Dispersion modelling intercomparison exercise

2000 ◽  
Vol 14 (1/2/3/4/5/6) ◽  
pp. 176
Author(s):  
E. Davakis ◽  
P. Deligiannis
Keyword(s):  
Dispersion Modelling ◽  
Intercomparison Exercise

Dispersion modelling of solid particles from vehicle exhaust into the atmosphere

Ekologija ◽  
2008 ◽  
Vol 54 (2) ◽  
pp. 117-123 ◽  
Author(s):  
Pranas Baltrėnas ◽  
Petras Vaitiekūnas ◽  
Saulius Vasarevičius ◽  
Saad Jordaneh
Keyword(s):  
Solid Particles ◽  
Dispersion Modelling ◽  
Vehicle Exhaust

scholarly journals 14C INTERCOMPARISON EXERCISE ON BONES AND IVORY SAMPLES: IMPLICATIONS FOR FORENSICS

Radiocarbon ◽  
2021 ◽  
pp. 1-12
Author(s):  
G Quarta ◽  
M Molnár ◽  
I Hajdas ◽  
L Calcagnile ◽  
I Major ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
International Atomic Energy Agency ◽  
Accelerator Mass Spectrometry ◽  
Reference Curve ◽  
Nuclear Testing ◽  
Energy Agency ◽  
Widespread Application ◽  
Intercomparison Exercise ◽  
High Degree ◽  
Data Calibration

ABSTRACT The application of accelerator mass spectrometry radiocarbon (AMS 14C) dating in forensics is made possible by the use of the large excursion of the 14C concentration in the post-WWII terrestrial atmosphere due to nuclear testing as a reference curve for data calibration. By this approach high-precision analyses are possible on samples younger than ∼70 years. Nevertheless, the routine, widespread application of the method in the practice of forensics still appears to be limited by different issues due to possible complex interpretation of the results. We present the results of an intercomparison exercise carried out in the framework of an International Atomic Energy Agency (IAEA) CRP-Coordinated Research Project between three AMS laboratories in Italy, Hungary, and Switzerland. Bone and ivory samples were selected with ages spanning from background (>50 ka) to 2018. The results obtained allow us to assess the high degree of reproducibility of the results and the remarkable consistency of the experimental determinations.

Optimizing the calculation grid for atmospheric dispersion modelling

2015 ◽  
Vol 142 ◽  
pp. 103-112
Author(s):  
S. Van Thielen ◽  
C. Turcanu ◽  
J. Camps ◽  
R. Keppens
Keyword(s):  
Atmospheric Dispersion ◽  
Dispersion Modelling ◽  
Atmospheric Dispersion Modelling ◽  
Calculation Grid

Distribution of total bacteria and staphylococci in PM2.5, PM10 and total dust in the emission of two fattening pig houses/Verteilung von Gesamtbakterien und Staphylokokken in PM2,5, PM10 und Gesamtstaub in der Emission von zwei Mastschweineställen

Gefahrstoffe ◽  
2020 ◽  
Vol 80 (09) ◽  
pp. 344-348
Author(s):  
M. Clauß ◽  
S. Linke ◽  
A. C. Springorum
Keyword(s):  
Particle Size ◽  
Size Fraction ◽  
Airborne Bacteria ◽  
Dispersion Modelling ◽  
Particle Size Fraction ◽  
Collection System ◽  
Total Dust ◽  
Dust Distribution ◽  
Selective Collection ◽  
Total Bacteria

The particle size distribution of airborne bacterial conglomerates is an important factor in calculating possible spread distances of the bacteria over the air. Therefore, a size-selective collection system based on an emission impinger was developed to compare the distribution of total bacteria and staphylococci in particle fractions PM2.5, PM10 and total dust in the emission of two fattening pig stables. Mean emissions of 7.2 × 104 cfu/m³ total bacteria, 6.1 × 104 cfu/m³ staphylococci and 2.8 × 106 cells/m3 measured. About 30% of total bacteria and staphylococci were found in the PM2.5 particle size fraction and about 60% in PM10. The average dust distribution was 80% PM10 and 60% PM2.5. The results show that airborne bacteria from fattening pig units mainly occur on larger particles and do not correlate with dust fractions. The found conditions should be considered in future dispersion modelling.

Assessment of Fine-Scale Dispersion Modelling for Near-Road Exposure Applications

2019 ◽  
pp. 347-350
Author(s):  
Jennifer L. Moutinho ◽  
Donghai Liang ◽  
Jeremy Sarnat ◽  
Armistead G. Russell
Keyword(s):  
Dispersion Modelling ◽  
Fine Scale

scholarly journals Metal measurement in aquatic environments by passive sampling methods: Lessons learning from an in situ intercomparison exercise

2016 ◽  
Vol 208 ◽  
pp. 299-308 ◽  
Author(s):  
A. Dabrin ◽  
J.-P. Ghestem ◽  
E. Uher ◽  
J.-L. Gonzalez ◽  
I.J. Allan ◽  
...  
Keyword(s):  
Passive Sampling ◽  
Sampling Methods ◽  
Aquatic Environments ◽  
Intercomparison Exercise
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