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40 results for “air monitoring”
SOC Fuel, Steam, and Air starvation monitoring using advanced tools
<p>Polarisation, impedance and THD data of fuel, steam, and air starvation of SOC with different sensitivity analyses</p>
City scale particulate matter monitoring using LoRaWAN based air quality IoT devices
<p>Air Quality (AQ) is a very topical issue for many cities and has a direct impact on citizen health. The AQ of a large UK city is being investigated using low-cost Particulate Matter (PM) sensors, and the results obtained by these sensors have been compared with government operated AQ stations. In the first pilot deployment six AQ Internet of Things (IoT) devices have been designed and built, each with four different low-cost PM sensors, and they have been deployed at two locations within the city. These devices are equipped with LoRaWAN wireless network transceivers to test city scale Low-Power Wide Area Network (LPWAN) coverage. The study concludes that i) the physical device developed can operate at a city scale ii) some low-cost PM sensors are viable for monitoring AQ and for detecting PM trends iii) LoRaWAN is suitable for city scale sensor coverage where connectivity is an issue. Based on the findings from this first pilot project a larger LoRaWAN enabled AQ sensor network is being deployed across the city of Southampton in the UK.</p>
Dataset for "Improving data quality of low-cost light-scattering PM sensors: Towards automatic air quality monitoring in urban environments"
<p>The dataset contains the data used in the article "Improving data quality of low-cost light-scattering PM sensors: Towards automatic air quality monitoring in urban environments".</p> <p>A low-cost monitoring system composed of 14 monitoring stations was positioned at the official monitoring station of Torino Rubino in the city of Turin (Italy). The official station is managed by the environmental agency ARPA Piemonte.</p> <p>Each low-cost station contains four low-cost light-scattering PM sensors (Honeywell HPMA115S0-XXX), one temperature and relative humidity sensor (DHT22), and one atmospheric pressure sensor (BME/BMP280).<br>The sampling time of the PM sensors was set to one second, while the other sensors generated measurements every 3-4 seconds.</p> <p>The official monitoring station uses both a gravimetric and a beta attenuation instrument for measuring PM.</p> <p>The data contained in this dataset was collected from October 2020 to November 2021. It contains the PM2.5, relative humidity, and temperature measurements of the low-cost monitoring system and the official measurements of the beta attenuation device.</p> <p>Measurements of low-cost sensors are expressed in UTC, while official measurements are expressed in UTC+1.</p> <p>Official PM measurements can be also found at https://aria.ambiente.piemonte.it/qualita-aria/dati.</p>
Continuous air pollution monitoring data for the Kanto region (Japan) derived from original observations by the National Institute for Environmental Studies Environmental Observatory (https://tenbou.nies.go.jp/download/).
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Data from: Mobile phones as monitors of personal exposure to air pollution: is this the future?
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Up in the air: threats to Afromontane biodiversity from climate change and habitat loss revealed by genetic monitoring of the Ethiopian Highlands bat
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A New Portable Monitor for Measuring Odorous Compounds in Oral, Exhaled and Nasal Air
ClinicalTrials.gov study NCT01139073. IPD Sharing: Not stated. Countries: 0. Publications: 1.
A Study Evaluating the Use of an Indoor Air Quality Monitor to Promote a Smoke-free Home
ClinicalTrials.gov study NCT06693700. IPD Sharing: YES. Countries: 1. Publications: 0.
Hyperlocal monitoring of traffic-related air pollution to assess near-term impacts of sustainable transportation interventions
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Monitoring the intensity distribution of earth-air activity around the Mogao Grottoes
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Datasets used in Detecting Plumes in Mobile Air Quality Monitoring Time Series with Density-based Spatial Clustering of Applications with Noise v01
<p>This repository contains the following data sets related to Detecting Plumes in Mobile Air Quality Monitoring Time Series with DBSCAN published in . Please cite the following: .</p> <p>Validated_Data.csv: A .csv file containing the validation set used in the study. Column headings are the following:</p> <p>"Lat1": GPS latitude of car location in degrees.<br> "Long1": GPS longitude of car location in degrees.<br> "LST": Measurement time stamp. Time zone US/Central.<br> "BC": Black carbon measurements in ng/m^3<br> "CO2": Carbon dioxide measurements in ppm.<br> "UFP": Ultrafine particle count in particles/cc.<br> "NOx": Oxides of nitrogen, defined as the sum of NO and NO2, in ppb.<br> "Anomaly": What has been manually flagged as "Anomaly" (2) or "Normal" (1).<br> "Uniq_Fac": Factor from 1-30 mapping to different days of the campaign. For example, all measurements with Uniq_Fac = 1 belong to the same day.</p> <p>Labeled_DBSCAN_Anomalies.csv: A .csv file containing points labeled as anomalies by the DBSCAN algorithm described in the manuscript. Columns are the following.</p> <p>"BC": Black carbon measurement (ng/m^3)<br> "CO2": Carbon dioxide measurement (ppm)<br> "NOx": Oxides of nitrogen, defined as the sum of NO and NO2 (ppb)<br> "UFP": Ultrafine particle count (p/cc)<br> "Anomaly": Whether the DBSCAN algorithm has labeled this point as "Anomaly" (2) or "Normal" (1)<br> "Uniq_Fac": Factor spanning from 1-277 grouping measurements taken on separate days by car. E.g. all measurements with Uniq_Fac=1 were grouped and analyzed together.<br> "LST": Timestamp (US/Central)<br> "Road_Class": TigerLINE census road class designation for the given point. Possible road classes are S1100 - Primary Road, S1200 - Secondary Road, S1400 - Local Road, S1630 - Ramps, S1640 - Service Drives, S1730 - Private Roads<br> "X": Universal Transverse Mercator Easting for Zone 15N (m).<br> "Y": Universal Transverse Mercator Northing for Zone 15N (m).</p> <p>*_To_Be_Validated.csv: A series of files where * denotes the following.</p> <p>"DB": DBSCAN Algorithm<br> "QOR": QOR Algorithm<br> "QAND": QAND Algorithm<br> "Drew": Drewnick Algorithm</p> <p>Each file contains the following columns:</p> <p>"Lat1": GPS latitude of car location in degrees.<br> "Long1": GPS longitude of car location in degrees.<br> "LST": Measurement time stamp. Time zone US/Central.<br> "BC": Black carbon measurements in ng/m^3<br> "CO2": Carbon dioxide measurements in ppm.<br> "UFP": Ultrafine particle count in particles/cc.<br> "NOx": Oxides of nitrogen, defined as the sum of NO and NO2, in ppb.<br> "Anomaly": What has been flagged as "Anomaly" (2) or "Normal" (1).<br> "Uniq_Fac": Factor from 1-30 mapping to different days of the campaign. For example, all measurements with Uniq_Fac = 1 belong to the same day.</p>
Air Quality Monitoring and Health Surveillance of Workers in the Photocopier Units
ClinicalTrials.gov study NCT01289184. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Indoor Air Quality Monitoring and Impact on Children's Health
ClinicalTrials.gov study NCT06197477. IPD Sharing: NO. Countries: 1. Publications: 0.
Accuracy and Precision of the Continuous Glucose Monitoring System 'CareSens Air 3' in Adult Patients With T1DM
ClinicalTrials.gov study NCT07296276. IPD Sharing: NO. Countries: 1. Publications: 0.
Digital Air Leak Monitoring for Patients Undergoing Lung Resection
ClinicalTrials.gov study NCT01810172. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Use of the Operational Air Quality Monitor (AQM) for In-Flight Water Testing Project
<p>Currently, the Air Quality Monitor (AQM) on-board ISS provides specific information for a number of target compounds in the air. However, there is a significant subset of common target compounds between air and water.&nbsp; Naturally, the following question arises, &ldquo;Can the AQM be used for both air and water quality monitoring?&rdquo;&nbsp; Previous directorate-level IR&amp;D funding led to the development of a water sample introduction method for mass spectrometry using electro-thermal vaporization (ETV).&nbsp; This vaporization source allows analytes in water samples to enter the gas phase, where they can be analyzed using a variety of techniques.&nbsp; This project will focus on the integration of the ETV with a ground-based AQM.&nbsp; The capabilities of this integrated platform will be evaluated using a subset of toxicologically important compounds.</p><p>The ETV unit was constructed using two glass tubes and a nichrome ribbon powered by a programmable DC power supply (G W Instec, PSM-3004).&nbsp; The nichrome ribbon was threaded through two 3-mm wide, 1-cm-long slot cuts on the inner tube placed 1.5 cm past the inlet.&nbsp; The ribbon was held securely by compressing it between the inner tube and two halves of an outer glass tube.&nbsp; These halves were held together using a flexible metal clamp.&nbsp; Inside the inner tube the ribbon was slightly curved, and an indent (1 mm diameter) was made on its surface for depositing a measured liquid sample drop.&nbsp; The ribbon was positioned in the upper half of the inner tube in such a way that the edge of the ribbon faced the front (inlet) side of the ETV unit.&nbsp; Holes (1 mm diameter) were made on the outer and inner glass tubes for sample introduction and were aligned with the ribbon indent.</p><p>The viability of the ETV approach for the analysis of water analytes was demonstrated using a ground-based, laboratory scale analyzer (reference:&nbsp; Dwivedi, P. et al.&nbsp; &ldquo;Electro-Thermal Vaporization Direct Analysis in Real Time-Mass Spectrometry for Water Contaminant Analysis During Space Missions,&rdquo; Analytical Chemistry, 85, 9898-9906 (2013)).&nbsp; The work in this proposal will extend that effort and interface the ETV to a ground version of the current in-flight AQM.&nbsp; Liquid sample will be introduce via a pipet through the sample injection port and placed onto the nichrome ribbon heated to a set temperature by an external, programmable power supply.&nbsp; Upon vaporization of the water sample, the target analytes will be swept into the AQM Sample-In port using nitrogen carrier gas.&nbsp; A vapor-phase analysis can then be performed by the AQM to identify and quantify the target analytes in the water samples.&nbsp; Parameters to be optimized include water sample size, carrier gas sweep rate, and ribbon temperature.&nbsp; The operating parameters of the vapor-phase analysis performed by the AQM will also need to be modified for this type of sampling methodology.&nbsp; A simple two-position valve attached to the ETV and a diverter tube will allow for manual selection of either a water sample through the ETV or an air sample through the diverter tube.&nbsp; The primary objective of this effort is to evaluate the viability of the ETV with ground-based, flight hardware.&nbsp; A proof-of-concept unit capable of water and air analysis utilizing the ETV will be developed.&nbsp; The target water analytes to be used in this work will come from a list provided by the water SMEs in the Toxicology and Environmental Chemistry Laboratories at JSC.&nbsp; These analytes are commonly observed in the ground analysis of water samples from ISS.&nbsp; A preliminary engineering evaluation of this set-up could potentially be performed with the goal of formulating a viable plan of integrating the ETV to the control soft
NARSTO EPA_SS_HOUSTON TEXAQS2000 Washburn Tunnel Air Quality Monitoring Data
The NARSTO_EPA_SS_HOUSTON_TEXAQS2000_WB_TUNNEL data contain gas and particle phase measurements collected in a tunnel in the Houston area during the summer of 2000. The primary objective of this study was to provide data for estimating vehicular emission factors and composition profiles as part of the TexAQS2000 program. Measurements were collected on each day from August 29, 2000 (Tuesday) through September 1, 2000 (Friday). Sampling was conducted during the 1200 - 1400 CDT and 1600 - 1800 CDT time periods each day. Measurements collected during the study included nitrogen oxides, carbon dioxide, carbon monoxide, ammonia, fine particulate matter (PM2.5), and individual hydrocarbon species.The Houston Supersite is one of several Supersites that was established in urban areas within the United States by the U.S. Environmental Protection Agency (EPA) to better understand the measurement, sources, and health effects of suspended particulate matter (PM). The overall goals were to characterize the composition and identify the sources of particulate matter in Southeastern Texas, to develop and test new methods for characterizing fine particulate matter, and to collect data on the physical and chemical characterization of fine particulate matter that can be used to support exposure and health effects studies.NARSTO (formerly North American Research Strategy for Tropospheric Ozone) is a public/private partnership, whose membership spans government, the utilities, industry, and academe throughout Mexico, the United States, and Canada. The primary mission is to coordinate and enhance policy-relevant scientific research and assessment of tropospheric pollution behavior; activities provide input for science-based decision-making and determination of workable, efficient, and effective strategies for local and regional air-pollution management. Data products from local, regional, and international monitoring and research programs are available.
NARSTO EPA Supersite (SS) Houston, Texas Air Quality Study 2000 (TexAQS2000) Texas Natural Resource Conservation Commission (TNRCC) continuous ambient monitoring stations (CAMS) Air Quality Data
NARSTO_EPA_HOUSTON_TEXAQS2000_CAMS_DATA is the North American Research Strategy for Tropospheric Ozone (NARSTO) Environmental Protection Agency (EPA) Supersite (SS) Houston, Texas Air Quality Study 2000 (TexAQS2000) Texas Natural Resource Conservation Commission (TNRCC) continuous ambient monitoring stations (CAMS) Air Quality Data. This data set contains 5-minute air quality measurements collected in Texas during August and September 2000 at 85 CAMS during TEXAQS2000. Measurements include carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxide (NO), nitrogen dioxide (NO2), oxides of nitrogen (NOx), total reactive nitrogen species (NOy), ozone, particulate matter (PM) 2.5 mass, hydrogen sulfide (H2S), wind speed, wind direction, maximum wind gust, air temperature, dewpoint temperature, humidity, precipitation, surface pressure, radiation, and visibility. CAMS are operated by the Texas Commission on Environmental Quality (TCEQ), local city or county governments, or private monitoring networks. Important monitoring site information: The site information data table in each of the 85 data files may not contain the latest TCEQ site information. A companion file site information spreadsheet (.csv) that lists data for all 85 sites is the latest TCEQ site information. The site information data tables in the 85 data files will not be updated. The 85 site spreadsheet companion document is the official source of site data, and this data is listed in the TEXAQS2000 CAMS guide document.NARSTO, which has since disbanded, was a public/private partnership, whose membership spanned across government, utilities, industry, and academe throughout Mexico, the United States, and Canada. The primary mission was to coordinate and enhance policy-relevant scientific research and assessment of tropospheric pollution behavior; activities provide input for science-based decision-making and determination of workable, efficient, and effective strategies for local and regional air-pollution management. Data products from local, regional, and international monitoring and research programs are still available.
NARSTO Pacific 2001 Air Quality Study (PAC2001) Greater Vancouver Regional District (GVRD) and and Canadian Air and Precipitation Monitoring Network (CAPMoN) Supplemental Air Quality Data
NARSTO_PAC2001_GVRD_CAPMON_AIR_QUAL_DATA is the North American Research Strategy for Tropospheric Ozone (NARSTO) Pacific 2001 Air Quality Study (PAC2001) Greater Vancouver Regional District (GVRD) and and Canadian Air and Precipitation Monitoring Network (CAPMoN) Supplemental Air Quality Data product. Data was obtained from January 1, 2001 to January 1, 2002. Air quality monitoring data routinely collect by the GVRD CAPMoN during the sampling period of PAC2001, are included as supplemental data for PAC2001.The GVRD monitoring network of 20 sites continued operation during the PAC2001 field study period, with enhanced quality assurance (QA) and quality control (QC) activities. At all sites, meteorological measurements were carried out at a 5-min time resolution. At a few specially equipped sites, particle mass PM10 were measured using tapered element oscillating microbalances (TEOMs). The network data complements the special study sites and form a spatial distribution of the pollutants. CAPMoN is a non-urban air quality monitoring network with siting criteria designed to ensure that the measurement locations are regionally representative (not affected by local sources of air pollution).The objectives were to determine the spatial patterns and establish the temporal trends of pollutants related to acid rain; provide for long-range transport model evaluations and effects research (aquatic, terrestrial, building materials and health); ensure the compatibility of federal, provincial and U.S. measurements; and study atmospheric processes. Scientists involved with the measurement of atmospheric pollution in urban centers would consider most CAPMoN sites to be remote and pristine. There are currently 19 measurement sites in Canada and 1 in the U.S. The Saturna Island site is located in the PAC2001 area of interest. PAC2001 was conducted from 1 August to 31 September 2001 in the Lower Fraser Valley (LFV), British Columbia, Canada. The study consisted of individual research projects organized to address several issues on ambient particulate matter and ozone that are important to policy makers. A special issue of Atmospheric Environment [Vol. 38(34), Nov 2004] described specific study objectives (Li, 2004) and presented a series of results papers from the field study. The ground sampling sites during the study were (1) Cassiar Tunnel, (2) Slocan Park, (3) Langley Ecole Lochiel, (4) Sumas Eagle Ridge, and (5) Golden Ears Provincial Park. Aloft measurements were taken from a Convair 580 and a Cessna 188. Selected measurement data were compiled for each site and aircraft and are archived as site-specific data sets.North American Research Strategy for Tropospheric Ozone (NARSTO), which has since disbanded, was a public/private partnership, whose membership spanned across government, utilities, industry, and academe throughout Mexico, the United States, and Canada. The primary mission was to coordinate and enhance policy-relevant scientific research and assessment of tropospheric pollution behavior; activities provide input for science-based decision-making and determination of workable, efficient, and effective strategies for local and regional air-pollution management. Data products from local, regional, and international monitoring and research programs are still available.
Air Quality Monitoring Protocol Amendment
<p>PM2.5 concentrations reported under standard and actual conditions</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.