CO₂ fluxes and concentrations are not well understood in Northeast China, where dominant land surface types are mixed forest and cropland. Here, we analyzed the CO₂ fluxes and concentrations using observations and the Weather Research and Forecasting model coupled with the Vegetation Photosynthesis and Respiration Model (WRF‐VPRM). We also used WRF‐VPRM outputs to examine CO₂ transport/dispersion and budgets. Finally, we investigated the uncertainties of simulating CO₂ fluxes related to four VPRM parameters (including maximum light use efficiency, photosynthetically active radiation half‐saturation value, and two respiration parameters) using off‐line ensemble simulations. The results indicated that mixed forests acted as a larger CO₂ source and sink than rice paddies in 2016 due to a longer growth period and stronger ecosystem respiration, although measured minimum daily mean net ecosystem exchange (NEE) was smaller at rice paddy (−10 μmol·m^‐2·s^‐1) than at mixed forest (−6.5 μmol·m^‐2·s^‐1) during the growing season (May–September). The monthly fluctuation of column‐averaged CO₂ concentrations (XCO₂) exceeded 10 ppm in Northeast China during 2016. The large summertime biogenic sinks offset about 70% of anthropogenic contribution of XCO₂ in this region. WRF‐VPRM modeling successfully captured seasonal and episodic variations of NEE and CO₂ concentrations; however, NEE in mixed forest was overestimated during daytime, mainly due to the uncertainties of VPRM parameters, especially maximum light use efficiency. These findings suggest that the WRF‐VPRM modeling framework will provide greater understanding of the natural and anthropogenic contributions to the carbon cycle in China, especially after calibration of parameters that control biogenic fluxes.

The eddy covariance method was used to study the CO₂ budget of the Liaohe Delta reed wetland in northern China during 2012–2015. The changes in environmental factors (including meteorology, vegetation, hydrology, and soil) were analyzed simultaneously. The change in the trend of the CO₂ concentration in the reed wetland was similar to global changes over the four years. The average annual CO₂ accumulation was 2.037 kg·CO₂·m⁻², ranging from 1.472 to 2.297 kg·CO₂·m⁻². The seasonal characteristics of the CO₂ exchange included high CO₂ absorption in June and July, and high emissions in April and from September to October, with the highest emissions in July 2015. The average temperatures from 2013 to 2015 were higher than the 50-year average, largely due to increased temperatures in winter. Precipitation was below the 50-year average, mainly because of low precipitation in summer. The average wind speed was less than the 50-year average, and sunshine duration decreased each year. The CO₂ exchange and environmental factors had a degree of correlation or consistency. The contribution of meteorology, vegetation, hydrology, and soil to the CO₂ budget was analyzed using the partial least squares method. Water and soil temperature had a greater effect on the CO₂ exchange variability. The regression equation of the CO₂ budget was calculated using the significant contributing factors, including temperature, precipitation, relative humidity, water-table level, salinity, and biomass. The model fit explained more than 70% of the CO₂ exchange, and the simulation results were robust.