IMECE2010-40121 The Entropy Analysis on NH 3 /CO 2 Cascade Refrigeration Cycle

ABSTRACT This paper introduces a cascade refrigeration cycle that uses natural refrigerants of CO 2 and NH 3 at low temperature. It introduces the character of CO 2 and NH 3 , besides analyzes the cascade refrigeration cycle. The optimal intermediate temperature of NH 3 /CO 2 cascade refrigeration cycle is determined by the entropy production minimization method．We analyze the four processes entropy production in both CO 2 cycle（LT side）and NH 3 cycle（HT side） and research how the total entropy production changes in the conditions of different T 0 ，different T CL and different △T. We also find that in order to enhance the efficiency of NH 3 /CO 2 cascade refrigeration cycle，it is necessary to reduce △T. It can be concluded that NH 3 /CO 2 cascade refrigeration cycle has a good future

Interferon regulatory factor 2 binding protein 2b regulates neutrophil versus macrophage fate during zebrafish definitive myelopoiesis

International audienceInterferon regulatory factor 2 binding protein 2b regulates neutrophil versus macrophage fate during zebrafish definitive myelopoiesis

Tree diversity depending on environmental gradients promotes biomass stability via species asynchrony in China's forest ecosystems

There is mounting evidence that biodiversity promotes ecological stability in changing environments. However, understanding diversity–stability relationships and their underlying mechanisms across large-scale tree diversity and natural environmental gradients are still controversial and largely lacking. We used thirty-nine 0.12 ha long-term permanent forest plots spanning China's various forest types to test the effects of multiple abiotic (climate, soil, age and topography) and biotic factors (taxonomic and structural diversity, functional diversity and community-mean traits, and species asynchrony) on biomass stability and its components (mean biomass and biomass variability) over time. We used multiple analytical methods to identify the best explanatory variables and complicated causal relationships for community biomass stability. Our results showed that species richness increased biomass stability by promoting species asynchrony. Structural and functional diversity had a weaker effect on biomass stability. Forest age and structural diversity increased mean biomass and biomass variability significantly and simultaneously. Communities dominated by tree species with high wood density had high biomass stability. Soil nitrogen enhanced biomass stability directly and indirectly through its effects on mean biomass. Soil nitrogen to phosphorus ratio increased biomass stability via increasing species asynchrony. Precipitation indirectly increased biomass stability by affecting tree diversity. Moreover, the direct and indirect effects of soil nutrients on biomass stability were greater than that of climate variables. Our results suggest that species asynchrony is the main mechanism proposed to explain the stabilizing effect of diversity on community biomass, supporting two mechanisms, namely, the biodiversity insurance hypothesis and complementary dynamics. Soil and climate factors also play an important role in shaping diversity–stability relationships. Our results provide a new insight into how tree diversity affects ecosystem stability across diverse community types and large-scale environmental gradients

Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: a perspective from long‐term data assimilation

It is critical to accurately estimate carbon (C) turnover time as it dominates the uncertainty in ecosystem C sinks and their response to future climate change. In the absence of direct observations of ecosystem C losses, C turnover times are commonly estimated under the steady state assumption (SSA), which has been applied across a large range of temporal and spatial scales including many at which the validity of the assumption is likely to be violated. However, the errors associated with improperly applying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestrations have yet to be fully quantified. Here, we developed a novel model-data fusion framework and systematically analyzed the SSA-induced biases using time-series data collected from 10 permanent forest plots in the eastern China monsoon region. The results showed that (a) the SSA significantly underestimated mean turnover times (MTTs) by 29%, thereby leading to a 4.83-fold underestimation of the net ecosystem productivity (NEP) in these forest ecosystems, a major C sink globally; (b) the SSA-induced bias in MTT and NEP correlates negatively with forest age, which provides a significant caveat for applying the SSA to young-aged ecosystems; and (c) the sensitivity of MTT to temperature and precipitation was 22% and 42% lower, respectively, under the SSA. Thus, under the expected climate change, spatiotemporal changes in MTT are likely to be underestimated, thereby resulting in large errors in the variability of predicted global NEP. With the development of observation technology and the accumulation of spatiotemporal data, we suggest estimating MTTs at the disequilibrium state via long-term data assimilation, thereby effectively reducing the uncertainty in ecosystem C sequestration estimations and providing a better understanding of regional or global C cycle dynamics and C-climate feedback

The role of functional uniqueness and spatial aggregation in explaining rarity in trees

Aim: Determining the drivers of species rarity is fundamental for understanding and conserving biodiversity. Rarity of a given species within its community may arise due to exclusion by other ecologically similar species. Conversely, rare species may occupy habitats that are rare in the landscape or they may be ill-suited to all available habitats. The first mechanism would lead to common and rare species occupying similar ecological space defined by functional traits. The second mechanism would result in common and rare species occupying dissimilar ecological space and spatial aggregation of rare species, either because they are specialists in rare habitats or because rare species tend to be dispersal limited. Here, we quantified the contribution of locally rare species to community functional richness and the spatial aggregation of species across tree communities world-wide to address these hypotheses. Location: Asia and the Americas. Time period: 2002 to 2012 (period that considers the censuses for the plots used). Major taxa studied: Angiosperm and Gymnosperm trees. Methods: We compiled a dataset of functional traits from all the species present in eight tree plots around the world to evaluate the contribution of locally rare species to tree community functional richness using multi- and univariate approaches. We also quantified the spatial aggregation of individuals within species at several spatial scales as it relates to abundance. Results: Locally rare tree species in temperate and tropical forests tended to be functionally unique and are consistently spatially clustered. Furthermore, there is no evidence that this pattern is driven by pioneer species being locally rare. Main conclusions: This evidence shows that locally rare tree species disproportionately contribute to community functional richness, and we can therefore reject the hypothesis that locally rare species are suppressed by ecologically similar, but numerically dominant, species. Rather, locally rare species are likely to be specialists on spatially rare habitats or they may be ill-suited to the locally available environments

Direct and indirect effects of climate on richness drive the latitudinal diversity gradient in forest trees

Data accessibility statement: Full census data are available upon reasonable request from the ForestGEO data portal, http://ctfs.si.edu/datarequest/ We thank Margie Mayfield, three anonymous reviewers and Jacob Weiner for constructive comments on the manuscript. This study was financially supported by the National Key R&D Program of China (2017YFC0506100), the National Natural Science Foundation of China (31622014 and 31570426), and the Fundamental Research Funds for the Central Universities (17lgzd24) to CC. XW was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB3103). DS was supported by the Czech Science Foundation (grant no. 16-26369S). Yves Rosseel provided us valuable suggestions on using the lavaan package conducting SEM analyses. Funding and citation information for each forest plot is available in the Supplementary Information Text 1.Peer reviewedPostprin

Space advanced technology demonstration satellite

The Space Advanced Technology demonstration satellite (SATech-01), a mission for low-cost space science and new technology experiments, organized by Chinese Academy of Sciences (CAS), was successfully launched into a Sun-synchronous orbit at an altitude of similar to 500 km on July 27, 2022, from the Jiuquan Satellite Launch Centre. Serving as an experimental platform for space science exploration and the demonstration of advanced common technologies in orbit, SATech-01 is equipped with 16 experimental payloads, including the solar upper transition region imager (SUTRI), the lobster eye imager for astronomy (LEIA), the high energy burst searcher (HEBS), and a High Precision Magnetic Field Measurement System based on a CPT Magnetometer (CPT). It also incorporates an imager with freeform optics, an integrated thermal imaging sensor, and a multi-functional integrated imager, etc. This paper provides an overview of SATech-01, including a technical description of the satellite and its scientific payloads, along with their on-orbit performance

Two ultraviolet radiation datasets that cover China

Ultraviolet (UV) radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization's measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes