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This paper applies the context-dependent total-factor energy efficiency (CD-TFEE) to determine the multi-layer disaggregate energy efficiency frontiers of twenty administrative regions in Taiwan for the year of 2016. The CD-TFEE overcomes the shortcoming of conventional TFEE index that TFEE is not able to find the “closest target” for each inefficient region in the short run. Furthermore, the CD-TFEE scores here deal with four types of energy inputs (electricity for production, electricity for household and non-household lighting, diesel sales, and gasoline sales), illustrating that multi-layer TFEE frontiers for each energy input in the case of Taiwan can be computed. Empirical results indicate that there are three levels of TFEE frontiers for electricity for production and four levels for other types of energy inputs. In addition, New Taipei City, Taipei City, Keelung City, and Penghu County are at the top level of TFEE frontier for all four energy inputs. This paper also demonstrates that the CD-TFEE procedure generates results different from the CD-DEA introduced by Seiford and Zhu (2003).

Abstract The hybrid pneumatic power system (HPPS) proposed in this research replaces the battery’s electric-chemical energy with flow work and optimizes the management and utilization of the energy. This power system is able to keep the internal-combustion engine working at its optimal condition and turn its waste energy into effective mechanical energy and so enhance the thermal efficiency of the whole system. Using computer simulation software ITI-SIM, this study simulates the overall dynamic characteristics of the system in accordance with the regulated running-vehicle test-mode ECE47, and, with experimental verification and analysis, proves that this system can meet the requirements of the standard running-car mode. As for recycling the waste energy, the experimental results show that this design could offset the shortcomings of the low-density of pneumatic power and so effectively enhance the efficiency of the whole system.

Atmospheric mercury (Hg) cycling is sensitive to climate-driven changes, but links with various teleconnections remain unestablished. Here, we revealed the El Niño-Southern Oscillation (ENSO) influence on gaseous elemental mercury (GEM) concentrations recorded at a background station in East Asia using the Hilbert-Huang transform (HHT). The timing and magnitude of GEM intrinsic variations were clearly distinguished by ensemble empirical mode decomposition (EEMD), revealing the amplitude of the GEM concentration interannual variability (IAV) is greater than that for diurnal and seasonal variability. We show that changes in the annual cycle of GEM were modulated by significant IAVs at time scales of 2-7 years, highlighted by a robust GEM IAV-ENSO relationship of the associated intrinsic mode functions. With confirmation that ENSO modulates the GEM annual cycle, we then found that weaker GEM annual cycles may have resulted from El Niño-accelerated Hg evasion from the ocean. Furthermore, the relationship between ENSO and GEM is sensitive to extreme events (i.e., 2015-2016 El Niño), resulting in perturbation of the long-term trend and atmospheric Hg cycling. Future climate change will likely increase the number of extreme El Niño events and, hence, could alter atmospheric Hg cycling and influence the effectiveness evaluation of the Minamata Convention on Mercury.

Lignocellulose biomass is one of the most abundant resources for sustainable biofuels. However, scaling up the biomass-to-biofuels conversion process for widespread usage is still pending due to the high cost of enzymes and the labor-intensive need for substrate-dependent enzyme mixtures. Current research efforts are therefore targeted at searching for or engineering lignocellulolytic enzymes of high efficiency. Some microorganisms produce multi-enzyme complexes called cellulosomes for increased degradation efficiency up to 50-fold. Here we examined the presence of cellulosomes in all bacterial and fungal species with protein sequences available. By using cellulosome proteins of one bacteria and one fungi as search queries, a sequence similarity search was performed in two databases: 1) the non-redundant database and 2) the EnsemblFungi database.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.AS-RCEC.TaiESM1.ssp585' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The Taiwan Earth System Model 1.0 climate model, released in 2018, includes the following components: aerosol: SNAP (same grid as atmos), atmos: TaiAM1 (0.9x1.25 degree; 288 x 192 longitude/latitude; 30 levels; top level ~2 hPa), atmosChem: SNAP (same grid as atmos), land: CLM4.0 (same grid as atmos), ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m), seaIce: CICE4. The model was run by the Research Center for Environmental Changes, Academia Sinica, Nankang, Taipei 11529, Taiwan (AS-RCEC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, ocean: 100 km, seaIce: 50 km.

# Low Evidence Yet for the Escalator to Extinction in Mountain Biota [https://doi.org/10.5061/dryad.83bk3jb1m](https://doi.org/10.5061/dryad.83bk3jb1m) To assess range shifts of global mountain species under warming climate, we compiled 2,200 quadruplets of historic (1849-1998) and modern (2003-2017) elevational range limits, both the upper and lower limit, for a total 2069 terrestrial plant and animal species, extracted from 21 peer-reviewed studies conducted across 23 montane regions. To test the three above-listed predictions of climate-driven risks, we analyzed the four metrics by pairs of response variables: lower and upper limit shifts combined (Model 1) as well as range extent change and midpoint shift combined (Model 2). We fitted two separate Bayesian multivariate response models (Model 1 and Model 2), applying a multivariate mixed-effects modelling approach (MMMs), to estimate correlations between pairs of response variables. Model significance for the three predictions of climate-driven risks was obtained against null models. ## Description of the data and file structure **Data.csv**: This CSV file contains species range shift records 2,200 quadruplets of historic (1849-1998) and modern (2003-2017) elevational range limits for a total 2069 terrestrial plant and animal species, extracted from 21 peer-reviewed studies. **Metadata.xlsx**: This XLSX file contains metadata for Data.xlsx. **Publication_list.xlsx**: This XLSX file lists the scientific reports included in the dataset. **1_MMMs.R**: This script contains the code used to conduct multivariate mixed-effects model analysis. **2_Null_model_example.R**: This script contains the code used to construct a null model by randomizing the boundary shifts with replacement among species historically at different elevational positions. Mountain biodiversity is rapidly reorganizing as species migrate upslope to track climate warming. Despite the potential threats of mountaintop extirpation, range shift gaps, and lowland biodiversity attrition, empirical evidence of these risks remains scarce. We analyzed 8,800 records of historical and modern elevational range limits for 440 animals and 1,629 plant species and found that the risk of mountaintop extirpation did not exceed random expectations. Upper limits expanded for species with narrow ranges or lowland affinities, but lower limits showed little contraction, implying scant risk to date of these threats, even in the tropics. Yet the predominance of upslope expansion combined with delayed mountaintop extirpations points to a biotic homogenization, which may profoundly alter biotic interactions in mountain ecosystems with increasing warming.

Silver-based Al-doped ZnO (AZO) multilayer coatings were prepared on glass by e-beam evaporation techniques. Optimization of the deposition conditions of both AZO and Ag layers were performed for better electrical and optical properties. The properties of the multilayers were affected by the deposition process of both AZO and Ag layers. The best multilayer coatings exhibit low sheet resistance of 5.34 Ω/sq and transmittance of more than 85%. The coatings have satisfactory properties of low resistance and high transmittance for application as transparent conductive electrodes.

The Chinese electric power industry, including its coal industry and other energy industries that are not efficient, contributes to China’s serious energy shortages and environmental contamination. The governing authority considers energy conservation to be one of the most prominent national targets, and has formulated various plans for decarbonizing the power system. Applying the trans-log cost function, this paper examined the trans-log cost function to analyze the potential inter-factor substitution among energy, capital and labor. We also investigated what role human capital played in energy substitution for the electric power sector during the period from 1981 to 2017. Three key results were derived: (1) energy is price-insensitive, (2) there exists large substitution sustainability between both capital and labor with energy, and (3) human capital input not only enhances the extent of energy substitutability with capital and labor but also is a substitute to energy itself. These findings imply that the liberalization of the electric price mechanism is conducive to lessening energy use and augmenting non-energy intensiveness, and that energy conservation technology could become more sustainable by investing more capital in the electricity sector, thereby achieving a capital–energy substitution and a decrease of CO2 emissions. We further suggest that the priority for the Chinese electric power industry should be to attach more importance to increasing human capital input.

A big surplus of power supply, especially during the off-peak period, causes operation problems to the present Taiwan Power Company (Taipower) system. Taipower is facing the difficulties of committing a large amount of nuclear generation at a low base load level.