•We show the increasing of NPV/IRR values and the failure of quota instrument.•We show the dynamic interactions of FIT system.•The tariffs should be adjusted frequently to keep IRR values at 8–12%.
...In 2011 China initiated policies to promote the adoption of solar photovoltaic (PV) using feed-in tariff (FIT) policies. Since then the PV domestic market expanded substantially. In the past six years, the FIT policies were updated (adjustment of tariff levels, division of three FIT regions, setting of installation quotas) to address emerging problems such as PV waste, explosive installation, unbalanced spatial distribution. This paper aims to investigate the historical development and implementation of FIT policies in China from 2011 to 2016. The tools of net present value (NPV)/internal rate of return (IRR), learning curve and the system dynamics are employed to show the degree of economic incentives of FIT policies, to understand the learning rate of centralized PV systems, and to study the dynamic mechanism of the FIT system. We conclude that in the near term the tariff levels should be adjusted more frequently to keep IRR values in the range of 8–12%, and a tight quota combined with the deployment of ultra-high voltage (UHV) lines should be continued for the provinces with severe PV waste.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Data assimilation algorithms rely on a basic assumption of an unbiased
observation error. However, the presence of inconsistent measurements with
nontrivial biases or inseparable baselines is ...unavoidable in practice.
Assimilation analysis might diverge from reality since the data assimilation
itself cannot distinguish whether the differences between model simulations
and observations are due to the biased observations or model deficiencies.
Unfortunately, modeling of observation biases or baselines which show strong
spatiotemporal variability is a challenging task. In this study, we report
how data-driven machine learning can be used to perform observation bias
correction for data assimilation through a real application, which is the
dust emission inversion using PM10 observations. PM10 observations are considered unbiased; however, a bias correction is necessary if they are used as a proxy for dust during dust storms since they actually represent a sum of dust particles and non-dust aerosols. Two observation bias correction methods have been designed in order to use PM10 measurements as proxy for the dust storm loads under severe dust conditions. The first one is the conventional chemistry transport model (CTM) that simulates life cycles of non-dust aerosols. The other one
is the machine-learning model that describes the relations between the
regular PM10 and other air quality measurements. The latter is trained
by learning using 2 years of historical samples. The machine-learning-based non-dust model is shown to be in better agreement with
observations compared to the CTM.
The dust emission inversion tests have been performed, through
assimilating either the raw measurements or the bias-corrected dust observations
using either the CTM or machine-learning model. The emission field, surface
dust concentration, and forecast skill are evaluated. The worst case is when
we directly assimilate the original observations. The forecasts driven by the
a posteriori emission in this case even result in larger errors than the
reference prediction. This shows the necessities of bias correction in data
assimilation. The best results are obtained when using the machine-learning
model for bias correction, with the existing measurements used more
precisely and the resulting forecasts close to reality.
The pathogenesis of lung cancer, the most common cancer, is complex and unclear, leading to limited treatment options and poor prognosis. To provide molecular insights into lung cancer development, ...we investigated the function and underlying mechanism of SH2B3 in the regulation of lung cancer. We indicated SH2B3 was diminished while TGF-β1 was elevated in lung cancer tissues and cells. Low SH2B3 level was correlated with poor prognosis of lung cancer patients. SH2B3 overexpression suppressed cancer cell anoikis resistance, proliferation, migration, invasion, and EMT, while TGF-β1 promoted those processes via reducing SH2B3. SH2B3 bound to JAK2 and SHP2 to repress JAK2/STAT3 and SHP2/Grb2/PI3K/AKT signaling pathways, respectively, resulting in reduced cancer cell anoikis resistance, proliferation, migration, invasion, and EMT. Overexpression of SH2B3 suppressed lung cancer growth and metastasis in vivo. In conclusion, SH2B3 restrained the development of anoikis resistance and EMT of lung cancer cells via suppressing JAK2/STAT3 and SHP2/Grb2/PI3K/AKT signaling cascades, leading to decreased cancer cell proliferation, migration, and invasion.
In 2017 about 37% of the world's wind turbines and 50% of the world's photovoltaic (PV) panels are installed in China. But at the same time a huge amount of wind power and PV power is wasted mainly ...because of insufficient flexibility of thermal power which is the dominant source in China's electricity system. This paper aims to assess the flexibility requirements for thermal power plants to accommodate large-scale variable renewable energies (VREs). This paper constructs three scenarios for the reference year of 2030, where VREs account for 16%, 19% and 22% in the electricity system respectively, and simulates corresponding residual load time series (residual load = load − hydropower − nuclear power − wind power − PV power). We find that the current average 1%/min ramp rate of thermal power plants is basically sufficient to deal with ramps in residual load in the future. But the current average 60% minimum load level of thermal power plants has to be improved to 40% or even 30%, otherwise the economic losses of VREs curtailment will be as high as 947.2×108 – 1632.0×108 CNY per year in the future. It is necessary and beneficial for the central authority to invest in retrofitting the existing huge thermal power plants to improve their minimum load level.
•This paper simulates the future VREs scenarios for the year of 2030.•1%/min ramp rate of thermal power is sufficient to follow ramps in residual load.•Minimum load level of thermal power has to be improved to 40% or even 30%.•It is a huge economic benefit to improve minimum load level of thermal power.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Building stock growth around the world drives extensive material consumption and environmental impacts. Future impacts will be dependent on the level and rate of socioeconomic development, along with ...material use and supply strategies. Here we evaluate material-related greenhouse gas (GHG) emissions for residential and commercial buildings along with their reduction potentials in 26 global regions by 2060. For a middle-of-the-road baseline scenario, building material-related emissions see an increase of 3.5 to 4.6 Gt CO2eq yr-1 between 2020-2060. Low- and lower-middle-income regions see rapid emission increase from 750 Mt (22% globally) in 2020 and 2.4 Gt (51%) in 2060, while higher-income regions shrink in both absolute and relative terms. Implementing several material efficiency strategies together in a High Efficiency (HE) scenario could almost half the baseline emissions. Yet, even in this scenario, the building material sector would require double its current proportional share of emissions to meet a 1.5 °C-compatible target.
Emission inversion using data assimilation fundamentally relies on having the correct assumptions about the emission background error covariance. A perfect covariance accounts for the uncertainty ...based on prior knowledge and is able to explain differences between model simulations and observations. In practice, emission uncertainties are constructed empirically; hence, a partially unrepresentative covariance is unavoidable. Concerning its complex parameterization, dust emissions are a typical example where the uncertainty could be induced from many underlying inputs, e.g., information on soil composition and moisture, land cover and erosive wind velocity, and these can hardly be taken into account together. This paper describes how an adjoint model can be used to detect errors in the emission uncertainty assumptions. This adjoint-based sensitivity method could serve as a supplement of a data assimilation inverse modeling system to trace back the error sources in case large observation-minus-simulation residues remain after assimilation based on empirical background covariance.
Nitric oxide generated by endothelial nitric oxide synthase (eNOS) plays an important role in maintaining cardiovascular homeostasis. Under various pathological conditions, abnormal expression of ...eNOS contributes to endothelial dysfunction and the development of cardiovascular diseases. A variety of pathological stimuli has been reported to decrease eNOS expression mainly through decreasing eNOS mRNA stability by regulating the binding of several cytosolic proteins to the cis-acting sequences within eNOS mRNA 3′ untranslated regions. However, the detailed mechanisms remain elusive. Because microRNAs inhibit gene expression through binding to the 3′ untranslated regions of their target mRNAs, microRNAs may be the important posttranscriptional modulators of eNOS expression. Here, we provided evidence that eNOS is a direct target of miR-155. Overexpression of miR-155 decreased, whereas inhibition of miR-155 increased, eNOS expression and NO production in human umbilical vein endothelial cells and acetylcholine-induced endothelium-dependent vasorelaxation in human internal mammary arteries. Inflammatory cytokines including tumor necrosis factor-α increased miR-155 expression. Inhibition of miR-155 reversed tumor necrosis factor-α–induced downregulation of eNOS expression and impairment of endothelium-dependent vasorelaxation. Moreover, we observed that simvastatin attenuated tumor necrosis factor-α–induced upregulation of miR-155 and ameliorated the effects of tumor necrosis factor-α on eNOS expression and endothelium-dependent vasodilation. Simvastatin decreased miR-155 expression through interfering mevalonate-geranylgeranyl-pyrophosphate-RhoA signaling pathway. These findings indicated that miR-155 is an essential regulator of eNOS expression and endothelium-dependent vasorelaxation. Inhibition of miR-155 may be a new therapeutic approach to improve endothelial dysfunction during the development of cardiovascular diseases.
Aerosol optical depths (AODs) from the new Himawari‐8 satellite instrument have been assimilated in a dust simulation model over East Asia. This advanced geostationary instrument is capable of ...monitoring the East Asian dust storms which usually have great spatial and temporal variability. The quality of the data has been verified through a comparison with AErosol RObotic NETwork AODs. This study focuses on extreme dust events only when dust aerosols are dominant; promising results are obtained in AOD assimilation experiments during a case in May 2017. The dust emission fields that drive the simulation model are strongly improved by the inverse modeling, and consequently, the simulated dust concentrations are in better agreements with the observed AOD as well as ground‐based observations of PM10. However, some satellite AODs show significant inconsistence with the simulations and the PM10 and AErosol RObotic NETwork observations, which might arise from retrieval errors over a partially clouded scene. The data assimilation procedure therefore includes a screening method to exclude these observations in order to avoid unrealistic results. A dust mask screening method is designed, which is based on selecting only those observations where the deterministic model produces a substantial amount of dust. This screen algorithm is tested to give more accurate result compared to the traditional method based on background covariance in the case study. Note that our screen method would exclude valuable information in case the model is not able to simulate the dust plume shape correctly; hence, applications in related studies require inspections of simulations and observations by user.
Key Points
The dust storm emission inversion is conducted by assimilating the new Himawari‐8 AODs with high spatiotemporal resolutions
A novel dust mask screen‐based selection is designed to exclude those less representative AODs
The estimated dust forecast shows better agreements with independent PM10 data
Full text
Available for:
DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
Imaging-type monitoring techniques are used in monitoring dynamic processes in many domains, including medicine, engineering, and geophysics. This paper aims to propose an efficient workflow for ...application of such data for the conditioning of simulation models. Such applications are very common in e.g. the geosciences, where large-scale simulation models and measured data are used to monitor the state of e.g. energy and water systems, predict their future behavior and optimize actions to achieve desired behavior of the system. In order to reduce the high computational cost and complexity of data assimilation workflows for high-dimensional parameter estimation, a residual-in-residual dense block extension of the U-Net convolutional network architecture is proposed, to predict time-evolving features in high-dimensional grids. The network is trained using high-fidelity model simulations. We present two examples of application of the trained network as a surrogate within an iterative ensemble-based workflow to estimate the static parameters of geological reservoirs based on binary-type image data, which represent fluid facies as obtained from time-lapse seismic surveys. The differences between binary images are parameterized in terms of distances between the fluid-facies boundaries, or fronts. We discuss the impact of the choice of network architecture, loss function, and number of training samples on the accuracy of results and on overall computational cost. From comparisons with conventional workflows based entirely on high-fidelity simulation models, we conclude that the proposed surrogate-supported hybrid workflow is able to deliver results with an accuracy equal to or better than the conventional workflow, and at significantly lower cost. Cost reductions are shown to increase with the number of samples of the uncertain parameter fields. The hybrid workflow is generic and should be applicable in addressing inverse problems in many geophysical applications as well as other engineering domains.
•We proposed a knowledge-based hybrid workflow for reservoir heterogeneity characterization.•The state-of-ther-art residual-in-residual dense block is employed to address highly-complex non-Gaussian models.•Results show that a significant reduction in computational cost was achieved while the accuracy remains on geological parameter estimations.•The hybrid workflow is generic and should be applicable in many geophysical applications as well as other engineering domains.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The present study aimed to evaluate the clinical outcomes of magnetic-activated cell sorting (MACS) in sperm preparation for male subjects with a sperm DNA fragmentation index (DFI) ≥30%. A total of ...86 patients who had undergone their first long-term long protocol were selected. The protocol involved in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) cycles, and the patients were divided into the MACS or control groups. The MACS group included sperm samples analyzed with MACS that were combined with density gradient centrifugation (DGC) and the swim-up (SU) technique (n = 39), and the control group included sperm samples prepared using standard techniques (DGC and SU; n = 41). No differences were noted with regard to basic clinical characteristics, number of oocytes retrieved, normal fertilization rate, cleavage rate, or transplantable embryo rate between the two groups in IVF/ICSI. In addition, the clinical pregnancy and implantation rates of the first embryo transfer cycles indicated no significant differences between the two groups. However, there was a tendency to improve the live birth rate (LBR) of the first embryo transfer cycle (63.2% vs 53.9%) and the cumulative LBR (79.5% vs 70.7%) in the MACS group compared with the control group. Moreover, the number of transferred embryos (mean ± standard deviation s.d.: 1.7 ± 0.7 vs 2.3 ± 1.6) and the transfer number of each retrieved cycle (mean ± s.d.: 1.2 ± 0.5 vs 1.6 ± 0.8) were significantly lower in the MACS group than those in the control group. Thus, the selection of nonapoptotic spermatozoa by MACS for higher sperm DFI could improve assisted reproductive clinical outcomes.
PDF
