The importance of reducing the systematic error due to non-linearity in N2O flux measurements by static chambers

Abstract

Closed (non-steady state) chamber measurements are often used to determine the gas exchange of N2O. Many researchers have addressed the underestimation of the emission estimates obtained from closed chamber measurements when using linear regression methods. However, the linear regression method is still usually applied to derive the flux. The importance of using non-linear regression methods is demonstrated with data from four fertilizing events each consisting of 1 month of automatic chamber measurements at Cabauw in the Netherlands in the period from July 2005 to July 2006. It is presented that the cumulative emission estimates with the exponential regression method are close to the cumulative emissions estimates with the intercept method. The linear estimates differ by up to 60% of the estimates with the exponential method. The performance of each method is validated using a C2H6 tracer and a goodness-of-fit analysis. The goodness-of-fit is much better for the exponential than the linear regression method. The systematic error due to linear regression is of the same order as the estimated uncertainty due to temporal variation. Therefore, closed-chamber data should be tested for non-linearity and an appropriate method should be used to calculate the flux.