INVESTIGADORES
RICCI Patricia
artículos
Título:
A novel sampling technique for monitoring atmospheric methane concentrations: a case study with livestock sources
Autor/es:
MANSILLA, R.A.; GOMBA, J.; RICCI, P.; CORREA, P.G.; JULIARENA, MARÍA PAULA
Revista:
SCIENCE OF THE TOTAL ENVIRONMENT
Editorial:
ELSEVIER SCIENCE BV
Referencias:
Lugar: Amsterdam; Año: 2024
ISSN:
0048-9697
Resumen:
The substantial increase in the presence of greenhouse gases (GHGs) in the atmosphere worldwide has led to the development of several sampling techniques to improve their quantification and to characterize the sources of high global warming potential gas emissions more accurately. In this context, we have developed a new method to estimate the time-averaged concentration of atmospheric methane by using a long hose that collects the gas by diffusion through one of its ends. We performed numerical simulations of the problem to illustrate the basis of our technique and to determine the numerical factors required to estimate the time-averaged concentration of methane. Our methodology was validated with two sets of experiments where the source of methane was animals in a respiration chamber. We compared the time-averaged methane concentration obtained with our methodology for periods (T) ranging from 1 to 4 days with those measured with the sensor of a respiration chamber. We found that our method’s accuracyimproves for days, where the estimated concentrations mostly do not differ by more than 10 % from the reference value. Even for the case day, the error does not surpass 20 %. In another set of tests, we verified that measuring the concentration of the half farthest from the collector’s inlet allows us to obtain a more accurate estimate of the mean external concentration than when measuring the concentration in the entire collector. This new methodology for air sampling in conjunction with numerical analysis is a viable alternative for quantifying GHG concentrations. In addition, the simple design of the devices shows remarkable benefits in both cost and simplicity for implementing large-scale individual sampling.