China's commitment to the UNFCCC to peak its emissions by 2030, or sooner, signaled a long anticipated shift in China's model of development with far reaching consequences. Cities in China, and particularly the residential sector in cities, will be charged with making significant reductions in emissions growth even as rates of urbanization continue to climb. Focusing on Beijing and Shanghai, this paper carries out a measures-based economic analysis of low carbon investment opportunities in the residential sector. Results find significant opportunity: between 2015 and 2030, BAU levels of CO2 emissions could be reduced by 10.2% in Beijing and 6.8% in Shanghai with the adoption of economically attractive low carbon measures. While these headline results underline the case for low carbon investment in the residential sectors of these megacities in China, a closer analysis provides insights for understanding the economics of decarbonisation in cities more generally. (C) 2016 The Authors. Published by Elsevier Ltd.
State-of-the-art silicon water splitting photoelectrochemical cells employ oxide protection layers that exhibit electrical conductance in between that of dielectric insulators and electronic conductors, optimizing both built-in field and conductivity. The SiO2-like layer interposed between a deposited protective oxide film and its Si substrate plays a key role as a tunnel oxide that can dominate the total device impedance. In this report, we investigate the effects of changes in interfacial SiO2 resistance and capacitance in the oxide bilayer through both solid state leakage current and capacitance–voltage measurements and through electrochemical methods applied to water splitting cells. Modelling is performed to describe both types of data in a simple and intuitive way, allowing for insights to be developed into the connections among both the dielectric (charge storage) and conductive (charge transport) properties of bilayer protective oxides and their effects on oxygen evolution performance. Finally, atomic layer deposited (ALD) Al2O3 is studied as an insulator layer with conductivity intermediate between that of tunnel oxide SiO2 and the more conductive ALD-TiO2, to further generalize this understanding.
In this research, a large-scale inexact optimization method was developed for the conjunctive use management of a watershed-lake water distribution system. The modeling framework has the advantages in taking into account the water balance of multi-reservoirs, satisfying the municipal industrial and agricultural water demands in the multi-period context, reflecting the relationship among multi-reservoirs, multiple water related projects, and maintaining the operational rules of certain lake levels. Moreover, such a method can also handle the uncertainty expressed as fuzzy membership functions through integrating the fuzzy credibility chance-constrained programming. The developed method was applied to the conjunctive use management of water resources in the lake Dianchi watershed, China. Cost-effective water allocation schemes for the groundwater project and the water transfer project, and optimal operational rules for the lake and multiple reservoirs were successfully obtained. Also, the annual water balance of the watershed-lake system and the system cost of the conjunctive water use were investigated and analyzed under multiple credibility levels of meeting the water demands for municipal, industrial and agricultural users.
Knowledge of the contribution that individual countries have made to global radiative forcing is important to the implementation of the agreement on "common but differentiated responsibilities" reached by the United Nations Framework Convention on Climate Change. Over the past three decades, China has experienced rapid economic development(1), accompanied by increased emission of greenhouse gases, ozone precursors and aerosols(2,3), but the magnitude of the associated radiative forcing has remained unclear. Here we use a global coupled biogeochemistry-climate model(4,5) and a chemistry and transport model(6) to quantify China's present-day contribution to global radiative forcing due to well-mixed greenhouse gases, short-lived atmospheric climate forcers and land-use-induced regional surface albedo changes. We find that China contributes 10% +/- 4% of the current global radiative forcing. China's relative contribution to the positive (warming) component of global radiative forcing, mainly induced by well-mixed greenhouse gases and black carbon aerosols, is 12% +/- 2%. Its relative contribution to the negative (cooling) component is 15% +/- 6%, dominated by the effect of sulfate and nitrate aerosols. China's strongest contributions are 0.16 +/- 0.02 watts per square metre for CO2 from fossil fuel burning, 0.13 +/- 0.05 watts per square metre for CH4, -0.11 +/- 0.05 watts per square metre for sulfate aerosols, and 0.09 +/- 0.06 watts per square metre for black carbon aerosols. China's eventual goal of improving air quality will result in changes in radiative forcing in the coming years: a reduction of sulfur dioxide emissions would drive a faster future warming, unless offset by larger reductions of radiative forcing from well-mixed greenhouse gases and black carbon.
Plasmonic nanostructures, which are used to generate surface plasmon polaritions (SPPs), always involve sharp corners where the charges can accumulate. This can result in strong localized electromagnetic fields at the metallic corners, forming the hot spots. The influence of the hot spots on the propagating SPPs are investigated theoretically and experimentally in a metallic slit structure. It is found that the electromagnetic fields radiated from the hot spots, termed as the hot spot cylindrical wave (HSCW), can greatly manipulate the SPP launching in the slit structure. The physical mechanism behind the manipulation of the SPP launching with the HSCW is explicated by a semi-analytic model. By using the HSCW, unidirectional SPP launching is experimentally realized in an ultra-small metallic step-slit structure. The HSCW bridges the localized surface plasmons and the propagating surface plasmons in an integrated platform and thus may pave a new route to the design of plasmonic devices and circuits.
Phosphorus (P) is viewed as one limiting factor for phytoplankton growth in freshwater lakes. Simple budget models are very efficient for cross-lakes comparisons, while neglecting key distinction between algal P and other forms. Here, a phosphorus budget model was developed to balance between process resolution and cross-system applicability, in which lake total phosphorus (TP) was divided into algal-bound P and other fractions. The model was tested for six lakes on the Yunnan Plateau, China and the Markov Chain Monte Carlo (MCMC) algorithm of Bayesian hierarchical inference was employed for parameters estimation. The model results showed that (a) both algal species composition and P loading are key factors that influence the efficiency of converting phosphorus into algal P; (b) variability of the settling velocity of non-algal P and algal P decreases with increasing TP concentrations, representing a lower capacity for restoration; and (c) settling velocity declined exponentially with the increase of trophic state index, indicating a potential rapid rise of P removal rates during eutrophication restoration. Two conceptual models were then proposed to identify the prior countermeasures for eutrophication restoration in the lakes: (a) for Conceptual Model II, e.g. Lake Lugu, increasing the physical settling of phosphorus should be given priority to; (b) for Conceptual Model I, including the other five lakes, increasing the biological settling of phosphorus should be paid extra attention. (C) 2016 Elsevier B.V. All rights reserved.
Abstract Phosphorus (P) is viewed as one limiting factor for phytoplankton growth in freshwater lakes. Simple budget models are very efficient for cross-lakes comparisons, while neglecting key distinction between algal P and other forms. Here, a phosphorus budget model was developed to balance between process resolution and cross-system applicability, in which lake total phosphorus (TP) was divided into algal-bound P and other fractions. The model was tested for six lakes on the Yunnan Plateau, China and the Markov Chain Monte Carlo (MCMC) algorithm of Bayesian hierarchical inference was employed for parameters estimation. The model results showed that (a) both algal species composition and P loading are key factors that influence the efficiency of converting phosphorus into algal P; (b) variability of the settling velocity of non-algal P and algal P decreases with increasing TP concentrations, representing a lower capacity for restoration; and (c) settling velocity declined exponentially with the increase of trophic state index, indicating a potential rapid rise of P removal rates during eutrophication restoration. Two conceptual models were then proposed to identify the prior countermeasures for eutrophication restoration in the lakes: (a) for Conceptual Model II, e.g. Lake Lugu, increasing the physical settling of phosphorus should be given priority to; (b) for Conceptual Model I, including the other five lakes, increasing the biological settling of phosphorus should be paid extra attention.
