The capture of carbon by aquatic ecosystems and its sequestration in sediments has been studied as a potential method for mitigating the adverse effects of climate change. However, the evaluation of in situ atmospheric CO2 fluxes is challenging because of the difficulty in making continuous measurements over areas and for periods of time that are environmentally relevant. The eddy covariance method for estimating atmospheric CO2 fluxes is the most promising approach to address this concern. However, methods to process the data obtained from eddy covariance measurements are still being developed, and the estimated air-water CO2 fluxes have large uncertainties and differ from those obtained using conventional methods. In this study, we improved the post-processing procedure for the eddy covariance method to reduce the uncertainty in the measured air-water CO2 fluxes. Our procedure efficiently removes low-quality fluxes using a combination of filtering methods based on the received signal strength indicator of the eddy covariance sensor, the normalized standard deviation of atmospheric CO2 and water vapor concentrations, and a high-pass filter. The improved eddy covariance fluxes revealed diurnal and semi-diurnal cycles and a significant relationship with water fCO2, patterns that were not observed from the results before filtering. Although there were still differences with indirect conventional measurements like the bulk formula method, the methods used in this study should improve the accuracy of carbon flow estimates at sites with complex terrains like coastal areas.