Eddy covariance (EC) technique is a widely used method to quantify the net exchange of CO2 between ecosystems and the atmosphere. The quality control and data analysis of calculated fluxes are essential to ensure accurate budget estimates. Ecosystem scale CO2 exchange between a typical permafrost peatland of the Great Hing'an Mountains and the atmosphere was measured during the growing season of 2014 and 2015 using the open-path eddy covariance technique. Footprint analysis and turbulence stationary test were applied to the calculated fluxes to improve the data accuracy. High quality data were then screened to study emission patterns. Combining widely used models with the observed data, an empirical model derived by photosynthetically active radiation was developed to fit daily photosynthesis reduction. Seasonal variation of apparent quantum yield (alpha, mol CO2 mol(-1) photon), maximum photosynthesis rate (P-max, mu mol CO2 m(-2) s(-1)) and temperature sensitivity for respiration (E-0, K) were found to follow a unimodal distribution and could be simulated by a Gaussian based equation. The use of EC data and the potential issues, especially the bias on respiration estimation, were discussed. Detailed utilization and analyses of the EC data are helpful in revealing the CO2 exchange patterns on different time scales, and also contribute to reducing the result differences between EC and other measurement techniques.

Eddy covariance (EC) technique is a widely used method to quantify the net exchange of CO2 between ecosystems and the atmosphere. The quality control and data analysis of calculated fluxes are essential to ensure accurate budget estimates. Ecosystem scale CO2 exchange between a typical permafrost peatland of the Great Hing'an Mountains and the atmosphere was measured during the growing season of 2014 and 2015 using the open-path eddy covariance technique. Footprint analysis and turbulence stationary test were applied to the calculated fluxes to improve the data accuracy. High quality data were then screened to study emission patterns. Combining widely used models with the observed data, an empirical model derived by photosynthetically active radiation was developed to fit daily photosynthesis reduction. Seasonal variation of apparent quantum yield (alpha, mol CO2 mol(-1) photon), maximum photosynthesis rate (P-max, mu mol CO2 m(-2) s(-1)) and temperature sensitivity for respiration (E-0, K) were found to follow a unimodal distribution and could be simulated by a Gaussian based equation. The use of EC data and the potential issues, especially the bias on respiration estimation, were discussed. Detailed utilization and analyses of the EC data are helpful in revealing the CO2 exchange patterns on different time scales, and also contribute to reducing the result differences between EC and other measurement techniques.