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75 results for “Emission Measurements”
Thermal infrared emissivity spectral library of silicates measured under the Mercury simulated environment
<p>This is the thermal emissivity spectral library of silicates measured as a function of temperature under Mercury simulated environment. Data is measured at the Planetary Spectroscopy Laboratory (PSL), Institute of Planetary Research, German Aerospace Center (DLR), Berlin. The spectral library will be used for mineral identification of Mercury surface using MERTIS datasets. The manuscript related to this work is submitted to Icarus on the title "<strong>Thermal Infrared Spectroscopy (7-14 µm) of Silicates under Simulated Mercury Daytime Surface Conditions and their Detection: Supporting MERTIS onboard the BepiColombo Mission".</strong></p>
Dataset of vehicle emission measurements in real-world subfreezing winter conditions
<p>Dataset of vehicle emission measurements in real-world subfreezing winter conditions. Measured by chasing the measured vehicle. See Info.txt for description of the data.</p>
Effective realization of abatement measures can reduce HFC-23 emissions
<p>Atmospheric observations (mole fractions) of halogenated greenhouse gases (HFC-23 (CHF<sub>3</sub>), PFC-318 (c-C<sub>4</sub>F<sub>8</sub>), HCFC-22 (CHClF<sub>2</sub>), HCFC-21 (CHCl<sub>2</sub>F), HFC-4310mee (C<sub>5</sub>H<sub>2</sub>F<sub>10</sub>), HFC-161 (C<sub>2</sub>H<sub>5</sub>F)) at the tall tower site at Cabauw, the Netherlands (51.972 °N, 4.927 °E, altitude -0.7 m a.s.l., 207 m a.g.l.), for the duration of a tracer (HFC-161) release experiment (17.06.2022 – 07.08.2022) within an extended (19.11.2021 – 7.8.2022) measurement campaign of halogenated greenhouse gases (>60 substances) at the Cabauw tall tower site. The measurements were conducted using a Medusa pre-concentration unit, coupled to gas chromatography and mass spectrometry (GC-MS), as is used within the global AGAGE network (<a href="https://agage.mit.edu/">https://agage.mit.edu/</a>). The HFC-161 tracer was released at 22 km distance from the Cabauw tall tower site, at 4 m a.s.l., 10 m a.g.l, at various flow rates. HFC-161 mole fractions are provided as the measured mole fractions and as the measured mole fractions normalised to the set tracer release flow rates.</p> <p>In addition, a subset of the above-described data is provided. This was used to assess the emissions of the above listed halogenated greenhouse gases from an industrial factory, by reference to the released HFC-161 tracer.</p> <p>The data are related to an article in Nature (https://doi.org/10.1038/s41586-024-07833-y).</p>
Nocturnal Light Emitting Diode Induced Fluorescence (LEDIF): A new technique to measure the chlorophyll a fluorescence emission spectral distribution of plant canopies in situ
<p>This repository contains data reported in the below study:</p> <p>Atherton, J., Liu, W. and Porcar-Castell, A., 2019. Nocturnal Light Emitting Diode Induced Fluorescence (LEDIF): A new technique to measure the chlorophyll a fluorescence emission spectral distribution of plant canopies in situ. <em>Remote Sensing of Environment</em>.</p> <p>Each text file contains the data-set used to produce the relevant figure (see file name). You can find the data to produce A.4. online at https://avaa.tdata.fi/web/smart/smear/ </p> <p>Please pay attention to the following before using this data.</p> <ol> <li><strong>Figure2_lampRadPanel_Wm2srnm.txt</strong>: Note that the shapes are of interest here. The magnitude is not the same as the incident light at top of canopy, as these spectra were measured in a laboratory. See paper section A.1. for more details. </li> <li><strong>Figure3_LEDIFspectra_Wm2srnm.txt</strong>: This data contains the whole observed spectrum including the non-fluorescence regions, which were saturated (warped) in the visible. The fluorescence region is approximately > 650 nm. </li> <li><strong>Figure4_AQYspectra_nm.txt</strong>: As with Figure3 the whole spectrum is included here.</li> <li><strong>FigureA3_repLEDIFspectra_[pmay/psep/usep]._nm.txt</strong>: Data from which the mean spectra (Figure3) were calculated, including the uncorrected red spectra. I have split these by canopy type to avoid name conflicts.</li> </ol> <p> </p>
Validation of Emission Spectroscopy Gas Temperature Measurements Using a Standard Flame Traceable to the International Temperature Scale of 1990 (ITS-90)
<p>Data underpinning the associated publication (https://doi.org/10.1007/s10765-019-2557-6) on accurate traceable measurement of post-flame temperatures.</p>
Measurements of savanna landscap fire emission factors for CO2, CO, CH4 and N2O using a UAV-based sampling methodology
<p>This dataset contains direct measurements of biomass burning emission factors for CO<sub>2</sub>, CO, CH<sub>4</sub> and N<sub>2</sub>O. It includes over 4500 EF bag measurements sampled using an unmanned aerial system (UAS), and measured fuel parameters and fire severity proxies during 129 individual fires. The measurements cover a variety of savanna ecosystems in Brazil, Australia, Botswana, Zambia, South-Africa and Mozambique under different seasonal conditions, sampled over the course of six fire seasons between 2017 and 2022. The table in the included word file explains the individual columns in the excell file. </p> <p> </p>
THE StellaR PAth WP1: Sun-as-a-star plasma Emission Measure Distributions
<p>This folder contains a set of plasma Emission Measure Distributions (EMDs) vs. temperature, derived from observations of the solar corona with the Soft X-ray Telescope (SXT) on board the solar satellite Yohkoh, and the prescription to build EMDs for coronae of solar-type stars with different activity levels, including both quiescent and flaring components. For details read the Description PDF file.</p>
Data presented in González-Flórez et al. 2023 "Insights into the size-resolved dust emission from field measurements in the Moroccan Sahara", Atmos. Chem. Phys.
<p>Meteorological, dust and saltation data used in González-Flórez et al., 2023. Data are based on measurements taken during an intensive dust field campaign conducted in the context of the FRontiers in dust minerAloGical coMposition and its Effects upoN climaTe (FRAGMENT) project. The campaign took place in September 2019 in a small ephemeral lake, locally named "L'Bour", located in the Lower Drâa Valley in Morocco. The description of the data is provided below:</p> <p>- t.nc: time series of temperature measured with four aspirated shield temperature sensors (Campbell Scientific 43502 fan-aspirated shield with 43347 RTD Temperature probe) placed at heights of 1m, 2m, 4m and 8m.</p> <p>- t005.nc time series of temperature measured with a temperature and relative humidity probe (Campbell Scientific HC2A-S3) at 0.5m height.</p> <p>- rh005.nc: time series relative humidity measured with a temperature and relative humidity probe (Campbell Scientific HC2A-S3) at 0.5m height.</p> <p>- wspd.nc: time series of wind speed measured with five 2-D sonic anemometers (Campbell Scientific WINDSONIC4-L) placed at heights of 0.4m, 0.8m, 2m, 5m and 10m.</p> <p>- sdir.nc: time series of wind direction measured with five 2-D sonic anemometers (Campbell Scientific WINDSONIC4-L) placed at heights of 0.4m, 0.8m, 2m, 5m and 10m.</p> <p>- radout.nc: time series of outgoing long wave radiation measured with a four-component net radiometer (Campbell Scientific NR01-L radiometer) placed at 1.5m height.</p> <p>- p015.nc: times series barometric pressure measured with a barometer (Campbell Scientific CS106) at around 1.5m height.</p> <p>- u_star_law.nc: time series friction velocity calculated through the law of the wall method.</p> <p>- z0_law.nc: time series of roughness length calculated through the law of the wall method.</p> <p>- zeta_law.nc: time series of dimensionless height, zref/L, where zref is the reference height (zref=2m) and L is the Obukhov length calculated through the law of the wall method.</p> <p>- psd_lower_15avg_20190904_000000_integrated_bins.nc: time series of 15-min average number concentrations in integrated size bin resolution measured with an optical particle counter (Fidas 200S, Palas GmbH) at ~1.8m height.</p> <p>- psd_upper_15avg_20190904_000000_integrated_bins.nc: time series of 15-min average number concentrations in integrated size bin resolution measured with an optical particle counter (Fidas 200S, Palas GmbH) at ~3.5m height and corrected for systematic bias based on an intercomparison between the two Fidas at the end of the campaign.</p> <p>- diff_flux_nb_15avg_20190904_000000_integrated_bins.nc: time series of 15-min average number diffusive flux calculated using the flux-gradient method.</p> <p>- q_15avg.nc: time series of 15-min average saltation flux calculated based on measurements with optical gate devices at heights of 0.05m, 0.15m and 0.3m as part of the Standalone AeoliaN Transport Real-time Instrument (SANTRI, Desert Research Institute).</p> <p>- geometric_diameters_integrated_size_bins.csv: containing the minimum, maximum and mean logarithmic optical diameter of the integrated size bins.</p> <p>- optical_diameters_integrated_size_bins: containing the minimum, maximum and mean logarithmic geometric diameter of the integrated size bins.</p> <p>SANTRI data were processed by Martina Klose (<a href="mailto:martina.klose@kit.edu">martina.klose@kit.edu</a>) and the rest by Cristina González Flórez (<a href="mailto:cristina.gonzalez@bsc.es">cristina.gonzalez@bsc.es</a>). Please, cite González-Flórez et al. (2023, ACP) if you use these data. If the data become the key main component of a paper then co-authorship may be offered. Contact Carlos Pérez García-Pando (<a href="mailto:carlos.perez@bsc.es">carlos.perez@bsc.es</a>) if more details are needed.</p> <p>This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 773051, FRAGMENT).</p>
Measurement report: Characterization of uncertainties of fluxes and fuel sulfur content from ship emissions at the Baltic Sea
<p>This data submission is connected to a scientific paper submitted to<br> Atmospheric Chemistry and Physics ("Measurement report: Characterization of uncertainties of fluxes and fuel sulfur content from ship emissions at the Baltic Sea" by Walden et al.). It consists of measurement results conducted beside the ship routs at the Baltic Sea near Helsinki, Finland. The gaseous and particle concentrations were measured along with the meteorological parameters, and the fluxes were calculated by the micrometeorological methods. The content of sulfur in the marine fuel, FSC, used by the passing ships was also calculated. We paid attention to calculate the uncertainties of the measurement results, both for the fluxes and for the FSC.</p> <p>The released data of:<br> 1. Gases, particles and met data (SO<sub>2</sub>, NO, NO<sub>2</sub>, O<sub>3</sub>, CO<sub>2</sub>, and N<sub>tot</sub> (number concentration of nanoparticles) as minute values. </p> <p>Data_ACP_Fig4_acbd.xlsx.</p> <p> <br> 2. Size distribution of nanoparticles (number concentration of nanoparticles at size class). Data_ACP_Fig6.xlsx</p> <p> <br> 3. Profiles of 30 min averages of gases, nanoparticles and meteorological parameters (SO<sub>2</sub>, NO, NO<sub>2</sub>, O<sub>3</sub>, CO<sub>2</sub>, and N<sub>tot</sub> (number concentration of nanoparticles), wind direction and wind speed, friction velocity, stability parameter and Monin-Obukhov length. Calculated values of atmospheric turbulence parameters and calculated fluxes of CO2 and nanoparticles by gradient and/or eddy covariance method.</p> <p>Data_ACP_Fig8_abcd_Fig9_abcd.xlsx<br> <br> 4. CO2 fluxes by Eddy covariance method from land based and sea based measurements. Concentration of CO2 in seawater and in air.</p> <p>Data_ACP_Fig10_ab.xlsxEngl</p>
Ammonia emission measurements of an intensively grazed pasture - Dataset
<p>Dataset presented and referenced in the corresponding Biogeosciences publication by Voglmeier et al. (2018) [see Related identifiers]. The dataset results from a field experiment in Posieux, Switzerland. During that experiment ammonia emissions of two pasture systems were measured over an entire grazing season in 2016. The spreadsheet file contains half-hourly values of measured ammonia concentration data, computed ammonia emissions, weather and turbulence data. Additionally the calculated nitrogen in the excretion of the cows and the grazing management is given. Detailed information on the measurement methods and the data evaluation is presented in Voglmeier et al. (2018).</p>
Hourly U.S. Building Electricity Use, Cost, and Emissions Baselines to Support Time-Sensitive Analyses of Energy Efficiency and Flexibility Measures
<p>These data underpin an analysis of the time-sensitive impacts of energy efficiency and flexibility measures in the U.S. building sector using Scout (<a href="https://scout.energy.gov">scout.energy.gov</a>), a reproducible and granular model of U.S. building energy use developed by the U.S. national labs for the U.S. Department of Energy's Building Technologies Office.</p> <p>The analysis applies sub-annual adjustments to U.S. baseline building energy use, cost, and emissions in order to characterize how these metrics vary across hour of the day, season, and geographic region in the U.S. building sector. These adjustments are based on daily energy load, price, and emissions shapes from various data sources and are used to re-apportion baseline energy, cost, and emissions totals from <a href="https://www.eia.gov/outlooks/aeo/data/browser/%20/%20%7b%20/%20# \ }/?id=2-AEO2018 \ { \ & \ }cases=r ef2018 \ { \ & \ }sourcekey=0">EIA's Annual Energy Outlook (AEO) Reference Case projections</a> across all hours of a year. The resulting sub-annual baselines are specified by building sector, end use, region, and season and can be used in analyses of building efficiency and flexibility measures to quantify their time-sensitive impacts at the national scale. Analyses of these data demonstrate that energy efficiency measures continue to show strong value under a time-sensitive framework while the value of flexibility depends on assumed electricity rates, measure magnitude and duration, and the amount of savings already captured by efficiency.</p> <p>The data uploaded below include CSV files that show hourly energy use, cost, and emissions totals for the U.S. building sector as well as by end-use, region, and season. An additional CSV includes residential and commercial price intensities (USD/quad) for all hours of the day based on different time-of-use (TOU) rate data from the U.S. Utility Rate Database (URDB). Further detail on each of these CSVs is given below:</p> <ul> <li>'TSV_baseline_totals.csv': this file shows hourly total energy, cost, and emissions estimates for commercial and residential buildings in 2018 and 2030. It presents these estimates in Quads (source), Quads (site), and TWh (site). For the cost totals, it presents two estimates for each year and building sector, including one using the median TOU rate from the URDB and one using the average retail rate for the corresponding building sector. For converting source energy to site, total delivered electricity and electricity-related losses data for the residential and commercial sector are drawn from <a href="https://www.eia.gov/outlooks/aeo/data/browser/#/?id=2-AEO2018&sourcekey=0">AEO Summary Table A2</a>.</li> <li>'TSV_baseline_end-use.csv': this file shows hourly energy, cost, and emissions estimates for commercial and residential buildings in 2018 and 2030 broken out by building end-use. It presents totals in terms of both source and site energy as above and presents cost totals based on the median TOU rate for each building sector from the URDB.</li> <li>'TSV_baseline_region.csv': this file shows hourly energy, cost, and emissions estimates for commercial and residential space heating and cooling end uses in 2018 and 2030 for each <a href="https://www.eia.gov/consumption/residential/maps.php">American Institute of Architects (AIA) climate zone</a>. It presents totals in terms of both source and site energy as above and presents cost totals based on the median TOU rate for each building sector from the URDB.</li> <li>'TSV_baseline_region_season.csv': this file shows a similar disaggregation of the data as ‘TSV_baseline_region.csv’, but it further disaggregates results by season. The seasonal definitions are as follows: 'intermediate' (October to November; March to April), 'winter' (November to February), and 'summer' (May to September).</li> <li>'TSV_annual_price_intensities.csv': this file presents annual hourly price intensities for the commercial and residential building sectors in 2018 and 2030 based on different TOU rate data from the URDB. Three different rate structures are included for each building sector, and these are the 5th, 50th, and 95th percentile of all existing commercial and residential TOU rates in the URDB in terms of their peak to off-peak price ratio.</li> </ul>
Setting up Methane Mitigation Measures for Indian Rice Fields: Representative Emissions and New Interpretations
<p>Setting up Methane Mitigation Measures for Indian Rice Fields: Representative Emissions and New Interpretations</p> <p>Fida Mohammad Sahil, Mukund Narayanan and Idhayachandhiran Ilampooranan*</p> <p>Department of Water Resources Development and Management, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India – 247667.</p> <p>*Corresponding Author (Email: idhaya@wr.iitr.ac.in)</p> <p>This repository contains the code and datasets generated in this study accepted in Global Biogeochemical Cycles Journal.</p>
Data for Measurement report: Air pollution emission factors of inland river ships under compliance with the 10 parts per million limit for sulfur content in fuel
<p>Since July 1, 2019, China’s domestic diesel fuel has been limited to 10 ppm of sulfur. Hence, to explore the applicability of the “sniffer” method and the distribution and level of inland river ships (IRSs) emission factors (EFs) under this limitation, we installed “sniffer” monitoring equipment, from August 2020 to June 2022, at the Gezhou Dam of the Yangtze River in China and monitored emissions from 8,238 IRSs in total passing through the lock. We partnered with the maritime department to select 100 ships passing through the lock to extract fuel oilsamples for direct fuel sulfur content detection, which determined the true fuel sulfur content of the passing ships. fuel sulfur content.</p> <p>The “sniffer” monitoring equipment included SO<sub>2</sub>, CO<sub>2</sub>, NO, and NO<sub>2</sub> gas sensors, PM<sub>2.5</sub> and PM<sub>10</sub> particulate matter sensors, as well as wind speed, wind direction, temperature, humidity, and pressure sensors.</p>
Tables and Data for "Synthesis of Satellite and Surface Measurements, Model Results, and FRAPPÉ Study Findings to Assess the Impacts of Oil and Gas Emissions Reductions on Maximum Ozone in the Denver Metro and Northern Front Range Region in Colorado"
<p>These are data sets and tables used in the paper "Synthesis of Satellite and Surface Measurements, Model Results, and FRAPPÉ Study Findings to Assess the Impacts of Oil and Gas Emissions Reductions on Maximum Ozone in the Denver Metro and Northern Front Range Region in Colorado" to be submitted to Earth and Space Science. The monitor site 2016 and 2017 counts files have gridded HYSPLIT back trajectory counts for the 4 highest ozone concentration days at each site, as described in the manuscript.</p>
First Atmospheric Measurements and Emission Estimates of HFO-1336mzz(Z)
<p>Atmospheric measurement data (mole fractions) for HFO-1336mzz(Z) (((<em>Z</em>)-1,1,1,4,4,4-hexafluoro-2-butene, <em>cis</em>-CF<sub>3</sub>CH=CHCF<sub>3</sub>). The data are related to article in ES&T (<a href="https://doi.org/10.1021/acs.est.3c01826">https://doi.org/10.1021/acs.est.3c01826</a>). Observations were made at the sites Beromünster (CH), Sottens (CH), Dübendorf (CH), Jungfraujoch (CH), and Cabauw (NL). Measurements were conducted using Medusa pre-concentration units coupled to gas chromatography and mass spectrometry (GC-MS), as is used within the global AGAGE network.</p>
Metadata with submitted Emission Control Science and Technology Journal manuscript Traceable uncertainty of exhaust flow meters embedded in portable emission measurement systems
<p>Metadata with submitted Emission Control Science and Technology Journal <em>Traceable uncertainty of exhaust flow meters embedded in portable emission measurement systems</em></p> <p>Link to article: https://link.springer.com/article/10.1007/s40825-025-00260-z</p>
Data of normal spectral emissivity measurements for Ta, Mo, W and Nb
<p>Data aquired during my master thesis about the normal spectral emissivty of Ta, Mo, W and Nb measured with an ohmic pulse heating apparatus and a us-DOAP</p>
Resazurin-based time-kill assay in Acinetobacter baumannii AB074. Fluorescence measurement data for excitation 544 nm, emission 590 nm, gain 1000.
<p>There were 21 groups: 3 groups of transferrin alone in 3 different concentrations (1/3, 1, and 3 times of its MIC); 4 groups of antibiotics alone (ciprofloxacin and meropenem in 1/3 and 1 MIC concentration each), 6 combo groups for ciprofloxacin and 6 combo groups for meropenem, 1 group of positive control with bacteria but without any drug and 1 group of negative control without bacteria, with RPMI only. 20 µL of 0.1% aqueous resazurin solution was added to each well and the plate was incubated at 37°C without shaking for 24 hours. After incubation fluorescence was measured (excitation 544 nm, emission 590 nm) at 0h, 1h, 2h, 4h, 6h, 8h, and 24 hrs using the FLUOstar Omega plate reader (BMG LABTECH GmbH, Germany). Plate layouts may vary.</p> <p>For more information contact author.</p>
Research data on pass-by sound emission measurements from train units for D7.4-Susteren pilot
<p>This dataset compiles sample measurement results for the N-RSD rail pilot from D7.4-Susteren pilot project report available once approved by the EC at https://cordis.europa.eu/project/id/860441/results. The data includes train unit subtypes, pass-by sound levels, speed, weight, wheel flat indication, brake type information and a sound emission rating. </p>
Data archive for the peer-reviewed journal article "Online measurements during simulated atmospheric aging track the strongly increasing oxidative potential of complex combustion aerosols relative to their primary emissions"
<p>This data archive accompanies the article "Online measurements during simulated atmospheric aging track the strongly increasing oxidative potential of complex combustion aerosols relative to their primary emissions", which was accepted in November 2024 in the peer-reviewed journal Environmental Science and Technology Letters. The data archive contains the processed OP_DTT, PM loading, oxidant level, and elemental ratio measurements presented in this journal article. </p>
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