This paper examines the causal relationships between carbon dioxide emissions, energy consumption and real economic output using panel cointegration and panel vector error correction modeling ...techniques based on the panel data for 28 provinces in China over the period 1995–2007. Our empirical results show that CO2 emissions, energy consumption and economic growth have appeared to be cointegrated. Moreover, there exists bidirectional causality between CO2 emissions and energy consumption, and also between energy consumption and economic growth. It has also been found that energy consumption and economic growth are the long-run causes for CO2 emissions and CO2 emissions and economic growth are the long-run causes for energy consumption. The results indicate that China's CO2 emissions will not decrease in a long period of time and reducing CO2 emissions may handicap China's economic growth to some degree. Some policy implications of the empirical results have finally been proposed.
► We conduct a panel data analysis of the energy–CO2–economy nexus in China. ► CO2 emissions, energy use and economic growth appear to be cointegrated. ► There exists bidirectional causality between energy consumption and economic growth. ► Energy consumption and economic growth are the long-run causes for CO2 emissions.
This paper is concerned with the polynomial filtering problem for a class of nonlinear systems with quantisations and missing measurements. The nonlinear functions are approximated with polynomials ...of a chosen degree and the approximation errors are described as low-order polynomial terms with norm-bounded coefficients. The transmitted outputs are quantised by a logarithmic quantiser and are also subject to randomly missing measurements governed by a Bernoulli distributed sequence taking values on 0 or 1. Dedicated efforts are made to derive an upper bound of the filtering error covariance in the simultaneous presence of the polynomial approximation errors, the quantisations as well as the missing measurements at each time instant. Such an upper bound is then minimised through designing a suitable filter gain by solving a set of matrix equations. The filter design algorithm is recursive and therefore applicable for online computation. An illustrative example is exploited to show the effectiveness of the proposed algorithm.
Improving energy efficiency and productivity is one of the most cost-effective ways for achieving the sustainable development target in China. This paper employs non-radial directional distance ...function approach to empirically investigate energy efficiency and energy productivity by including CO2 emissions as an undesirable output. Three production scenarios, namely energy conservation (EC), energy conservation and emission reduction (ECER), and energy conservation, emission reduction and economic growth (ECEREG), are specified to assess China's energy efficiency and productivity growth during the period of Eleventh Five-Year Plan. Our empirical results show that there exist substantial differences in China's total-factor energy efficiency and productivity under different scenarios. Under the ECEREG scenario, the national average total-factor energy efficiency score was 0.6306 in 2005–2010, while the national average total-factor energy productivity increased by 0.27% annually during the period. The main driving force for energy productivity growth in China was energy technological change rather than energy efficiency change.
•China's regional energy efficiency and productivity in 2005–2010 are evaluated.•Three production scenarios are considered.•Non-radial directional distance function with CO2 emissions is employed.•Technological change is the main driver for China's energy productivity growth.
Global awareness on energy security and climate change has created much interest in assessing economy-wide energy efficiency performance. A number of previous studies have contributed to evaluate ...energy efficiency performance using different analytical techniques among which data envelopment analysis (DEA) has recently received increasing attention. Most of DEA-related energy efficiency studies do not consider undesirable outputs such as CO2 emissions in their modeling framework, which may lead to biased energy efficiency values. Within a joint production framework of desirable and undesirable outputs, in this paper we construct both static and dynamic energy efficiency performance indexes for measuring industrial energy efficiency performance by using several environmental DEA models with CO2 emissions. The dynamic energy efficiency performance indexes have further been decomposed into two contributing components. We finally apply the indexes proposed to assess the industrial energy efficiency performance of different provinces in China over time. Our empirical study shows that the energy efficiency improvement in China's industrial sector was mainly driven by technological improvement.
► China's industrial energy efficiency is evaluated by DEA models with CO2 emissions. ► China's industrial energy efficiency improved by 5.6% annually since 1997. ► Industrial energy efficiency improvement in China was mainly driven by technological improvement.
This paper proposes a parametric frontier approach to estimating economy-wide energy efficiency performance from a production efficiency point of view. It uses the Shephard energy distance function ...to define an energy efficiency index and adopts the stochastic frontier analysis technique to estimate the index. A case study of measuring the economy-wide energy efficiency performance of a sample of OECD countries using the proposed approach is presented. It is found that the proposed parametric frontier approach has higher discriminating power in energy efficiency performance measurement compared to its nonparametric frontier counterparts.
The LAFL (i.e. LEC1, ABI3, FUS3, and LEC2) master transcriptional regulators interact to form different complexes that induce embryo development and maturation, and inhibit seed germination and ...vegetative growth in Arabidopsis. Orthologous genes involved in similar regulatory processes have been described in various angiosperms including important crop species. Consistent with a prominent role of the LAFL regulators in triggering and maintaining embryonic cell fate, their expression appears finely tuned in different tissues during seed development and tightly repressed in vegetative tissues by a surprisingly high number of genetic and epigenetic factors. Partial functional redundancies and intricate feedback regulations of the LAFL have hampered the elucidation of the underpinning molecular mechanisms. Nevertheless, genetic, genomic, cellular, molecular, and biochemical analyses implemented during the last years have greatly improved our knowledge of the LALF network. Here we summarize and discuss recent progress, together with current issues required to gain a comprehensive insight into the network, including the emerging function of LEC1 and possibly LEC2 as pioneer transcription factors.
Coherence distillation is one of the central problems in the resource theory of coherence. In this Letter, we complete the deterministic distillation of quantum coherence for a finite number of ...coherent states under strictly incoherent operations. Specifically, we find the necessary and sufficient condition for the transformation from a mixed coherent state into a pure state via strictly incoherent operations, which recovers a connection between the resource theory of coherence and the algebraic theory of majorization lattice. With the help of this condition, we present the deterministic coherence distillation scheme and derive the maximum number of maximally coherent states obtained via this scheme.
This paper proposes a real options model for evaluating renewable energy investment by considering uncertain factors such as CO2 price, non-renewable energy cost, investment cost and market price of ...electricity. A phase-out mechanism is built into the model to reflect the long-term changes of subsidy policy. We apply the proposed model to empirically evaluate the investment value and optimal timing for solar photovoltaic power generation in China. Our empirical results show that the current investment environment in China may not be able to attract immediate investment, while the development of carbon market helps advance the optimal investment time. A sensitivity analysis is conducted to investigate the dynamics of investment value and optimal timing under the changes of unit generating capacity, subsidy level, market price of electricity, CO2 price and investment cost. It is found that the high investment cost and the volatility of electricity and CO2 prices, are not conducive to attract immediate investment. Instead, increasing the level of subsidy, promoting technological progress and maintaining the stability of market are useful to stimulate investment.
•Propose real option model for evaluating renewable energy investment under uncertainty•Evaluate solar PV power generation in China by considering multiple uncertain factors•Explore the dynamics of value and optimal investment timing by sensitivity analysis
This paper examines the optimal control of CO2 emissions from a perspective of efficiency analysis. Several centralized data envelopment analysis (DEA) models are introduced to study the optimal ...allocation of CO2 emissions under spatial, temporal and spatial–temporal allocation strategies, respectively. The models have been used to determine the optimal paths for controlling CO2 emissions at provincial and regional levels in China. A sensitivity analysis of the optimal path on the emission control coefficient under spatial–temporal allocation strategy is further carried out. Our empirical results show that more developed regions should take emission reduction responsibility earlier than less developed regions in China. Of the three allocation strategies, spatial–temporal allocation strategy seems to be a better choice for achieving the optimal control of CO2 emissions at country level since it is more encompassing by allowing both timing and spatial substitutions. It is also found that there exists an inverted U-shape relationship between the aggregate optimal GDP and the emission control coefficient, which shows that modest emission reduction policy might be more appropriate for China in order to achieve the joint goals of economic development and CO2 emission reduction.
•The optimal control of CO2 emissions in China is examined.•Centralized DEA models are used to allocate CO2 emissions under different strategies.•More developed regions should implement emission reduction earlier.•Modest emission reduction policy could be more appropriate for China.
This paper is concerned with the distributed state estimation problem over wireless sensor networks. The communication links are unreliable that are subject to random link failures modeled as a set ...of independent Bernoulli processes. To estimate the plant state collaboratively, a Kalman-consensus filtering approach is developed where the sensors spread the local information obtained from the Kalman filtering algorithm by performing a consensus of the inverse covariance matrices at each time instant. Sufficient conditions for the stochastic boundedness of the Kalman-consensus filter are established. It is shown that the filtering performance is directly influenced by the network connectivity and the collective observability. A numerical example is illustrated to verify the proposed results.
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