Characterization of Publication Rotogravure Press Emission Rates and Compositions

2001 ◽  
Vol 16 (4) ◽  
pp. 471-481 ◽  
Author(s):  
R. A. Wadden ◽  
Maryann Suero ◽  
L. M. Conroy ◽  
J. E. Franke ◽  
P. A. Scheff
Keyword(s):  
Emission Rates

Emission Rates and Characterization of Aerosols Produced During the Spreading of Dewatered Class B Biosolids

2007 ◽  
Vol 41 (10) ◽  
pp. 3537-3544 ◽  
Author(s):  
Tania Paez-Rubio ◽  
Abel Ramarui ◽  
Jeffrey Sommer ◽  
Hua Xin ◽  
James Anderson ◽  
...  
Keyword(s):  
Emission Rates ◽  
Class B

Characterization of organic, metal and trace element PM2.5 species and derivation of freeway-based emission rates in Los Angeles, CA

2012 ◽  
Vol 435-436 ◽  
pp. 159-166 ◽  
Author(s):  
James W. Liacos ◽  
Winnie Kam ◽  
Ralph J. Delfino ◽  
James J. Schauer ◽  
Constantinos Sioutas
Keyword(s):  
Los Angeles ◽  
Trace Element ◽  
Emission Rates ◽  
Organic Metal

scholarly journals Characterization of PM10 Emission Rates from Roadways in a Metropolitan Area Using the SCAMPER Mobile Monitoring Approach

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1332
Author(s):  
Dennis R. Fitz ◽  
Kurt Bumiller
Keyword(s):  
Metropolitan Area ◽  
Emission Rate ◽  
Emission Rates ◽  
Mobile System ◽  
The Road ◽  
Dust Generation ◽  
Significant Difference ◽  
Sand And Gravel ◽  
Pm10 Emission

The SCAMPER mobile system for measuring PM10 emission rates from paved roads was used to characterize emission rates from a wide variety of roads in the Phoenix, AZ metropolitan area. Week-long sampling episodes were conducted in March, June, September, and December. A 180 km-long route was utilized and traveled a total of 18 times. PM10 emission rate measurements were made at 5-second resolution for over 3200 km of roads with a precision of approximately 25%. The PM10 emission rates varied by over two orders of magnitude and were generally low unless the road was impacted with dust deposited by activities such as construction, sand and gravel operations, agriculture, and vehicles traveling on or near unpaved shoulders and roads. The data were tabulated into averages for each of 67 segments that the route was divided into. The segment-averaged PM10 emission rates ranged from zero to 2 mg m−1, with an average of 0.079 mg m−1. There was no significant difference in emission rates between seasons. There was a major drop in emission rates over a weekend, when dust generation activities such as construction are expected to be much reduced. By Monday, the PM10 emission rates had risen to the levels of the previous Friday. This indicates that roads quickly reach an equilibrium PM10 generating potential.

scholarly journals The Potential of Low-Cost Tin-Oxide Sensors Combined with Machine Learning for Estimating Atmospheric CH4 Variations around Background Concentration

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 107
Author(s):  
Rodrigo Rivera Martinez ◽  
Diego Santaren ◽  
Olivier Laurent ◽  
Ford Cropley ◽  
Cécile Mallet ◽  
...  
Keyword(s):  
Machine Learning ◽  
Tin Oxide ◽  
Oil And Gas ◽  
Spatial Scales ◽  
Low Cost ◽  
Learning Model ◽  
Background Concentration ◽  
Emission Rates ◽  
Machine Learning Model

Continued developments in instrumentation and modeling have driven progress in monitoring methane (CH4) emissions at a range of spatial scales. The sites that emit CH4 such as landfills, oil and gas extraction or storage infrastructure, intensive livestock farms account for a large share of global emissions, and need to be monitored on a continuous basis to verify the effectiveness of reductions policies. Low cost sensors are valuable to monitor methane (CH4) around such facilities because they can be deployed in a large number to sample atmospheric plumes and retrieve emission rates using dispersion models. Here we present two tests of three different versions of Figaro® TGS tin-oxide sensors for estimating CH4 concentrations variations, at levels similar to current atmospheric values, with a sought accuracy of 0.1 to 0.2 ppm. In the first test, we characterize the variation of the resistance of the tin-oxide semi-conducting sensors to controlled levels of CH4, H2O and CO in the laboratory, to analyze cross-sensitivities. In the second test, we reconstruct observed CH4 variations in a room, that ranged from 1.9 and 2.4 ppm during a three month experiment from observed time series of resistances and other variables. To do so, a machine learning model is trained against true CH4 recorded by a high precision instrument. The machine-learning model using 30% of the data for training reconstructs CH4 within the target accuracy of 0.1 ppm only if training variables are representative of conditions during the testing period. The model-derived sensitivities of the sensors resistance to H2O compared to CH4 are larger than those observed under controlled conditions, which deserves further characterization of all the factors influencing the resistance of the sensors.

Chemical composition and volatility distribution of SOA formed by ozonolysis of β-caryophyllene between 213-313 K

2020 ◽  
Author(s):  
Linyu Gao ◽  
Magdalena Vallon ◽  
Junwei Song ◽  
Wei Huang ◽  
Thomas Leisner ◽  
...  
Keyword(s):  
Significant Contribution ◽  
Basis Set ◽  
Emission Rates ◽  
Particle Phase ◽  
Reaction Products ◽  
Iodide Ions ◽  
Phase Partitioning ◽  
Aerosol Mass ◽  
Different Temperatures

<p>β-Caryophyllene is the most common and abundant of the sesquiterpenes emitted into the atmosphere (Duhl et al., 2008). Although sesquiterpene emission rates were estimated to be only 9–16% of the total terpene emissions (Duhl et al., 2008), they are more reactive and larger in size than monoterpenes. Consequently, their aerosol mass yields are large and result in a significant contribution to the SOA budget in the atmosphere (Tasoglou and Pandis, 2015). Therefore, we studied the composition of both gas and particle phases as well as phase partitioning of SOA from ozonolysis of β-caryophyllene in presence and absence of NOx at five temperatures (213 K, 243 K, 273 K, 298 and 313 K) in the AIDA aerosol simulation chamber. This work focusses on the characterization of the SOA by mass spectrometry employing a FIGAERO-HR-TOF-CIMS operated with iodide ions and a HR-TOF-AMS (both Aerodyne Inc.). Particle phase analysis shows three groups of compound masses with m/z 240-400, (C<sub>5-16</sub>),  (m/z 400-560, (C<sub>20-34</sub>), and m/z 560-680, (C<sub>35-40</sub>) classified as monomers, dimers, and trimers, respectively.  Trimeric compounds were observed preferentially in SOA formed at higher temperatures (273 K, 298 K, 313 K), while only monomeric and dimeric compounds were detected at lower temperatures (243 K and 213 K). Interestingly, dimeric compounds, including C<sub>x</sub>H<sub>y</sub>O<sub>z</sub> and C<sub>x</sub>H<sub>y</sub>O<sub>z</sub>N<sub>1</sub>, contribute more to SOA mass for the lower temperatures. Comparing volatility distributions for the five different temperatures using the Volatility Basis Set (VBS) and thermal desorption information from FIGAERO-CIMS (298-473 K) we find more compounds with lower volatility for lower SOA formation temperatures. This contribution will discuss the volatility distributions obtained with and without NOx as well as the abundance of specific reaction products.</p>

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