atmospheric monitoring
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2021 ◽  
Vol 5 (1) ◽  
pp. 78
Author(s):  
Juan Diaz ◽  
Zach Agioutantis ◽  
Dionissios T. Hristopulos ◽  
Steven Schafrik

Underground coal mining Atmospheric Monitoring Systems (AMS) have been implemented for real-time or near real-time monitoring and evaluation of the mine atmosphere and related parameters such as gas concentration (e.g., CH4, CO, O2), fan performance (e.g., power, speed), barometric pressure, ambient temperature, humidity, etc. Depending on the sampling frequency, AMS can collect and manage a tremendous amount of data, which mine operators typically consult for everyday operations as well as long-term planning and more effective management of ventilation systems. The raw data collected by AMS need considerable pre-processing and filtering before they can be used for analysis. This paper discusses different challenges related to filtering raw AMS data in order to identify and remove values due to sensor breakdowns, sensor calibration periods, transient values due to operational considerations, etc., as well as to homogenize time series for different variables. The statistical challenges involve the removal of faulty values and outliers (due to systematic problems) and transient effects, gap-filling (by means of interpolation methods), and homogenization (setting a common time reference and time step) of the respective time series. The objective is to derive representative and synchronous time series values that can subsequently be used to estimate summary statistics of AMS and to infer correlations or nonlinear dependence between different data streams. Identification and modeling of statistical dependencies can be further exploited to develop predictive equations based on time series models.


2021 ◽  
Author(s):  
Wei Li ◽  
Han Wang ◽  
Jing Wu ◽  
Baocheng Yu ◽  
Wenxia Xu ◽  
...  

Chemosphere ◽  
2021 ◽  
Vol 279 ◽  
pp. 130631
Author(s):  
Akane Yamakawa ◽  
David Amouroux ◽  
Emmanuel Tessier ◽  
Sylvain Bérail ◽  
Ina Fettig ◽  
...  

2021 ◽  
pp. 498-506
Author(s):  
J.C. Diaz ◽  
Z. Agioutantis ◽  
S. Schafrik ◽  
D.T. Hristopulos

2021 ◽  
Vol 16 (06) ◽  
pp. P06027
Author(s):  
A. Aab ◽  
P. Abreu ◽  
M. Aglietta ◽  
J.M. Albury ◽  
I. Allekotte ◽  
...  

2021 ◽  
Vol 14 (4) ◽  
pp. 3015-3032
Author(s):  
Bradley D. Hall ◽  
Andrew M. Crotwell ◽  
Duane R. Kitzis ◽  
Thomas Mefford ◽  
Benjamin R. Miller ◽  
...  

Abstract. The NOAA Global Monitoring Laboratory serves as the World Meteorological Organization Global Atmosphere Watch (WMO/GAW) Central Calibration Laboratory (CCL) for CO2 and is responsible for maintaining the WMO/GAW mole fraction scale used as a reference within the WMO/GAW program. The current WMO-CO2-X2007 scale is embodied by 15 aluminum cylinders containing modified natural air, with CO2 mole fractions determined using the NOAA manometer from 1995 to 2006. We have made two minor corrections to historical manometric records: fixing an error in the applied second virial coefficient of CO2 and accounting for loss of a small amount of CO2 to materials in the manometer during the measurement process. By incorporating these corrections, extending the measurement records of the original 15 primary standards through 2015, and adding four new primary standards to the suite, we define a new scale, identified as WMO-CO2-X2019. The new scale is 0.18 µmol mol−1 (ppm) greater than the previous scale at 400 ppm CO2. While this difference is small in relative terms (0.045 %), it is significant in terms of atmospheric monitoring. All measurements of tertiary-level standards will be reprocessed to WMO-CO2-X2019. The new scale is more internally consistent than WMO-CO2-X2007 owing to revisions in propagation and should result in an overall improvement in atmospheric data records traceable to the CCL.


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