ALBERT

Description: The behavior of whole ecosystems in humid climate zone in response to drought is less well documented. Continuous measurements of carbon dioxide and water vapor exchange using the eddy covariance technique during 2003–2007 were made above a subtropical evergreen coniferous plantation in Southeast China. Seasonal distribution of precipitation and temperature was out of step during the summer, which resulted in droughts frequently. Gross ecosystem photosynthesis (GEP), ecosystem respiration (RE) and net ecosystem production (NEP) showed clear seasonality, with low rates during seasonal drought and in winter. The exponential response of monthly GEP and RE to air temperature provided us an implication that monthly NEP was less sensitive and only increased linearly. However, the function response of monthly NEP and its components (GEP and RE) disappeared under high temperature and low moisture. Monthly and year RE showed a linear and positive dependence on the corresponding GEP, with statistically significant. Annual NEP varied among years from 306 to 430 g C m−2 (mean 395, SD 50). Interannual variability in NEP was controlled primarily by air temperature and the ratio of precipitation and evapotranspiration that affected the RE/GEP ratio, which varied between 0.76 and 0.81 (mean 0.78, SD 0.02).

Description: This paper explores the seasonal and inter-annual variations in surface energy exchanges at an alpine shrub-meadow ecosystem (AM) and an alpine meadow-steppe (AS) on the Qinghai-Tibetan Plateau using the 4–5-year continuous flux measurements by the eddy covariance technique. Although ground solar radiation (Kd) was lower at AM than at AS, net radiation (Rn) was higher at AM than at AS due to the lower surface reflectivity for short-wave radiation (albedo) and the lower ratio of upward long-wave radiation to downward long-wave radiation (Lu/Ld) at AM. The ratio of Rn/Kd was lower (about 0.4) at AS than at AM (about 0.6). In the annual scale, annual precipitation was the most important factor controlling energy partitioning at AS, while temperature, especially during the spring, controlled the inter-annual variations in energy partitioning at AM characterized by low temperature. Vegetation growth played an important role in controlling energy partitioning at seasonal scale at both sites. However, soil water content was also one of major factors affecting Bowen ratio (β) due to the lower soil water-holding capacity at AS as compared with AM. Under non-drought conditions, the influence of vapor pressure deficit (VPD) on energy partitioning at half-hourly scale was stronger at AM than at AS due to higher vegetation cover thereof.

Description: Clouds can significantly affect carbon uptake of forest ecosystems by affecting incoming solar radiation on the ground, temperature and other environmental factors. In this study, we analyzed the effects of cloudiness on the net ecosystem exchange of carbon dioxide (NEE) of a temperate broad-leaved Korean pine mixed forest at Changbaishan (CBS) and a subtropical evergreen broad-leaved forest at Dinghushan (DHS) of ChinaFLUX, based on the flux data obtained during June–August from 2003 to 2006. The results showed that the response of the NEE of forest ecosystem to photosynthetically active radiation (PAR) was different under clear sky and cloudy sky conditions, and this difference was not consistent between CBS and DHS. Compared with clear skies, light-saturated maximum photosynthetic rate (Pec,max) of CBS during mid-growing season (from June to August) was respectively enhanced by 34%, 25%, 4% and 11% on cloudy skies in 2003, 2004, 2005 and 2006; however, Pec,max of DHS was higher under clear skies than under cloudy skies from 2004 to 2006. NEE of forests at CBS reached its maximum when the clearness index (kt) was between 0.4 and 0.6, and the NEE decreased obviously when kt exceeded 0.6. Compare with CBS, although NEE of forest at DHS tended to the maximum when kt varied between 0.4 and 0.6, the NEE did not decrease noticeably when kt exceeded 0.6. The results indicated that cloudy sky conditions were more beneficial to carbon uptake for the temperate forest ecosystem rather than for the subtropical forest ecosystem. This is due to the fact that the non-saturating light conditions and increase of diffuse radiation were more beneficial to photosynthesis, and the reduced temperature was more conducive to decreasing the ecosystem respiration in temperate forest ecosystems under cloudy sky conditions. This phenomenon is important to evaluate carbon uptake of temperate forests under climate change conditions.

Description: This study compared the CO2 fluxes over three grassland ecosystems in China, including a temperate steppe (TS) in Inner Mongolia, an alpine shrub-meadow (ASM) in Qinghai and an alpine meadow-steppe (AMS) in Tibet. The measurements were made in 2004 and 2005 using the eddy covariance technique. Objectives were to document the different seasonality of net ecosystem exchange of CO2 (NEE) and its components, gross ecosystem photosynthesis (GEP) and ecosystem respiration (Reco), and to examine how environmental factors affect carbon exchange in the three grassland ecosystems. It was warmer in 2005 than in 2004, especially during the growing season (from May to September), across the three sites. The annual precipitation at TS in 2004 (364.4 mm) was close the annual average (350 mm), whereas the precipitation at TS in 2005 (153.3 mm) was significantly below the average. Both GEP and Reco of the temperate steppe in 2005 were significantly reduced by the extreme drought stress, resulting in net carbon release during almost the whole growing season. The magnitude of CO2 fluxes (daily and annual sums) was largest for the alpine shrub-meadow and smallest for the alpine meadow-steppe. The seasonal trends of GEP, Reco and NEE of the alpine shrub-meadow tracked closely with the variation in air temperature, while the seasonality of GEP, Reco and NEE of the temperate steppe and the alpine meadow-steppe was more related to the variation in soil moisture. The alpine shrub-meadow was a local carbon sink over the two years. The temperate steppe and alpine meadow-steppe were acting as net carbon source, with more carbon loss to the atmosphere in warmer and drier year of 2005. Annual precipitation was the primary climate driver for the difference in annual GEP and NEE among the three sites and between the two years. We also found the annual GEP and NEE depended significantly on the growing season length, which was mainly a result of the timing and amount of precipitation for the temperate steppe and the alpine meadow-steppe, but was more linked to the variation in air temperature for the alpine shrub-meadow.

Description: In order to use the global available eddy-covariance (EC) flux dataset and remote-sensing measurements to provide estimates of gross primary productivity (GPP) at landscape (101–102 km2), regional (103–106 km2) and global land surface scales, we developed a satellite-based GPP algorithm using LANDSAT data and an upscaling framework. The satellite-based GPP algorithm uses two improved vegetation indices (Enhanced Vegetation Index – EVI, Land Surface Water Index – LSWI). The upscalling framework involves flux footprint climatology modelling and data-model fusion. This approach was first applied to an evergreen coniferous stand in the subtropical monsoon climatic zone of south China. The EC measurements at Qian Yan Zhou tower site (26°44´48" N, 115°04´13" E), which belongs to the China flux network and the LANDSAT and MODIS imagery data for this region in 2004 were used in this study. A consecutive series of LANDSAT-like images of the surface reflectance at an 8-day interval were predicted by blending the LANDSAT and MODIS images using an existing algorithm (ESTARFM: Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model). The seasonal dynamics of GPP were then predicted by the satellite-based algorithm. MODIS products explained 60% of observed variations of GPP and underestimated the measured annual GPP (= 1879 g C m−2) by 25–30%; while the satellite-based algorithm with default static parameters explained 88% of observed variations of GPP but overestimated GPP during the growing seasonal by about 20–25%. The optimization of the satellite-based algorithm using a data-model fusion technique with the assistance of EC flux tower footprint modelling reduced the biases in daily GPP estimations from about 2.24 g C m−2 day−1 (non-optimized, ~43.5% of mean measured daily value) to 1.18 g C m−2 day−1 (optimized, ~22.9% of mean measured daily value). The remotely sensed GPP using the optimized algorithm can explain 92% of the seasonal variations of EC observed GPP. These results demonstrated the potential combination of the satellite-based algorithm, flux footprint modelling and data-model fusion for improving the accuracy of landscape/regional GPP estimation, a key component for the study of the carbon cycle.

Description: Clouds can significantly affect carbon exchange process between forest ecosystems and the atmosphere by influencing the quantity and quality of solar radiation received by ecosystem's surface and other environmental factors. In this study, we analyzed the effects of cloudiness on net ecosystem exchange of carbon dioxide (NEE) in a temperate broad-leaved Korean pine mixed forest at Changbaishan (CBS) and a subtropical evergreen broad-leaved forest at Dinghushan (DHS), based on the flux data obtained during June–August from 2003 to 2006. The results showed that the response of NEE of forest ecosystems to photosynthetically active radiation (PAR) differed under clear skies and cloudy skies. Compared with clear skies, the light-saturated maximum photosynthetic rate (Pec,max) at CBS under cloudy skies during mid-growing season (from June to August) increased by 34%, 25%, 4% and 11% in 2003, 2004, 2005 and 2006, respectively. In contrast, Pec,max of the forest ecosystem at DHS was higher under clear skies than under cloudy skies from 2004 to 2006. When the clearness index (kt) ranged between 0.4 and 0.6, the NEE reached its maximum at both CBS and DHS. However, the NEE decreased more dramatically at CBS than at DHS when kt exceeded 0.6. The results indicate that cloudy sky conditions are beneficial to net carbon uptake in the temperate forest ecosystem and the subtropical forest ecosystem. Under clear skies, vapor pressure deficit (VPD) and air temperature increased due to strong light. These environmental conditions led to greater decrease in gross ecosystem photosynthesis (GEP) and greater increase in ecosystem respiration (Re) at CBS than at DHS. As a result, clear sky conditions caused more reduction of NEE in the temperate forest ecosystem than in the subtropical forest ecosystem. The response of NEE of different forest ecosystems to the changes in cloudiness is an important factor that should be included in evaluating regional carbon budgets under climate change conditions.

Description: Isotope ratio infrared spectroscopy (IRIS) provides an in situ technique for measuring δ13C in atmospheric CO2. A number of methods have been proposed for calibrating the IRIS measurements, but few studies have systematically evaluated their accuracy for atmospheric applications. In this study, we carried out laboratory and ambient measurements with two commercial IRIS analyzers and compared the accuracy of four calibration strategies. We found that calibration based on the 12C and 13C mixing ratios (Bowling et al., 2003) and on linear interpolation of the measured delta using the mixing ratio of the major isotopologue (Lee et al., 2005) yielded accuracy better than 0.06‰. Over a 7-day atmospheric measurement in Beijing, the two analyzers agreed to within −0.02 ± 0.18‰ after proper calibration. However, even after calibration the difference between the two analyzers showed a slight correlation with concentration, and this concentration dependence propagated through the Keeling analysis, resulting in a much larger difference of 2.44‰ for the Keeling intercept. The high sensitivity of the Keeling analysis to the concentration dependence underscores the challenge of IRIS for atmospheric research.

Description: The ESA Aeolus mission aims to measure wind profiles from space. In preparation for launch we aim to assess the expected bias in retrieved winds from the Mie and Rayleigh channel signals induced by atmospheric heterogeneity. Observation biases are known to be detrimental when gone undetected in Numerical Weather Prediction (NWP). Aeolus processing equipment should therefore be prepared to detect heterogeneous atmospheric scenes and take measures, e.g., reject or reduce the weight of observations when used in NWP. Radiosondes provide the wind vector at about 10 m resolution. We present a method to simulate co-located cloud and aerosol optical properties from radiosonde observations. We show that cloud layers can be detected along the radiosonde path from radiosonde measured relative humidity and temperature. A parameterization for aerosol backscatter and extinction along the radiosonde path is presented based on a climatological aerosol backscatter profile and radiosonde relative humidity. The resulting high-resolution database of atmospheric wind and optical properties serves as input for Aeolus wind simulations. It is shown that Aeolus wind error variance grows quadratically with bin size and the wind-shear over the bin. Strong scattering aerosol or cloud layers may cause biases exceeding 1ms−1 for typical tropospheric conditions and 1 km Mie channel bin size, i.e., substantially larger than the mission bias requirement of 0.4 ms−1. Advanced level-2 processing of Aeolus winds including estimation of atmosphere optical properties is needed to detect regions with large heterogeneity, potentially yielding biased winds. Besides applicable for Aeolus the radiosonde database of co-located high-resolution wind and cloud information can be used for the validation of atmospheric motion wind vectors (AMV) or to correct their height assignment errors.

Description: In order better to understand the particle-size distribution of particulate PBDEs and their deposition pattern in human respiratory tract, we made an one year campaign 2012–2013 for the measurement of size-resolved aerosol particles at Shanghai urban site. The results showed that particulate PBDEs exhibited a bimodal distribution with a mode peak in the accumulation particle size range and the second mode peak in the coarse particle size ranges. As the number of bromine atoms in the molecule increased, accumulation mode peak intensity increased while coarse mode peak intensity decreased. This change was the consistent with the variation of PBDEs' sub-cooled vapor pressure. Absorption and adsorption process dominated the distribution of PBDEs among the different size particles. Evaluated deposition flux of Σ13PBDE was 26.8 pg h−1, in which coarse particles contributed most PBDEs in head and tracheobronchial regions, while fine mode particles contributed major PBDEs in the alveoli region. In associated with the fact that fine particles can penetrate deeper into the respiratory system, fine particle-bound highly brominated PBDEs can be inhaled more deeply into human lungs and cause a greater risk to human health.

Description: Isotope ratio infrared spectroscopy (IRIS) provides an in-situ technique for measuring δ13C in atmospheric CO2. A number of methods have been proposed for calibrating the IRIS measurements, but few studies have systematically evaluated their accuracy for atmospheric applications. In this study, we carried out laboratory and ambient measurements with two commercial IRIS analyzers and compared the accuracy of four calibration strategies. We found that calibration based on the 12C and 13C mixing ratios (Bowling et al., 2003) and that based on linear interpolation of the measured delta using the mixing ratio of the major isotopologue (Lee et al., 2005) yielded accuracy better than 0.06‰. Over a 7-day atmospheric measurement in Beijing, the two analyzers differed by 9.44 ± 1.65‰ (mean ± 1 standard deviation of hourly values) before calibration and agreed to within −0.02 ± 0.18‰ after properly calibration. However, even after calibration the difference between the two analyzers showed a slight correlation with concentration, and this concentration dependence propagated through the Keeling analysis resulting in a much larger difference of 2.44‰ for the Keeling intercept. The high sensitivity of the Keeling analysis to the concentration dependence underscores the challenge of IRIS for atmospheric research.