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Titel |
Development of a low cost and low power consumption system for monitoring
CO2 soil concentration in volcanic areas. |
VerfasserIn |
Shadia Awadallah Estévez, David Moure-García, Pedro Torres-González, Leopoldo Acosta Sánchez, Itahiza Domínguez Cerdeña |
Konferenz |
EGU General Assembly 2017
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Medientyp |
Artikel
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Sprache |
en
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 19 (2017) |
Datensatznummer |
250150629
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Publikation (Nr.) |
EGU/EGU2017-15109.pdf |
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Zusammenfassung |
Volatiles dissolved in magma are released as gases when pressure or stress conditions
change. H2O, CO2, SO2 and H2S are the most abundant gases involved in volcanic
processes. Emission rates are related to changes in the volcanic activity. Therefore, in order to
predict possible eruptive events, periodic measurements of CO2 concentrations from the soil
should be carried out.
In the last years, CO2 monitoring has been widespread for many reasons. A direct
relationship between changes in volcanic activity and variations in concentration, diffuse flux
and isotope ratios of this gas, have been observed prior to some eruptions or unrest processes.
All these factors have pointed out the fact that CO2 emission data are crucial in volcanic
monitoring programs. In addition, relevant instrumentation development has also taken
place: improved accuracy, cost reduction and portability.
Considering this, we propose a low cost and a low power consumption system for
measuring CO2 concentration in the soil based on Arduino. Through a perforated pick-axe
buried at a certain depth, gas samples are periodically taken with the aid of a piston. These
samples are injected through a pneumatic circuit in the spectrometer, which measures the
CO2 concentration. Simultaneously, the system records the following meteorological
parameters: atmospheric pressure, precipitation, relative humidity and air and soil
temperature. These parameters are used to correct their possible influence in the CO2 soil
concentration. Data are locally stored (SD card) and transmitted via GPRS or WIFI to a data
analysis center. |
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