Effect of the Instrument Surface Heating on CO2 Flux from Open-Path Eddy Covariance System at Linze Station
JI Xi-bin
Abstract
JI Xi-bin
Abstract
The instrument surface heating of LI-7500 analyzer has a significant impact on the measurement of CO2 flux from open-path eddy covariance system,and the Burba correction to CO2 flux is a most critical requirement for improving CO2 measurement,net ecosystem exchange(NEE) estimate,and global CO2 exchange and climate change modeling,etc.The sensible heat flux inside the optical path,latent heat flux and CO2 flux were corrected using Burba correction approach for one annual datasets of measurements from an open-path eddy covariance system and from an automatic meteorological observation tower installed a maize field at Linze station.The results show that heat exchange from the bottom window and spars are the main contributor of the correction term of sensible heat flux inside the path with the mean values of 6.81 W·m-2 and 2.68 W·m-2,respectively.For latent heat flux,the magnitude of the correction term is least and negligible,and the mean value is only about 0.24 W·m-2.However,the measurements of CO2 flux and seasonal NEE are significantly affected by the Burba correction approach,and the mean values of the correction term are 19.14 μg·CO2·m-2·s-1 and 313.21 mg·C·m-2·d-1,respectively.Furthermore,with lower air temperature,the magnitude of the correction term is larger expect for the latent heat flux.For instance,during the growing season,the corrected terms of sensible heat flux inside the path,latent heat flux,CO2 flux and daily NEE are 6.94 W·m-2,0.33 W·m-2,12.86 μg·CO2·m-2·s-1 and 161.58 mg·C·m-2·d-1,and are about 60.4%,220.0%,50.6% and 37.4% of the values of the coordinates during the non-growing season,respectively.Most of all,no-using the Burba correction procedure could let to overestimate the carbon uptake with value around 25.85 g·C·m-2 during the growing season,and underestimate the carbon emission from the agroecosystem with the value around 88.47 g·C·m-2 during the non-growing season.
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The instrument surface heating of LI-7500 analyzer has a significant impact on the measurement of CO2 flux from open-path eddy covariance system,and the Burba correction to CO2 flux is a most critical requirement for improving CO2 measurement,net ecosystem exchange(NEE) estimate,and global CO2 exchange and climate change modeling,etc.The sensible heat flux inside the optical path,latent heat flux and CO2 flux were corrected using Burba correction approach for one annual datasets of measurements from an open-path eddy covariance system and from an automatic meteorological observation tower installed a maize field at Linze station.The results show that heat exchange from the bottom window and spars are the main contributor of the correction term of sensible heat flux inside the path with the mean values of 6.81 W·m-2 and 2.68 W·m-2,respectively.For latent heat flux,the magnitude of the correction term is least and negligible,and the mean value is only about 0.24 W·m-2.However,the measurements of CO2 flux and seasonal NEE are significantly affected by the Burba correction approach,and the mean values of the correction term are 19.14 μg·CO2·m-2·s-1 and 313.21 mg·C·m-2·d-1,respectively.Furthermore,with lower air temperature,the magnitude of the correction term is larger expect for the latent heat flux.For instance,during the growing season,the corrected terms of sensible heat flux inside the path,latent heat flux,CO2 flux and daily NEE are 6.94 W·m-2,0.33 W·m-2,12.86 μg·CO2·m-2·s-1 and 161.58 mg·C·m-2·d-1,and are about 60.4%,220.0%,50.6% and 37.4% of the values of the coordinates during the non-growing season,respectively.Most of all,no-using the Burba correction procedure could let to overestimate the carbon uptake with value around 25.85 g·C·m-2 during the growing season,and underestimate the carbon emission from the agroecosystem with the value around 88.47 g·C·m-2 during the non-growing season.
Key concepts: Eddy covariance, Sensible heat, Latent heat, Flux (metallurgy), Heat flux, Environmental science, Atmospheric sciences, Meteorology