[Evaluation of gap-filling methods for CH4 flux data based on eddy covariance method in the Lake Taihu, China]. / æ¶¡åº¦ç›¸å ³è§‚æµ‹çš„å¤ªæ¹–CH4通量数据插补方法评价.

Eddy covariance method has become a key technique to measure CH4 flux continuously in lakes. A large number of CH4 flux data was missing due to variable reasons. In order to reconstruct a complete time series of CH4 flux, it is necessary to find an appropriate gap-filling method to insert the CH4 flux data gap. Based on the routine meteorological data and CH4 flux data measured at Bifenggang site in the eastern part of the Taihu eddy flux network during 2014 to 2017, we analyzed the control factors of CH4 flux at the half-hour scale and daily scale. With those data, we tested that whether nonlinear regression method and two machine learning methods, random forest algorithm and error back propagation algorithm, could fill the CH4 flux gap at the half-hour scale and daily scale. The results showed that CH4 flux at the half-hour scale was mainly influenced by sediment temperature, friction velocity, air temperature, relative humidity, latent heat flux and water temperature at 20 cm in the growing season, and was mainly affected by relative humidity, latent heat flux, wind speed, sensible heat flux and sediment temperature in non-growing season. The CH4 flux at the daily scale was mainly affected by latent heat flux and relative humidity. Random forest model was the best in CH4 flux data gap filling at both time scales. The random forest model with the input variables of day of year, solar elevation angle, sediment temperature, friction velocity, air temperature, water temperature at 20 cm, relative humidity, air pressure, and wind speed was more suitable for filling the CH4 flux data gap at the half-hour scale. The random forest model with the input variables of day of year, sediment temperature, friction velocity, air temperature, water temperature at 20 cm, relative humidity, air pressure, wind speed, and downward shortwave radiation was more suitable for filling CH4 flux data gap at the day scale. The interpolation models could fill the data gap better at daily scale than that at the half-hour scale.

[Effects of chamber characteristics on CO2 and CH4 flux at the water-air interface measured by the chamber method]. / 箱体特征对箱式法观测水-气界面CO2和CH4通量的影响.

The chamber method is widely used to measure CO2 and CH4 flux in inland water. However, the designs of chamber used in various studies are different and lack unified standards, which would affect the observation results. To clarify the impacts of chamber characteristics, including light transmittance, air pressure difference inside and outside the chamber, and gas mixing degree in the chamber, on CO2 and CH4 flux measurements at the water-air interface, we compared the effects of transparent/opaque chamber, the chamber with/without air pressure equalizing device and fan on CO2 and CH4 flux measurements in the aquaculture pond, based on the multi-channel closed dynamic chamber system. The results showed that, during the daytime in summer, compared with the transparent chamber which could measure the actual CO2 flux, when CO2 was emitted from the pond, the opaque chamber overestimated the CO2 flux by 90%; when CO2 was absorbed by the pond, the opaque chamber underestimated the CO2 flux by 50%. The CH4 diffusion flux measured by the opaque chamber was 40% lower than that measured by the transparent chamber. There was no significant difference between CO2 and CH4 flux measured by the chamber with and without air pressure equalizing device. CO2 flux observed by the chamber without fan had poor representativeness, being 20% higher than that observed by the chamber with fan. Moreover, CH4 flux emitted through different pathways could not be distinguished using the chamber without fan. Therefore, when the chamber method was used to observe the CO2 and CH4 flux at the water-air interface, the chamber shall be transparent and be installed with fan.

[Analysis of Greenhouse Gas Emission Characteristics and Their Influencing Factors in the Algae Zone of Lake Taihu].

In order to identify CH4 and CO2 emission flux characteristics and their impact factors in the algal lake zone of Lake Taihu, CH4 and CO2 fluxes were observed by the improved closed chamber method in Meiliang Bay in Lake Taihu. The relationships between CH4 and CO2 flux and meteorological factors were analyzed. The results showed that CH4 and CO2 fluxes had obvious diurnal variations. The CH4 flux in the daytime was higher than that in the nighttime in spring; however, the CH4 flux in the nighttime was higher than that in the daytime in summer. The CO2 uptake flux in the daytime was higher than that in the nighttime in spring and summer. The algae zone of Lake Taihu was a CH4 source for the atmosphere. The average CH4 flux was 4.047 nmol ·(m2 ·s)-1 and 40.779 nmol ·(m2 ·s)-1 in spring and summer, respectively. The zone was the CO2 sink for the atmosphere in spring and summer. The average CO2 flux was -0.160 µmol ·(m2 ·s)-1 and -0.033 µmol ·(m2 ·s)-1 in spring and summer, respectively. On an hourly scale, the CH4 emission flux was positively correlated with air temperature and water temperature (r=0.20, P<0.01 and r=0.34, P<0.01, respectively). When wind speed was lower than 6 m ·s-1, the CH4 flux was positively correlated with wind speed (r=0.71, P<0.01). The CO2 uptake flux had a significant positive correlation with air temperature and wind speed (r=0.14, P<0.01 and r=0.33, P<0.05, respectively). However, the CO2 uptake flux was negatively correlated with air pressure and solar radiation (r=-0.41, P<0.01 and r=-0.35, P<0.01, respectively). The CO2 efflux had a significant positive correlation with wind speed (r=0.40, P<0.05). The CO2 efflux was negatively correlated with solar radiation (r=-0.35, P<0.01). On a daily scale, the CH4 emission flux had a significant positive correlation with air temperature and water temperature (r=0.83, P<0.01 and r=0.78, P<0.01, respectively).