Cross-interference correction and simultaneous multi-gas analysis based on infrared absorption

In this paper, we present simultaneous multiple pollutant gases （CO2, CO, and NO） measurements by using the non-dispersive infrared （NDIR） technique. A cross-correlation correction method is proposed and used to correct the cross-interferences among the target gases. The calculation of calibration curves is based on least-square fittings with third-order polynomials, and the interference functions are approximated by linear curves. The pure absorbance of each gas is obtained by solving three simultaneous equations using the fitted interference functions. Through the interference correction, the signal created at each filter channel only depends on the absorption of the intended gas. Gas mixture samples with different concentrations of CO2, CO, and NO are pumped into the sample cell for analysis. The results show that the measurement error of each gas is less than 4.5%.

A Re-examination of Density Effects in Eddy Covariance Measurements of CO_2 Fluxes

Corrections of density effects resulting from air-parcel expansion/compression are important in interpreting eddy covariance fluxes of water vapor and CO2 when open-path systems are used. To account for these effects, mean vertical velocity and perturbation of the density of dry air are two critical parameters in treating those physical processes responsible for density variations. Based on various underlying assumptions, different studies have obtained different formulas for the mean vertical velocity and perturbation of the density of dry air, leading to a number of approaches to correct density effects. In this study, we re-examine physical processes related to different assumptions that are made to formulate the density effects. Specifically, we re-examine the assumptions of a zero dry air flux and a zero moist air flux in the surface layer, used for treating density variations, and their implications for correcting density effects. It is found that physical processes in relation to the assumption of a zero dry air flux account for the influence of dry air expansion/compression on density variations. Meanwhile, physical processes in relation to the assumption of a zero moist air flux account for the influence of moist air expansion/compression on density variations. In this study, we also re-examine mixing ratio issues. Our results indicate that the assumption of a zero dry air flux favors the use of the mixing ratio relative to dry air, while the assumption of a zero moist air flux favors the use of the mixing ratio relative to the total moist air. Additionally, we compare different formula for the mean vertical velocity, generated by air-parcel expansion/compression, and for density effect corrections using eddy covariance data measured over three boreal ecosystems.

Relationship among Different Soil Biochemical Methods to Determine Soil Health

Numerous soil biochemical methods are used to determine the soil health status, but the relationships among these methods are not well understood. Relationships among soil biochemical tests, 1) chloroform fumigated microbial biomass C (CFMBC), 2) permanganate oxidizable C (POXC), 3) Solvita CO2-burst (Solvita), 4) Solvita labile amino nitrogen (SLAN), and short-term soil CO2 efflux during laboratory incubation using (v) Alkali-base trap (Alkali) and (vi) infrared gas analyzer (IRGA), were evaluated for nine agricultural soils collected across the Red River Valley of North Dakota and Minnesota, USA. Not a single test is comprehensive to relate with all soil biochemical tests. Coefficient of variation percentage for particular method varied with soil type. Among six tests, CFMBC is significantly (p < 0.05) related with Alkali (r = 0.37), Solvita (r = 0.57), SLAN (r = 0.52), and POXC (r = 0.68). Soil CFMBC correlates with most of soil biochemical tests and can be potential to determine soil biochemical condition.