科研成果

Abstract Climate change will likely increase the total streamflow in most headwaters on the Tibetan Plateau in the next decades, yet the response of runoff components to climate change and permafrost thaw remain largely uncertain. Here, we investigate the changes in runoff components under a changing climate, based on a high-resolution cryosphere-hydrology model (Spatial Processes in Hydrology model, SPHY) and multi-decadal streamflow observations at the upstream (Jimai) and downstream stations (Maqu and Tangnaihai) in the source-region of the Yellow River (SYR). We find that rainfall flow dominates the runoff regime in SYR (contributions of 48%?56%), followed by snowmelt flow (contributions of 26%/23% at Maqu/Tangnaihai). Baseflow is more important at Jimai (32%) than at the the downstream stations (21%?23%). Glacier meltwater from the Anyê Maqên and Bayankala Mountains contributes negligibly to the downstream total runoff. With increasing temperature and precipitation, the increase in total runoff is smaller in the warm and wet downstream stations than in the cold and dry upstream station. This is because of a higher increase in evapotranspiration and a larger reduction in snowmelt flow in the downstream region in response to a warming climate. With temperature increase, there is less increase in rainfall flow in the downstream region due to increased water loss through evapotranspiration. Meanwhile, the decline in snowmelt flow is larger further downstream, which can negatively impact the spring irrigation for the whole Yellow River basin that supports the livelihoods of 140 million people. Importantly, we find that baseflow plays an increasingly important role in the permafrost-dominated upstream region with atmospheric warming and permafrost thaw, accompanied by decreased surface flow. These findings improve our current understanding of how different hydrological processes respond to climate change and provide insights for optimizing hydropower and irrigation systems in the entire Yellow River basin under a rapidly changing climate.

Performance and molecular changes of an aerobic denitrifying phosphorus accumulating bacteria Pseudomonas psychrophila HA-2 have been investigated under different temperatures and ZnO nanoparticles (NPs) exposures. Strain HA-2 removed 95.7% of total nitrogen (TN) and 24.6% of phosphorus at 10°C, which was attributed to the joint up-regulation of intracellular energy metabolism and ribosome. Moreover, with the increase of ZnO NPs from 0 to 100mg/L, TN and phosphurs removal efficiencies decreased from 95.7% to 44.5% and 24.6% to 6.8% at 10°C, respectively, whereas phosphorus removal rate increased from 10.5% to 24.5% at 20°C. Further transcriptomics and proteomics revealed that significant down-regulation of purine and amino acid metabolisms was the main reason for the inhibitory effect at 10°C, while the up-regulation of antioxidant pathways and functional genes expressions was responsible for the promoted phosphorus accumulation at 20°C. This study provides a potential solution for improving biological nutrients removal processes in winter months.

Deep convolutional neural networks (CNNs) have demonstrated impressive performance on many visual tasks. Recently, they became useful models for the visual system in neuroscience. However, it is still not clear what is learned by CNNs in terms of neuronal circuits. When a deep CNN with many layers is used for the visual system, it is not easy to compare the structure components of CNNs with possible neuroscience underpinnings due to highly complex circuits from the retina to the higher visual cortex. Here, we address this issue by focusing on single retinal ganglion cells with biophysical models and recording data from animals. By training CNNs with white noise images to predict neuronal responses, we found that fine structures of the retinal receptive field can be revealed. Specifically, convolutional filters learned are resembling biological components of the retinal circuit. This suggests that a CNN learning from one single retinal cell reveals a minimal neural network carried out in this cell. Furthermore, when CNNs learned from different cells are transferred between cells, there is a diversity of transfer learning performance, which indicates that CNNs are cell specific. Moreover, when CNNs are transferred between different types of input images, here white noise versus natural images, transfer learning shows a good performance, which implies that CNNs indeed capture the full computational ability of a single retinal cell for different inputs. Taken together, these results suggest that CNNs could be used to reveal structure components of neuronal circuits, and provide a powerful model for neural system identification.

Glyoxal and methylglyoxal are vital carbonyl compounds in the atmosphere and play substantial roles in radical cycling and ozone formation. The partitioning process of glyoxal and methylglyoxal between the gas and particle phase via reversible and irreversible pathways could efficiently contribute to secondary organic aerosol (SOA) formation. However, the relative importance of two partitioning pathways still remains elusive, especially in the real atmosphere. In this study, we launched five field observations in different seasons and simultaneously measured glyoxal and methylglyoxal in the gas and particle phase. The field-measured gas-particle partitioning coefficients were 5–7 magnitudes higher than the theoretical ones, indicating the significant roles of reversible and irreversible pathways in the partitioning process. The particulate concentration of dicarbonyls and product distribution via the two pathways were further investigated using a box model coupled with the corresponding kinetic mechanisms. We recommended the irreversible reactive uptake coefficient γ for glyoxal and methylglyoxal in different seasons in the real atmosphere, and the average value of 8.0×10-3 for glyoxal and 2.0×10-3 for methylglyoxal best represented the loss of gaseous dicarbonyls by irreversible gas-particle partitioning processes. Compared to the reversible pathways, the irreversible pathways played a dominant role, with a proportion of more than 90% in the gas-particle partitioning process in the real atmosphere and the proportion was significantly influenced by relative humidity and inorganic components in aerosols. However, the reversible pathways were also substantial, especially in winter, with a proportion of more than 10%. The partitioning processes of dicarbonyls in reversible and irreversible pathways jointly contributed to more than 25% of SOA formation in the real atmosphere. To our knowledge, this study is the first to systemically examine both reversible and irreversible pathways in the ambient atmosphere, strives to narrow the gap between model simulations and field-measured gas-particle partitioning coefficients, and reveals the importance of gas-particle processes for dicarbonyls in SOA formation.

In 1623, the Dutch East India Company (VOC) beheaded twenty-one men on charges of conspiracy and treason in a public execution. Ten of the condemned were employees of the English East India Company (EIC) who had been trading in the Moluccas, better known as the Spice Islands, alongside their Dutch counterparts since the beginning of the century. The incident was hardly the most outrageous mass violence in the region’s tumultuous past. Nevertheless, the EIC dubbed the episode the “Amboyna Massacre,” which gained remarkable significance in various historical writings and unexpected longevity in the British culture in the following centuries. Alison Games’s monograph Inventing the English Massacre is the latest scholarly inquiry into the ambiguous conspiracy and the episode’s long afterlife, spanning British imperial history.

We evaluated the effectiveness of new indices of text comprehension in measuring relative text difficulty. Specifically, we examined the efficacy of automated indices produced by the web-based computational tool Coh-Metrix. In an analysis of 60 instructional science texts, we divided texts into groups that were considered to be more or less difficult to comprehend. The defining criteria were based on Coh-Metrix indices that measure independent factors underlying text coherence: referential overlap and vocabulary accessibility. In order to validate the text difficulty groups, participants read and recalled two “difficult” and two “easy” texts that were similar in topic and length. Easier texts facilitated faster reading times and better recall compared to difficult texts. We discuss the implications of these results in the context of theoretically motivated techniques for improving textbook selection. 

Heating decarbonization is a major challenge for China to meet its 2060 carbon neutral commitment, yet most existing studies on China's carbon neutrality focus on supply side (e.g., grid decarbonization, zero-carbon fuel) rather than demand side (e.g., heating and cooling in buildings and industry). In terms of end use energy consumption, heating and cooling accounts for 50% of the total energy consumption, and heat pumps would be an effective driver for heating decarbonization along with the decarbonization on power generation side. Previous study has discussed the underestimated role of the heat pump in achieving China's goal of carbon neutrality by 2060. In this paper, various investigation and assessments on heat pumps from research to applications are presented. The maximum decarbonization potential from heat pump in a carbon neutral China future could reach around 1532Mton and 670Mton for buildings and industrial heating respectively, which show nearly 2 billion tons CO2 emission reduction, 20% current CO2 emission in China. Moreover, a region-specific technology roadmap for heat pump development in China is suggested. With collaborated efforts from government incentive, technology R&D, and market regulation, heat pump could play a significant role in China's 2060 carbon neutrality.

Indoor air is a complicated matrix. There are various volatile organic compounds (VVOCs) such as formaldehyde and volatile organic compounds (VOCs) such as benzene, toluene, and xylene in indoor air. They are of low concentration and have different polarities. This chapter first introduces the sampling methods, sample treatment, and analysis of VVOCs (mainly carbonyls and ketones) in indoor air. The 2,4-dinitrophenyl-hydrazine (DNPH) derivatization – high-performance liquid chromatography (HPLC) method – is the most commonly used for the determination of VVOCs. Then four sampling methods for VOCs, including active sampling, passive sampling, whole-air sampling, and solid-phase microextraction (SPME), are introduced. Thermal desorption and solvent extraction are two commonly used methods to pretreat the samples for further analysis. GC combined with MS, FID, ECD, or BID is frequently used for the VVOCs, VOCs, quantitation.

It is challenging to simulate the snapback behaviors under electrostatic discharge (ESD) stresses due to the limitation of simulation program with integrated circuit emphasis (SPICE) simulation tools. In this brief, a new model is proposed to investigate the avalanche breakdown effect using the voltage-controlled current source (VCCS), which greatly facilitates the calculation of the avalanche multiplication factor M and improves the convergence characteristics. In particular, this new method transfers the exponential relationship of M into the linear relationship of the VCCS gain. The versatility of the model is validated by its operations in various ESD protection circuits with MOS as the discharge device, while the scalability is demonstrated by its applications in varied device sizes.

With the Kigali Amendment (KA) coming into effect in China, the control of hydrofluorocarbons (HFCs) emissions has become more imperative. The mobile air-conditioning (MAC) sector is one of the important HFCs consumer sectors, and therefore studying its feasible mitigation paths and costs is of great significance to China's successful implementation of KA. This study used the bottom-up method with updated emission factors to re-evaluate the emission inventory of HFCs from the MAC sector in China from 2005 to 2020. The average annual growth rate of HFCs consumption in the MAC sector is 9.8%, and HFCs emissions have increased from 5.8 (5.3‒6.2) kt in 2005 to 22.2 (20.6‒23.8) kt in 2020, with an average annual growth rate of 8.8%. Using the Gompertz model combined with the Weibull function of vehicle survival rate, the ownership and new registrations of internal combustion engine vehicles (ICEVs) and electric vehicles (EVs) in China are predicted. The ownership of ICEVs and EVs is projected to be 310 million and 91 million in 2030, respectively and 2 million and 641 million in 2060, respectively. HFCs emissions in the MAC sector would reach 59.8 (55.3‒64.3) kt (80.0‒93.0 Mt CO2- eq) in 2060 if without any control measure. To implement the KA, the cumulative of 1.6 Gt CO2-eq emissions would be reduced. Under the other two accelerated mitigation scenarios, the MAC sector's HFCs will reach their emissions peak in 2028 and 2025 and achieve zero emissions in 2050 and 2046, respectively. Under the accelerated mitigation with recovery scenario, the cumulative emissions are only 15.0% of the business as usual (BAU) scenario. Using HFO-1234yf as the substitute, the unit abatement cost of the MAC sector is 27.3‒37.4 USD t−1 CO2-eq.

Both antibiotics and sediments can affect the denitrification in aquatic systems. However, little is known how an-tibiotics influence the denitrification in the presence of sediments. Here, the effects of antibiotics (sulfamethox-azole, tetracycline and ofloxacin) on denitrification in the absence and presence of sediments were investigated. The influencing mechanisms were revealed by quantifying the denitrification functional genes (DNGs), 16S-seq of bacteria, and antibiotic resistance genes (ARGs). The results showed that the presence of antibiotics inhibited NO3-N reduction by decreasing the abundances of narG, nirK, nosZ, total DNGs, and denitrifying bacteria. How-ever, the inhibition effect was alleviated by sediments, which promoted the growth of bacteria and decreased the selective pressure of antibiotics as the vector of bacteria and antibiotics, thus increasing the abundances of denitrifying bacteria and all the DNGs. Partial least-squares path model disclosed that antibiotics had negative ef-fects on bacteria, ARGs and DNGs, while sediments had negative effects on ARGs but positive effects on bacteria and DNGs. The network analysis further revealed the close relation of the genera Bacillus, Acinetobacter, and En-terobacter with the ARGs and DNGs. The findings are helpful to understand the denitrification in antibiotic-polluted natural waters. (C) 2021 Elsevier B.V. All rights reserved.

Abstract We present the first-generation full-waveform tomographic model (SinoScope 1.0) for the crust-mantle structure beneath China and adjacent regions. The three-component seismograms from 410 earthquakes recorded at 2,427 stations are employed in iterative gradient-based inversions for three successively broadened period bands of 70–120 s, 50–120 s, and 30–120 s. Synthetic seismograms were computed using GPU-accelerated spectral-element simulations of seismic wave propagation in 3-D anelastic models, and Fréchet derivatives were calculated based on an adjoint-state method facilitated by a checkpointing algorithm. The inversion involved 352 iterations, which required 18,600 wavefield simulations. SinoScope 1.0 is described in terms of isotropic P-wave (VP), horizontally and vertically polarized S-wave velocities (VSH and VSV), and mass density (ρ), which are independently constrained with the same data set coupled with a stochastic L-BFGS quasi-Newton optimization scheme. It systematically reduced differences between observed and synthetic full-length seismograms. We performed a detailed resolution analysis by repairing input random parametric perturbations, indicating that resolution lengths can approach the half propagated wavelength within the well-covered areas. SinoScope 1.0 reveals strong lateral heterogeneities in the lithosphere, and features correlate well with geological observations, such as sedimentary basins, Holocene volcanoes, Tibetan Plateau, Philippine Sea Plate, and various tectonic units. The asthenosphere lies below the lithosphere beneath East and Southeast Asia, bounded by subduction trenches and cratonic blocks. Furthermore, we observe an enhanced image of well-known slabs along strongly curved subduction zones, which do not exist in the initial model.