Abstract
Two methods were described to estimate interference in the measurements of infrared (IR) photoacoustic multi-gas analyzer (PAMGA). One is IR spectroscopic analysis (IRSA) and the other is mathematical simulation. An Innova 1412 analyzer (AirTech Instruments, Ballerup, Denmark) with two different filter configurations was used to provide examples that demonstrate the two methods. The filter configuration in Example #1 consists of methane (CH4), methanol (MeOH), ethanol (EtOH), nitrous oxide (N2O), carbon dioxide (CO2), and water vapor (H2O), and in Example #2 of ammonia (NH3), MeOH, EtOH, N2O, CO2, and H2O. The interferences of NH3 as a non-target gas in Example #1 were measured to validate the two methods. The interferences of H2O and NH3 as target gases in Example #2 were also measured to evaluate the analyzer’s internal cross compensation algorithm. Both simulation and experimental results showed that the interference between the target gases could be eliminated by the internal cross compensation algorithm. But the interferences of non-target gases on target gases could not be addressed by the internal cross compensation, while they could be assessed by the IRSA and mathematical simulation methods. If the IR spectrum of a non-target gas overlaps with that of target gas A at filter A, it could affect not only gas A (primary interference), but also other target gases by secondary interference (because the IR spectrum of gas A overlaps with gas B at filter B and thus affects gas B measurements). The IRSA and mathematical simulation methods can be used to estimate the interference in IR PAMGA measurements prior to purchase or calibration of the unit.
Highlights
Agriculture is an important source of air emissions, including greenhouse gases, volatile organic compounds, and ammonia (NH3) [1,2,3]
Two methods, IR spectroscopic analysis (IRSA) and mathematical simulation, were introduced in the present study to investigate the interference in IR photoacoustic multi-gas analyzer (PAMGA) measurements
The objective of this study was to explore the proper use of the IR PAMGA in agriculture air quality studies including (1) configuring the filters based on the application of the IR PAMGA; (2) estimating the interference of non-target gases in the monitoring environment before conducting actual field experiments to determine if a particular IR PAMGA can be used in the application; (3) simulating the interference when new non-target gases were discovered after the actual field experiments were conducted to evaluate the IR PAMGA data; and
Summary
Agriculture is an important source of air emissions, including greenhouse gases, volatile organic compounds, and ammonia (NH3) [1,2,3]. Some of these emissions have been regulated by federal, state, and local agencies [4,5,6]. There is a need for IR PAMGA users to better understand the interference in the IR PAMGA measurements and to determine if the IR PAMGA can be properly used For this purpose, two methods, IR spectroscopic analysis (IRSA) and mathematical simulation, were introduced in the present study to investigate the interference in IR PAMGA measurements. The objective of this study was to explore the proper use of the IR PAMGA in agriculture air quality studies including (1) configuring the filters based on the application of the IR PAMGA; (2) estimating the interference of non-target gases in the monitoring environment before conducting actual field experiments to determine if a particular IR PAMGA can be used in the application; (3) simulating the interference when new non-target gases were discovered after the actual field experiments were conducted to evaluate the IR PAMGA data; and (4) experimentally evaluating the analyzer’s internal cross compensation algorithm
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