfaces in order of their effectiveness. Methods We conducted a systematic review, using a literature search up to November 2016, to identify randomised trials comparing support surfaces for pressure ulcer prevention. Two reviewers independently performed study selection, risk of bias assessment and data extraction. We grouped the support surfaces according to their characteristics and formed evidence networks using these groups. We used network meta-analysis to estimate the relative effects and effectiveness ranking of the groups for the outcomes of pressure ulcer incidence and participant comfort. GRADE was used to assess the certainty of evidence. Main results We included 65 studies in the review. The network for assessing pressure ulcer incidence comprised evidence of low or very low certainty for most network contrasts. There was moderate-certainty evidence that powered active air surfaces and powered hybrid air surfaces probably reduce pressure ulcer incidence compared with standard hospital surfaces (risk ratios (RR) 0.42, 95% confidence intervals (CI) 0.29 to 0.63; 0.22, 0.07 to 0.66, respectively). The network for comfort suggested that powered active air-surfaces are probably slightly less comfortable than standard hospital mattresses (RR 0.80, 95% CI 0.69 to 0.94; moderate-certainty evidence). Conclusions This is the first network meta-analysis of the effects of support surfaces for pressure ulcer prevention. Powered active air-surfaces probably reduce pressure ulcer incidence, but are probably less comfortable than standard hospital surfaces. Most prevention evidence was of low or very low certainty, and more research is required to reduce these uncertainties. PMID:29474359
Support surfaces for pressure ulcer prevention: A network meta-analysis.
Shi, Chunhu; Dumville, Jo C; Cullum, Nicky
2018-01-01
Pressure ulcers are a prevalent and global issue and support surfaces are widely used for preventing ulceration. However, the diversity of available support surfaces and the lack of direct comparisons in RCTs make decision-making difficult. To determine, using network meta-analysis, the relative effects of different support surfaces in reducing pressure ulcer incidence and comfort and to rank these support surfaces in order of their effectiveness. We conducted a systematic review, using a literature search up to November 2016, to identify randomised trials comparing support surfaces for pressure ulcer prevention. Two reviewers independently performed study selection, risk of bias assessment and data extraction. We grouped the support surfaces according to their characteristics and formed evidence networks using these groups. We used network meta-analysis to estimate the relative effects and effectiveness ranking of the groups for the outcomes of pressure ulcer incidence and participant comfort. GRADE was used to assess the certainty of evidence. We included 65 studies in the review. The network for assessing pressure ulcer incidence comprised evidence of low or very low certainty for most network contrasts. There was moderate-certainty evidence that powered active air surfaces and powered hybrid air surfaces probably reduce pressure ulcer incidence compared with standard hospital surfaces (risk ratios (RR) 0.42, 95% confidence intervals (CI) 0.29 to 0.63; 0.22, 0.07 to 0.66, respectively). The network for comfort suggested that powered active air-surfaces are probably slightly less comfortable than standard hospital mattresses (RR 0.80, 95% CI 0.69 to 0.94; moderate-certainty evidence). This is the first network meta-analysis of the effects of support surfaces for pressure ulcer prevention. Powered active air-surfaces probably reduce pressure ulcer incidence, but are probably less comfortable than standard hospital surfaces. Most prevention evidence was of low or very low certainty, and more research is required to reduce these uncertainties.
Taheri-Garavand, Amin; Karimi, Fatemeh; Karimi, Mahmoud; Lotfi, Valiullah; Khoobbakht, Golmohammad
2018-06-01
The aim of the study is to fit models for predicting surfaces using the response surface methodology and the artificial neural network to optimize for obtaining the maximum acceptability using desirability functions methodology in a hot air drying process of banana slices. The drying air temperature, air velocity, and drying time were chosen as independent factors and moisture content, drying rate, energy efficiency, and exergy efficiency were dependent variables or responses in the mentioned drying process. A rotatable central composite design as an adequate method was used to develop models for the responses in the response surface methodology. Moreover, isoresponse contour plots were useful to predict the results by performing only a limited set of experiments. The optimum operating conditions obtained from the artificial neural network models were moisture content 0.14 g/g, drying rate 1.03 g water/g h, energy efficiency 0.61, and exergy efficiency 0.91, when the air temperature, air velocity, and drying time values were equal to -0.42 (74.2 ℃), 1.00 (1.50 m/s), and -0.17 (2.50 h) in the coded units, respectively.
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
NASA Astrophysics Data System (ADS)
Golobokova, Liudmila; Polkin, Victor
2014-05-01
The newly observed kickoff of the Northern Route development drew serious attention to state of the Arctic Resource environment. Occurring climatic and environmental changes are more sensitively seen in polar areas in particular. Air environment control allows for making prognostic assessments which are required for planning hazardous environmental impacts preventive actions. In August - September 2013, RV «Professor Khlustin» Northern Sea Route expeditionary voyage took place. En-route aerosol sampling was done over the surface of the Beringov, Chukotka and Eastern-Siberia seas (till the town of Pevek). The purpose of sampling was to assess spatio-temporal variability of optic, microphysical and chemical characteristics of aerosol particles of the surface layer within different areas adjacent to the Northern Sea Route. Aerosol test made use of automated mobile unit consisting of photoelectric particles counter AZ-10, aetalometr MDA-02, aspirator on NBM-1.2 pump chassis, and the impactor. This set of equipment allows for doing measurements of number concentration, dispersed composition of aerosols within sizes d=0.3-10 mkm, mass concentration of submicron sized aerosol, and filter-conveyed aerosols sampling. Filter-conveyed aerosols sampling was done using method accepted by EMEP and EANET monitoring networks. The impactor channel was upgraded to separate particles bigger than 1 mkm in size, and the fine grain fraction settled down on it. Reverse 5-day and 10-day trajectories of air mass transfer executed at heights of 10, 1500 and 3500 m were analyzed. The heights were selected by considerations that 3000 m is the height which characterizes air mass trend in the lower troposphere. 1500 m is the upper border of the atmospheric boundary layer, and the sampling was done in the Earth's surface layer at less than 10 m. Minimum values of the bespoken microphysical characteristics are better characteristic of higher latitudes where there are no man induced sources of aerosols while the natural ones are of lower severity due to low temperatures endemic for the Arctic Ocean areas. For doing the assessment of the air mass components chemical formulation samples of water soluble fraction of the atmospheric aerosol underwent chemical analysis. Sum of main ions within the aerosol composition varied from 0.23 to 16.2 mkg/m3. Minimum ion concentrations are defined in the aerosol sampled over the Chukotka sea surface at still. Chemical composition of the Beringov and Chukotka sea aerosol was dominated by impurities of sea origin coming from the ocean with air mass. Ion sum increased concentrations were observed in the Pevek area (Eastern Siberia Sea). Aerosol chemical composition building was impacted by air mass coming from the shore. Maximum concentrations of the bespoken components are seen in the aerosol sampled during stormy weather. Increase of wind made it for raising into the air of the sea origin particles. Ingestion of sprays onto the filter was eliminated by covering the sample catcher with a special protective hood. This completed survey is indicative of favourable state of atmosphere in the arctic resource of the Russian Arctic Eastern Section during Summer-Autumn season of 2013. The job is done under financial support of project. 23 Programs of fundamental research of the RAS Presidium, Partnership Integration Project, SB RAS. 25.
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.
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 ...
EPA scientists develop Federal Reference & Equivalent Methods for measuring key air pollutants
EPA operates a nationwide air monitoring network to measure six primary air pollutants: carbon monoxide, lead, sulfur dioxide, ozone, nitrogen dioxide, and particulate matter as part of its mission to protect human health and the environment.
NASA Astrophysics Data System (ADS)
Zhao, Lirong; Wang, Xinming; He, Qiusheng; Wang, Hao; Sheng, Guoying; Chan, L. Y.; Fu, Jiamo; Blake, D. R.
Toxic air pollutants in street canyons are important issues concerning public health especially in some large Asian cities like Guangzhou. In 1998 <18% of Guangzhou citizens used public transportation modes, with a majority commuting on foot (42%) or by bicycle (22%). Of the pedestrians, 57% were either senior citizens or students. In the present study, we measured toxic air pollutants while walking along urban streets in Guangzhou to evaluate pedestrian exposure. Volatile organic compounds (VOCs) were collected with sorbent tubes, and PM 10 and CO were measured simultaneously with portable analyzers. Our results showed that pedestrian exposure to PM 10 (with an average of 303 μg m -3 for all samples) and some toxic VOCs (for example, benzene) was relatively high. Monocyclic aromatic hydrocarbons were found to be the most abundant VOCs, and 71% of the samples had benzene levels higher than 30 μg m -3. Benzene, PM 10 and CO in walk-only streets were significantly lower ( p<0.05) than in traffic streets, and the differences in exposure levels between new urban streets and old urban streets were highly significant ( p<0.01). Pedestrian exposure to toxic VOCs and PM 10 was higher than those reported in other public transportation modes (bus and subway). The good correlations between BTEX, PM 10 and CO in the streets indicated that automotive emission might be their major source. Our study also showed that the risk to pedestrians due to air pollution was misinterpreted by the reported air quality index based on measurement of SO 2, NO x and PM 10 in the government monitoring stations. An urban roadside monitoring station might be needed by air quality monitoring networks in large Asian cities like Guangzhou, in order to survey exposure to air toxics in urban roadside microenvironments.
The Roland Maze Project school-based extensive air shower network
NASA Astrophysics Data System (ADS)
Feder, J.; Jȩdrzejczak, K.; Karczmarczyk, J.; Lewandowski, R.; Swarzyński, J.; Szabelska, B.; Szabelski, J.; Wibig, T.
2006-01-01
We plan to construct the large area network of extensive air shower detectors placed on the roofs of high school buildings in the city of Łódź. Detection points will be connected by INTERNET to the central server and their work will be synchronized by GPS. The main scientific goal of the project are studies of ultra high energy cosmic rays. Using existing town infrastructure (INTERNET, power supply, etc.) will significantly reduce the cost of the experiment. Engaging high school students in the research program should significantly increase their knowledge of science and modern technologies, and can be a very efficient way of science popularisation. We performed simulations of the projected network capabilities of registering Extensive Air Showers and reconstructing energies of primary particles. Results of the simulations and the current status of project realisation will be presented.
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.
Air quality measurements and monitoring network in the Republic of Latvia
DOE Office of Scientific and Technical Information (OSTI.GOV)
Grinman, A.; Lyulko, J.; Dubrovskaja, R.
1996-12-31
The territory of Latvia is covered with a wide environmental monitoring network, that falls under 2 main categories: (1) regional network featuring the region and involved in international monitoring programs, including EMEP, GAW, IM; (2) state network providing for local pollution monitoring of the atmosphere (19 posts), precipitation (5 station) and radioactivity (46 station). In 1994, measurements were made at 20 stationary posts located in Daugavpils (2), Jekabpils (2), Jurmala, (2), Liepaja (2), Nigrande (1), Olaine (1), Rezekne (1), Riga (5), Valn-dera (2), Ventspils (2). This atmospheric air observation network covers mostly towns densely populated with industrial objects and othermore » pollutant emitting sources. Thus, the observation programs encompass measurements of pollutants that have higher concentrations in the ambient air. Results indicate that the annual pollution dynamics are closely connected with concentration fluctuations in the seasons. The sulfur dioxide and nitrogen dioxide concentrations increased during the heating season in Jekabpils, Jurmala and Valmiera, i.e., in the town that have many small heating installations. The data obtained allow to trace a dependence of measurement values upon the location of the observational posts vis-a-vis the pollutant emitting sources.« less
A cellulose liquid crystal motor: a steam engine of the second kind
Geng, Yong; Almeida, Pedro Lúcio; Fernandes, Susete Nogueira; Cheng, Cheng; Palffy-Muhoray, Peter; Godinho, Maria Helena
2013-01-01
The salient feature of liquid crystal elastomers and networks is strong coupling between orientational order and mechanical strain. Orientational order can be changed by a wide variety of stimuli, including the presence of moisture. Changes in the orientation of constituents give rise to stresses and strains, which result in changes in sample shape. We have utilized this effect to build soft cellulose-based motor driven by humidity. The motor consists of a circular loop of cellulose film, which passes over two wheels. When humid air is present near one of the wheels on one side of the film, with drier air elsewhere, rotation of the wheels results. As the wheels rotate, the humid film dries. The motor runs so long as the difference in humidity is maintained. Our cellulose liquid crystal motor thus extracts mechanical work from a difference in humidity. PMID:23293743
A cellulose liquid crystal motor: a steam engine of the second kind.
Geng, Yong; Almeida, Pedro Lúcio; Fernandes, Susete Nogueira; Cheng, Cheng; Palffy-Muhoray, Peter; Godinho, Maria Helena
2013-01-01
The salient feature of liquid crystal elastomers and networks is strong coupling between orientational order and mechanical strain. Orientational order can be changed by a wide variety of stimuli, including the presence of moisture. Changes in the orientation of constituents give rise to stresses and strains, which result in changes in sample shape. We have utilized this effect to build soft cellulose-based motor driven by humidity. The motor consists of a circular loop of cellulose film, which passes over two wheels. When humid air is present near one of the wheels on one side of the film, with drier air elsewhere, rotation of the wheels results. As the wheels rotate, the humid film dries. The motor runs so long as the difference in humidity is maintained. Our cellulose liquid crystal motor thus extracts mechanical work from a difference in humidity.
Rodgers, J C; Kenney, J W
1997-02-01
The Department of Energy has constructed a deep geologic repository for defense transuranic waste disposal. The Waste Isolation Pilot Plant, located in Southeastern New Mexico, is slated to receive transuranic waste by truck delivery beginning in 1998. The Environmental Evaluation Group (EEG) provides an independent evaluation of the impact on the health and environment in New Mexico of the WIPP project. Since 1985, the EEG has operated a network of air monitoring sites around WIPP and in nearby communities. The radionuclide concentration data from these air samples have been assembled into a useful baseline data base after resolution of a number of methodological and quality assurance issues. Investigation thresholds for the principal radionuclides have been calculated from combined data collected from several sites. These action levels will provide a critical quantitative basis for decisions of whether future airborne radionuclide measurements are attributable to accidental releases.
Sadiq, Abderrahmane; El Fazziki, Abdelaziz; Ouarzazi, Jamal; Sadgal, Mohamed
2016-01-01
This paper presents an integrated and adaptive problem-solving approach to control the on-road air quality by modeling the road infrastructure, managing traffic based on pollution level and generating recommendations for road users. The aim is to reduce vehicle emissions in the most polluted road segments and optimizing the pollution levels. For this we propose the use of historical and real time pollution records and contextual data to calculate the air quality index on road networks and generate recommendations for reassigning traffic flow in order to improve the on-road air quality. The resulting air quality indexes are used in the system's traffic network generation, which the cartography is represented by a weighted graph. The weights evolve according to the pollution indexes and path properties and the graph is therefore dynamic. Furthermore, the systems use the available pollution data and meteorological records in order to predict the on-road pollutant levels by using an artificial neural network based prediction model. The proposed approach combines the benefits of multi-agent systems, Big data technology, machine learning tools and the available data sources. For the shortest path searching in the road network, we use the Dijkstra algorithm over Hadoop MapReduce framework. The use Hadoop framework in the data retrieve and analysis process has significantly improved the performance of the proposed system. Also, the agent technology allowed proposing a suitable solution in terms of robustness and agility.
Sampling properties of directed networks
NASA Astrophysics Data System (ADS)
Son, S.-W.; Christensen, C.; Bizhani, G.; Foster, D. V.; Grassberger, P.; Paczuski, M.
2012-10-01
For many real-world networks only a small “sampled” version of the original network may be investigated; those results are then used to draw conclusions about the actual system. Variants of breadth-first search (BFS) sampling, which are based on epidemic processes, are widely used. Although it is well established that BFS sampling fails, in most cases, to capture the IN component(s) of directed networks, a description of the effects of BFS sampling on other topological properties is all but absent from the literature. To systematically study the effects of sampling biases on directed networks, we compare BFS sampling to random sampling on complete large-scale directed networks. We present new results and a thorough analysis of the topological properties of seven complete directed networks (prior to sampling), including three versions of Wikipedia, three different sources of sampled World Wide Web data, and an Internet-based social network. We detail the differences that sampling method and coverage can make to the structural properties of sampled versions of these seven networks. Most notably, we find that sampling method and coverage affect both the bow-tie structure and the number and structure of strongly connected components in sampled networks. In addition, at a low sampling coverage (i.e., less than 40%), the values of average degree, variance of out-degree, degree autocorrelation, and link reciprocity are overestimated by 30% or more in BFS-sampled networks and only attain values within 10% of the corresponding values in the complete networks when sampling coverage is in excess of 65%. These results may cause us to rethink what we know about the structure, function, and evolution of real-world directed networks.
Networking Multiple Autonomous Air and Ocean Vehicles for Oceanographic Research and Monitoring
NASA Astrophysics Data System (ADS)
McGillivary, P. A.; Borges de Sousa, J.; Rajan, K.
2013-12-01
Autonomous underwater and surface vessels (AUVs and ASVs) are coming into wider use as components of oceanographic research, including ocean observing systems. Unmanned airborne vehicles (UAVs) are now available at modest cost, allowing multiple UAVs to be deployed with multiple AUVs and ASVs. For optimal use good communication and coordination among vehicles is essential. We report on the use of multiple AUVs networked in communication with multiple UAVs. The UAVs are augmented by inferential reasoning software developed at MBARI that allows UAVs to recognize oceanographic fronts and change their navigation and control. This in turn allows UAVs to automatically to map frontal features, as well as to direct AUVs and ASVs to proceed to such features and conduct sampling via onboard sensors to provide validation for airborne mapping. ASVs can also act as data nodes for communication between UAVs and AUVs, as well as collecting data from onboard sensors, while AUVs can sample the water column vertically. This allows more accurate estimation of phytoplankton biomass and productivity, and can be used in conjunction with UAV sampling to determine air-sea flux of gases (e.g. CO2, CH4, DMS) affecting carbon budgets and atmospheric composition. In particular we describe tests in July 2013 conducted off Sesimbra, Portugal in conjunction with the Portuguese Navy by the University of Porto and MBARI with the goal of tracking large fish in the upper water column with coordinated air/surface/underwater measurements. A thermal gradient was observed in the infrared by a low flying UAV, which was used to dispatch an AUV to obtain ground truth to demonstrate the event-response capabilities using such autonomous platforms. Additional field studies in the future will facilitate integration of multiple unmanned systems into research vessel operations. The strength of hardware and software tools described in this study is to permit fundamental oceanographic measurements of both ocean and atmosphere over temporal and spatial scales that have previously been problematic. The methods demonstrated are particularly suited to the study of oceanographic fronts and for tracking and mapping oil spills or plankton blooms. With the networked coordination of multiple autonomous systems, individual components may be changed out while ocean observations continue, allowing coarse to fine spatial studies of hydrographic features over temporal dimensions that would otherwise be difficult, including diurnal and tidal periods. Constraints on these methods currently involve coordination of data archiving systems into shipboard operating systems, familiarization of oceanographers with these methods, and existing nearshore airspace use constraints on UAVs. An important outcome of these efforts is to understand the methodology for using multiple heterogeneous autonomous vehicles for targeted science exploration.
Adaptive Sampling for Urban Air Quality through Participatory Sensing
Zeng, Yuanyuan; Xiang, Kai
2017-01-01
Air pollution is one of the major problems of the modern world. The popularization and powerful functions of smartphone applications enable people to participate in urban sensing to better know about the air problems surrounding them. Data sampling is one of the most important problems that affect the sensing performance. In this paper, we propose an Adaptive Sampling Scheme for Urban Air Quality (AS-air) through participatory sensing. Firstly, we propose to find the pattern rules of air quality according to the historical data contributed by participants based on Apriori algorithm. Based on it, we predict the on-line air quality and use it to accelerate the learning process to choose and adapt the sampling parameter based on Q-learning. The evaluation results show that AS-air provides an energy-efficient sampling strategy, which is adaptive toward the varied outside air environment with good sampling efficiency. PMID:29099766
2017-10-01
AU/ACSC/MORALES/AY17 AIR COMMAND AND STAFF COLLEGE DISTANCE LEARNING AIR UNIVERSITY DATA MAYHEM VERSUS NIMBLE INFORMATION : TRANSFORMING...HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS by Luis A. Morales, Major, USAF A Research...finding solutions to compliment and supplement human analysts’ capacity, so intelligence and information can reach operators and end-users at the
In June, 1998, the U.S. EPA established the National Dioxin Air Monitoring Network (NDAMN). The primary goal of NDAMN is determine the temporal and geographical variability of atmospheric CDDs, CDFs, and coplanar PCBs at rural and nonimpacted locations throughout the United Stat...
Peter E. Koestner; Karen A. Koestner; Daniel G. Neary
2012-01-01
The Sierra Ancha International Cooperative Program on Assessment and Monitoring of Air Pollution Effects on Forests study site or (SAEF-ICP II) is part of an international network of cooperative forest monitoring sites spread throughout Europe and the United States. The United Nations Economic Commission for Europe established the ICP II network in 1985 to monitor long...
McGwin, G; Modjarrad, K; Reiland, A; Tanner, S; Rue, L W
2006-12-01
To determine the prevalence of transportation related safety behaviors, such as seatbelt and helmet use, in primetime US television programs and commercials. Cross sectional study. Top rated television programs and associated commercials from four major US television networks were reviewed for the prevalence of transportation safety related behaviors during a one month period in 2005. Programs were categorized according to the time and network of airing, program type, program rating, and--for commercials--type of product being advertised Occupants of automobiles, motorcycles, or bicycles in 507 instances in which a transportation scene was aired. Seatbelt use was depicted in 62% and 86% of individuals in television program and commercial automobile scenes, respectively. The prevalence of motorcycle helmet use was 47% in television programs and 100% in commercials. Bicycle helmets were used in 9% of television programs and 84% of commercials. The frequency of seatbelt use in programs and commercials varied by television rating and genre but did not differ by network, time of airing, or age of character portrayed. The prevalence of safety related behaviors aired on major US networks during primetime slots is higher than previous reports but still much lower than national averages. Commercials, in contrast, portray transportation safety measures with a frequency that exceeds that of US television programs or most national surveys.
Modeling the potential of different countries for pandemic spread over the global air network
NASA Astrophysics Data System (ADS)
Sun, Zhe; Lv, Baolei; Xu, Bing
2017-04-01
Air network plays an important role in the spread of global epidemics due to its superior speed and range. Understanding the disease transmission pattern via network is the foundation for the prevention and control of future pandemics. In this study, we measured the potential of different countries for the pandemic spread by using a disease transmission model which integrated inter-country air traffic flow and geographic distance. The model was verified on the spread pattern of 2003 SARS, 2009 H1N1 influenza and 2014 Ebola by setting starting point at China, Mexico and Guinea respectively. Results showed that the model well reproduced the spread direction during the early stage as the time course were in good agreement with the reported arrival dates. Then the model was used to simulate the potential risk of each country in spreading the disease as the origin country. We observed that countries in North America, Europe and East Asia had the highest risk of transmission considering their high degree in the air network. We also found that for most starting countries, United States, United Kingdom, Germany and France would become the most-important spreading cores. Compared with empirical Susceptible-Infectious-Recover model, this model could respond much faster to the disease spread with no need for empirical disease transmission parameters.
Determining Usability Versus Cost and Yields of a Regional Transport
NASA Technical Reports Server (NTRS)
Gvozdenovic, Slobodan
1999-01-01
Regional transports are designed to operate on air networks having the basic characteristics of short trip distances and low density passengers/cargo, i.e. small numbers of passengers per flight. Regional transports passenger capacity is from 10 to 100 seats and operate on routes from 350 to 1000 nautical miles (nm). An air network operated by regional transports has the following characteristics: (1) connecting regional centers; (2) operating on low density passengers/cargo flow services with minimum two frequencies per day; (3) operating on high density passengers/cargo flow with more than two frequencies per day; and (4) operating supplemental services whenever market demands in order to help bigger capacity aircraft already operating the same routes. In order to meet passenger requirements providing low fares and high or required number of frequencies, airlines must constantly monitor operational costs and keep them low. It is obvious that costs of operating aircraft must be lower than yield obtained by transporting passengers and cargo. The requirement to achieve favorable yield/cost ratio must provide the answer to the question of which aircraft will best meet a specific air network. An air network is defined by the number of services, the trip distance of each service, and the number of flights (frequencies) per day and week.
2006-03-01
equally essential to examine the antecedents that bring a person to a particular network location. The previous body of knowledge in social networks...Locus of Control on Social Network Position in Friendship Networks THESIS Gary J. Moore, Captain, USAF AFIT/GEM/ENV/06M-11 DEPARTMENT OF THE AIR...THE LONGITUDINAL EFFECTS OF SELF-MONITORING AND LOCUS OF CONTROL ON SOCIAL NETWORK POSITION IN FRIENDSHIP NETWORKS THESIS Presented to the
Identifying influencers from sampled social networks
NASA Astrophysics Data System (ADS)
Tsugawa, Sho; Kimura, Kazuma
2018-10-01
Identifying influencers who can spread information to many other individuals from a social network is a fundamental research task in the network science research field. Several measures for identifying influencers have been proposed, and the effectiveness of these influence measures has been evaluated for the case where the complete social network structure is known. However, it is difficult in practice to obtain the complete structure of a social network because of missing data, false data, or node/link sampling from the social network. In this paper, we investigate the effects of node sampling from a social network on the effectiveness of influence measures at identifying influencers. Our experimental results show that the negative effect of biased sampling, such as sample edge count, on the identification of influencers is generally small. For social media networks, we can identify influencers whose influence is comparable with that of those identified from the complete social networks by sampling only 10%-30% of the networks. Moreover, our results also suggest the possible benefit of network sampling in the identification of influencers. Our results show that, for some networks, nodes with higher influence can be discovered from sampled social networks than from complete social networks.
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.
Network Sampling with Memory: A proposal for more efficient sampling from social networks.
Mouw, Ted; Verdery, Ashton M
2012-08-01
Techniques for sampling from networks have grown into an important area of research across several fields. For sociologists, the possibility of sampling from a network is appealing for two reasons: (1) A network sample can yield substantively interesting data about network structures and social interactions, and (2) it is useful in situations where study populations are difficult or impossible to survey with traditional sampling approaches because of the lack of a sampling frame. Despite its appeal, methodological concerns about the precision and accuracy of network-based sampling methods remain. In particular, recent research has shown that sampling from a network using a random walk based approach such as Respondent Driven Sampling (RDS) can result in high design effects (DE)-the ratio of the sampling variance to the sampling variance of simple random sampling (SRS). A high design effect means that more cases must be collected to achieve the same level of precision as SRS. In this paper we propose an alternative strategy, Network Sampling with Memory (NSM), which collects network data from respondents in order to reduce design effects and, correspondingly, the number of interviews needed to achieve a given level of statistical power. NSM combines a "List" mode, where all individuals on the revealed network list are sampled with the same cumulative probability, with a "Search" mode, which gives priority to bridge nodes connecting the current sample to unexplored parts of the network. We test the relative efficiency of NSM compared to RDS and SRS on 162 school and university networks from Add Health and Facebook that range in size from 110 to 16,278 nodes. The results show that the average design effect for NSM on these 162 networks is 1.16, which is very close to the efficiency of a simple random sample (DE=1), and 98.5% lower than the average DE we observed for RDS.
Network Sampling with Memory: A proposal for more efficient sampling from social networks
Mouw, Ted; Verdery, Ashton M.
2013-01-01
Techniques for sampling from networks have grown into an important area of research across several fields. For sociologists, the possibility of sampling from a network is appealing for two reasons: (1) A network sample can yield substantively interesting data about network structures and social interactions, and (2) it is useful in situations where study populations are difficult or impossible to survey with traditional sampling approaches because of the lack of a sampling frame. Despite its appeal, methodological concerns about the precision and accuracy of network-based sampling methods remain. In particular, recent research has shown that sampling from a network using a random walk based approach such as Respondent Driven Sampling (RDS) can result in high design effects (DE)—the ratio of the sampling variance to the sampling variance of simple random sampling (SRS). A high design effect means that more cases must be collected to achieve the same level of precision as SRS. In this paper we propose an alternative strategy, Network Sampling with Memory (NSM), which collects network data from respondents in order to reduce design effects and, correspondingly, the number of interviews needed to achieve a given level of statistical power. NSM combines a “List” mode, where all individuals on the revealed network list are sampled with the same cumulative probability, with a “Search” mode, which gives priority to bridge nodes connecting the current sample to unexplored parts of the network. We test the relative efficiency of NSM compared to RDS and SRS on 162 school and university networks from Add Health and Facebook that range in size from 110 to 16,278 nodes. The results show that the average design effect for NSM on these 162 networks is 1.16, which is very close to the efficiency of a simple random sample (DE=1), and 98.5% lower than the average DE we observed for RDS. PMID:24159246
NASA Astrophysics Data System (ADS)
Hearty, T. J., III; Vollmer, B.; Wei, J. C.; Huwe, P. M.; Albayrak, A.; Wu, D. L.; Cullather, R. I.; Meyer, D. L.; Lee, J. N.; Blaisdell, J. M.; Susskind, J.; Nowicki, S.
2017-12-01
The surface air and skin temperatures reported by the Atmospheric Infrared Sounder (AIRS), the Modern-Era Retrospective analysis for Research and Applications (MERRA), and MERRA-2 at Summit, Greenland are compared with near surface air temperatures measured at National Oceanic and Atmospheric Administration (NOAA) and Greenland Climate Network (GC-Net) weather stations. Therefore this investigation requires familiarity with a heterogeneous set of swath, grid, and point data in several different formats, different granularity, and different sampling. We discuss the current subsetting capabilities available at the GES DISC (Goddard Earth Sciences Data Information Services Center) to perform the inter-comparisons necessary to evaluate the quality and trustworthiness of these datasets. We also explore potential future services which may assist users with this type of intercomparison. We find the AIRS Surface Skin Temperature (TS) is best correlated with the NOAA 2 m air temperature (T2M) but it tends to be colder than the station measurements. The difference may be the result of the frequent near surface temperature inversions in the region. The AIRS Surface Air Temperature (SAT) is also well correlated with the NOAA T2M but it has a warm bias with respect to the NOAA T2M during the cold season and a larger standard error than surface temperature. This suggests that the extrapolation of the temperature profile to the surface is not valid for the strongest inversions. Comparing the temperature lapse rate derived from the 2 stations shows that the lapse rate can increase closer to the surface. We also find that the difference between the AIRS SAT and TS is sensitive to near surface inversions. The MERRA-2 surface and near surface temperatures show improvements over MERRA but little sensitivity to near surface temperature inversions.
Mari, Montse; Nadal, Martí; Schuhmacher, Marta; Domingo, José L
2010-04-15
Kohonen's self-organizing maps (SOM) is one of the most popular artificial neural network models. In this study, SOM were used to assess the potential relationships between polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) congener profiles in environmental (soil, herbage, and ambient air) and biological (plasma, adipose tissue, and breast milk) samples, and the emissions of a hazardous waste incinerator (HWI) in Spain. The visual examination of PCDD/F congener profiles of most environmental and biological samples did not allow finding out any differences between monitors. However, the global SOM analysis of environmental and biological samples showed that the weight of the PCDD/F stack emissions of the HWI on the environmental burden and on the exposure of the individuals living in the surroundings was not significant in relation to the background levels. The results confirmed the small influence of the HWI emissions of PCDD/Fs on the environment and the population living in the neighborhood.
Sampling from complex networks using distributed learning automata
NASA Astrophysics Data System (ADS)
Rezvanian, Alireza; Rahmati, Mohammad; Meybodi, Mohammad Reza
2014-02-01
A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.
Optimization of analytical laboratory work using computer networking and databasing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Upp, D.L.; Metcalf, R.A.
1996-06-01
The Health Physics Analysis Laboratory (HPAL) performs around 600,000 analyses for radioactive nuclides each year at Los Alamos National Laboratory (LANL). Analysis matrices vary from nasal swipes, air filters, work area swipes, liquids, to the bottoms of shoes and cat litter. HPAL uses 8 liquid scintillation counters, 8 gas proportional counters, and 9 high purity germanium detectors in 5 laboratories to perform these analyses. HPAL has developed a computer network between the labs and software to produce analysis results. The software and hardware package includes barcode sample tracking, log-in, chain of custody, analysis calculations, analysis result printing, and utility programs.more » All data are written to a database, mirrored on a central server, and eventually written to CD-ROM to provide for online historical results. This system has greatly reduced the work required to provide for analysis results as well as improving the quality of the work performed.« less
NASA Technical Reports Server (NTRS)
Bowen, Brent (Editor); Gudmundsson, Sveinn (Editor); Oum, Tae (Editor)
2003-01-01
The UNO Aviation Institute Monograph Series began in 1994 as a key component of the education outreach and information transfer missions of the Aviation Institute and the NASA Nebraska Space Grant & EPSCoR Programs. The series is an outlet for aviation materials to be indexed and disseminated through an efficient medium. Publications are welcome in all aspects of aviation. Publication formats may include, but are not limited to, conference proceedings, bibliographies, research reports, manuals, technical reports, and other documents that should be archived and indexed for future reference by the aviation and world wide communities. The Conference proceedings of the 2003 Air Transport Research Society (ATRS) world conference, volume 5 is presented. The topics include: 1) The Temporal Configuration of Airline Networks in Europe; 2) Determination and Applications of Environmental Costs at Different Sized Airports-Aircraft Noise and Engine Emissions; 3) Cost Effective Measures to Reduce CO2 Emissions in the Air Freight Sector; 4) An Assessment of the Sustainability of Air Transport System: Quantification of Indicators; 5) Regulation, Competition and Network Evolution in Aviation; 6) Regulation in the Air: Price and Frequency Cap; 7) Industry Consolidation and Future Airline Network Structures in Europe; 8) Application of Core Theory to the U.S. Airline Industry; 9) Air Freight Transshipment Route Choice Analysis; 10) A Fuzzy Approach of the Competition on Air Transport Market; and 11) Developing Passenger Demand Models for International Aviation from/to Egypt: A Case Study of Cairo Airport and Egyptair.
Function approximation and documentation of sampling data using artificial neural networks.
Zhang, Wenjun; Barrion, Albert
2006-11-01
Biodiversity studies in ecology often begin with the fitting and documentation of sampling data. This study is conducted to make function approximation on sampling data and to document the sampling information using artificial neural network algorithms, based on the invertebrate data sampled in the irrigated rice field. Three types of sampling data, i.e., the curve species richness vs. the sample size, the curve rarefaction, and the curve mean abundance of newly sampled species vs.the sample size, are fitted and documented using BP (Backpropagation) network and RBF (Radial Basis Function) network. As the comparisons, The Arrhenius model, and rarefaction model, and power function are tested for their ability to fit these data. The results show that the BP network and RBF network fit the data better than these models with smaller errors. BP network and RBF network can fit non-linear functions (sampling data) with specified accuracy and don't require mathematical assumptions. In addition to the interpolation, BP network is used to extrapolate the functions and the asymptote of the sampling data can be drawn. BP network cost a longer time to train the network and the results are always less stable compared to the RBF network. RBF network require more neurons to fit functions and generally it may not be used to extrapolate the functions. The mathematical function for sampling data can be exactly fitted using artificial neural network algorithms by adjusting the desired accuracy and maximum iterations. The total numbers of functional species of invertebrates in the tropical irrigated rice field are extrapolated as 140 to 149 using trained BP network, which are similar to the observed richness.
Eight Year Climatologies from Observational (AIRS) and Model (MERRA) Data
NASA Technical Reports Server (NTRS)
Hearty, Thomas; Savtchenko, Andrey; Won, Young-In; Theobalk, Mike; Vollmer, Bruce; Manning, Evan; Smith, Peter; Ostrenga, Dana; Leptoukh, Greg
2010-01-01
We examine climatologies derived from eight years of temperature, water vapor, cloud, and trace gas observations made by the Atmospheric Infrared Sounder (AIRS) instrument flying on the Aqua satellite and compare them to similar climatologies constructed with data from a global assimilation model, the Modern Era Retrospective-Analysis for Research and Applications (MERRA). We use the AIRS climatologies to examine anomalies and trends in the AIRS data record. Since sampling can be an issue for infrared satellites in low earth orbit, we also use the MERRA data to examine the AIRS sampling biases. By sampling the MERRA data at the AIRS space-time locations both with and without the AIRS quality control we estimate the sampling bias of the AIRS climatology and the atmospheric conditions where AIRS has a lower sampling rate. While the AIRS temperature and water vapor sampling biases are small at low latitudes, they can be more than a few degrees in temperature or 10 percent in water vapor at higher latitudes. The largest sampling biases are over desert. The AIRS and MERRA data are available from the Goddard Earth Sciences Data and Information Services Center (GES DISC). The AIRS climatologies we used are available for analysis with the GIOVANNI data exploration tool. (see, http://disc.gsfc.nasa.gov).
Empirical downscaling of daily minimum air temperature at very fine resolutions in complex terrain
Zachary A. Holden; John T. Abatzoglou; Charles H. Luce; L. Scott Baggett
2011-01-01
Available air temperature models do not adequately account for the influence of terrain on nocturnal air temperatures. An empirical model for night time air temperatures was developed using a network of one hundred and forty inexpensive temperature sensors deployed across the Bitterroot National Forest, Montana. A principle component analysis (PCA) on minimum...