Increased CO2 emissions surpass reductions of non-CO2 emissions more under higher experimental warming in an alpine meadow

Exploring the ecological meanings of temperature sensitivity of ecosystem respiration from different methods

Temperature sensitivity (Q10) of ecosystem respiration (Re) is a critical parameter for predicting global terrestrial carbon dynamics and its response to climate warming. However, the determination of Q10 has been controversial. In this study, we scrutinized the underpinnings of three mainstream methods to reveal their relationships in estimating Q10 for Re in the Heihe River Basin, northwest China. Specifically, these methods are Q10 estimated from the long-term method (Q10_long), short-term method (Q10_short), and the low-frequency (Q10_lf) and high-frequency (Q10_hf) signals decomposed by the singular spectrum analysis (SSA) method. We found that: 1) Q10_lf and Q10_long are affected by the confounding effects caused by non-temperature factors, and are 1.8 ± 0.3 and 1.7 ± 0.3, respectively. 2) The high-frequency signals of the SSA method and short-term method have consistent roles in removing the confounding effects. Both Q10_short and Q10_hf reflect the actual response of respiration to temperature. 3) Overall, Q10_long has a larger variability (1.7 ± 0.3) across different biomes, whereas Q10_short and Q10_hf show convergence (1.4 ± 0.2 and 1.3 ± 0.1, respectively). These results highlight the fact that Q10 can be overestimated by the long-term method, whereas the short-term method and high-frequency signals decomposed by the SSA method can obtain closer and convergent values after removing the confounding effects driven by non-temperature factors. Therefore, it is recommended to use the Q10 value estimated by the short-term method or high-frequency signals decomposed by the SSA method to predict carbon dynamics and its response to global warming in Earth system models.

Comparative responses of carbon flux components in recovering bare patches of degraded alpine meadow in the Source Zone of the Yellow River

The patchy degradation of alpine grasslands is a common phenomenon on the Qinghai-Tibetan Plateau, and the presence of bare patches (BP) in degraded grasslands significantly affects the functioning of the alpine meadow ecosystem. The succession of vegetation-recovered BP may lead to significant changes in ecosystem carbon (C) cycling. To date, it is unclear whether different components of net ecosystem carbon exchange (NEE) respond similarly or differently to the succession of recovering BP. Here, we conducted a field monitoring experiment in a degraded alpine meadow, and selected three successional stages for recovering BP to study the response of NEE and its components. We found that the succession of recoevering BP increased ecosystem respiration (ER) during the growing season and decreased ER during the off-growing season, with the differences in annual carbon output between different successional stages being insignificant. However, gross primary productivity increased with the successional gradient, and carbon input at the later stage of succession was significantly greater than that at the middle stage of succession. The succession of recovering BP promoted the carbon sequestration function of the alpine grassland, with the grassland acting as a carbon sink when it reached the state of healthy alpine meadow, while it acted as a carbon source during the middle stage of succession. Compared with BP, the amount of carbon sequested by healthy alpine meadows increased significantly by 219 g·C·m-2·yr-1. We also found that the responses of other components to the succession of recovering BP were inconsistent. In addition, the effects of succession of recovering BP on carbon flux were related to field-monitored variables (soil temperature and water content) and other considered variables (biomass, organic carbon, and microbial biomass carbon). These research findings highlight the importance of restoring vegetation in BPs, and are crucial for predicting the carbon balance in the future and formulating sustainable grassland management strategies.

Effect of greenhouse gas emissions on the life cycle of biomass energy production and conversion under different straw recycling modes

With the gradual growth of greenhouse gas (GHG) emissions during the agricultural cultivation cycle, GHG emissions specific to the production and conversion of biomass energy is becoming increasingly problematic. Current studies lack analysis of net GHG emissions generated during full life cycle of agricultural cultivation, straw use and bioenergy production. This study measures the global warming potential of biomass energy production and conversion processes under different agricultural cultivation cycle systems based on life cycle approach, accompanied by four straw treatment methods: fast pyrolysis, slow pyrolysis, flash pyrolysis and anaerobic fermentation. The demonstration of Heilongjiang Province showed that the net GHG emissions of rice and soybean over 52.39% and 101.57% higher than those of corn, respectively. The amount of standard coal saved by fast pyrolysis treatment, slow pyrolysis treatment and anaerobic fermentation treatment of straw was only 38.38%, 78.02% and 61.98% of that of flash pyrolysis treatment. The relationship between environmental pressure and economic growth was decoupled during 2011-2017 and coupled in 2017-2020. This study contributes to green production of biomass energy. The methodology in this paper can be used to account for and assess the carbon effect of the entire straw recycling chain in any region.

The Effect of Thinning Management on the Carbon Density of the Tree Layers in Larch–Birch Mixed Natural Secondary Forests of the Greater Khingan Range, Northeastern China

Natural secondary forests not only contribute to the total balance of terrestrial carbon, but they also play a major role in the future mitigation of climate change. In China, secondary forests have low productivity and carbon sequestration, which seriously restricts the sustainable development of the forest. Thinning is a core measure of scientific management of forest ecosystems and is a primary natural forest management technique. The carbon density of the tree layer is most affected by thinning. Taking larch–birch mixed natural secondary forests in the Greater Khingan Range, Northeast China, as the research object, we analyzed the changes in tree layer carbon density of secondary forests under different thinning intensities. The results showed that in five thinned groups, when intensity was 49.6%, the diameter at breast height (DBH) and individual tree biomass significantly increased. Thinning had no significant effect on the carbon content of the tree stem, branches and bark, but had significant effects on the carbon content of leaves. Our result showed that the carbon content of birch leaves increased and that of larch decreased. As the thinning intensity increases, the proportion of broad-leaved tree species (birch) increased, yet larch decreased. In the short term, thinning will reduce the total biomass and carbon density of tree layers. However, when the thinning intensity was 49.6%, the carbon accumulation was higher than that of the blank control group (CK group) after thinning for 12 years. This shows that after a long period of time, the carbon density of tree layers will exceed that of the CK group. Reasonable thinning intensity management (49.6% thinning intensity) of natural secondary forests can make trees grow better, and the proportion of broad-leaved trees increases significantly. It can also increase the carbon sequestration rate and lead to more accumulation of biomass and carbon density. This can not only promote the growth of secondary forests, but also shows great potential for creating carbon sinks and coping with climate change.

Preparation of adsorption materials by combustion method: a new approach to the preparation of magnesia doped with trace zirconium

Here, Zr-doping MgO adsorbents were prepared by combustion method with the aid of salicylic acid which was a facile and efficient method for functional material preparation. The one doped with 2% ZrO2 showed excellent performance in CO2 capture.

Simulation of Daily Mean Soil Temperatures for Agricultural Land Use Considering Limited Input Data

A one-dimensional simulation model that simulates daily mean soil temperature on a daily time-step basis, named AGRISOTES (AGRIcultural SOil TEmperature Simulation), is described. It considers ground coverage by biomass or a snow layer and accounts for the freeze/thaw effect of soil water. The model is designed for use on agricultural land with limited (and mostly easily available) input data, for estimating soil temperature spatial patterns, for single sites (as a stand-alone version), or in context with agrometeorological and agronomic models. The calibration and validation of the model are carried out on measured soil temperatures in experimental fields and other measurement sites with various climates, agricultural land uses and soil conditions in Europe. The model validation shows good results, but they are determined strongly by the quality and representativeness of the measured or estimated input parameters to which the model is most sensitive, particularly soil cover dynamics (biomass and snow cover), soil pore volume, soil texture and water content over the soil column.