Renewable energy plays an important role in reducing global carbon (CO2) emission. This paper builds a RER (renewable energy consumption rate) index to represent the energy structure of a country and ...proposes a U-shaped RKC (renewable energy Kuznets Curve) hypothesis between RER and economic growth. We also examine the dynamic relationship between RER and the Environmental Kuznets Curve (EKC) hypothesis using two panel data sets of 17 major developing and developed countries as well as six geo-economic regions of the world during 1990–2014. Panel co-integration tests indicate that a long-run relationship exists among economic growth, RER and carbon emission. We employ the fully modified ordinary least squares (FMOLS) and the dynamic ordinary least squares (DOLS) techniques to estimate the co-integration coefficients of the panels and individual countries/regions respectively. The results verify both the EKC and RKC hypotheses, indicating that a 10% rise in RER would to a 1.6% carbon emission reduction. It is also found that the RKC turning points of individual countries and the entire samples in general take place before the turning points of the respective EKCs. It suggests that promoting renewable energy consumption to make RKC cross its turning point earlier can accelerate EKC to reach its turning point more quickly. This finding has important policy implications with respect to the development and utilization of renewable energy and environmental protection.
The dynamic relationship between EKC and RKC. Display omitted
•We examined the relationship between renewable energy and GDP.•A U-shaped curve exists between GDP and renewable energy consumption.•The turning points of RKCs take place earlier than that of the EKCs.•Promoting RKC arrive its turning point in advance can accelerate EKC to reach its turning point more quickly.
Considering the necessity of increasing the renewable energy consumption stated in the European Green Deal (European Commission policy initiatives envisaging European Union (EU) to become climate ...neutral by 2050), the aim of this paper is to validate the so-called Environmental Kuznets curve (EKC) and the revised (or renewable energy) Kuznets curve (RKC) in ten Central and Eastern European (CEE) countries (represented by Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, and Slovenia) in the period from 1990 until 2019. Conditioned by data availability, the impact of governance in these countries on greenhouse gas (GHG) emissions is assessed in the period 2002–2019.
The results based on the panel autoregressive distributed lag (ARDL) models indicated the contribution of renewable energy consumption in reducing pollution and the role of labour productivity in enhancing GHG emissions in the long run. Moreover, our findings demonstrated that domestic credit to private sector reduced pollution in the long run only in the period of 2002–2019. In addition, such factors as the rule of law, regulatory quality and control of corruption were the governance dimensions that contributed to the environmental quality in the long run. The empirical results of our study might be helpful in supporting the environmental and economic policies in the EU countries for achieving their sustainable development and the European Green Deal objectives.
In the context of recent environmental debates related to the impact of economic development on environment quality, this paper's aim is to explain the GHG emissions in few EU New Member States ...(Bulgaria, Slovakia, Slovenia, Czech Republic, Hungary, Romania and Poland) in the period 1990–2019 using a panel data approach (panel threshold and dynamic panel models) and a time series approach (vector error correction models). The importance of this study is related to the identification of paths to reduce pollution in order to manage climate challenges. The results indicate similarities and differences in terms of the impact of various indicators on the total GHG emissions and in the agricultural sector. There is a negative correlation between human development index/GDP and total GHG emissions when GDP growth is below and above 0.83%. Above this threshold estimate, there is a more strong and negative correlation between human development index and GHG emissions than below the threshold value. Below 1.41%, human development index and growth of value-added in agriculture do not influence pollution in agriculture. Above 1.41%, economic growth and change in value-added in agriculture positively influence the pollution in this sector. The relationship between GDP and GHG is inverted N-shaped for Bulgaria, Hungary, Czech Republic, Slovakia, Slovenia and Romania (sample countries), while the relationship between value-added in agriculture and GHG is N-shaped. This research confirms the U-shaped RKC at the national level and for agriculture in the sample countries, while an inversely U pattern was observed for Poland. Renewable energy consumption reduces total GHG emissions in the sample countries. Some policy proposals are indicated to promote a sustainable development in these countries with less pollution.
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This paper deals with the first analysis of the neutron and gamma time series measured with organic scintillators from plutonium samples by using information measures. Fast neutron detection with ...organic scintillators has been widely used for various nuclear safeguards applications and homeland security. One of the significant attributes of special nuclear materials (SNM) is the high multiplicity events in a short period of time. The time distributions of neutron and gamma-rays events for the plutonium metal plates designed as fuel plates for the Idaho National Laboratory (INL) Zero Power were measured with the Fast Neutron Multiplicity Counter (FNMC) consisting of 8 EJ-309 liquid scintillators and 8 stilbene detectors. Since the neutron correlated counts within the coincidence window of 40 ns are related to 240Pu effective mass of plutonium metal plates, it is of interest to investigate the randomness of the measured neutron and gamma-rays events. To access such information, we resort to complexity measures in the hope of being able to connect complexity values with the reliability of detection. That was done through (i) application of Kolmogorov complexity (KC) and its derivatives Kolmogorov spectrum and its highest value (KCM) and running complexity (RKC) and (ii) establishing the “breaking point” after which there exists a sharp drop in the running Kolmogorov complexity of the neutron and gamma-rays time series. It was found that the complexity of all the time series detected from the sample with 5, 9, 11, 13, and 15 plutonium plates had the high almost identical values of KC while the sample with 3 plates had by one-third smaller KC values than all the others. These calculations were supplemented by the Lypaunov exponents for a time series and the National Institute of Standards and Technology (NIST)tests. The low KC values can be addressed to the different sources of uncertainties in measuring procedure with the sample consisting of three plates. The complexity measures applied in this study are capable of revealing aspects of information that would otherwise remain hidden to the one-off complexity estimate.
•Time series from the plutonium samples measured with organic scintillators.•Time series investigated by application of Kolmogorov complexity and its derivates.•Establishing the “breaking point” in the running Kolmogorov complexity.•Time series measured either by 8 or 16 detectors show nearly the same randomness.•Scintillators reliably measured the neutron and gamma events on a nanosecond scale.
In this work, we aim at constructing numerical schemes, that are as efficient as possible in terms of cost and conservation of invariants, for the Vlasov–Fokker–Planck system coupled with Poisson or ...Ampère equation. Splitting methods are used where the linear terms in space are treated by spectral or semi-Lagrangian methods and the nonlinear diffusion in velocity in the collision operator is treated using a stabilized Runge–Kutta–Chebyshev (RKC) integrator, a powerful alternative of implicit schemes. The new schemes are shown to exactly preserve mass and momentum. The conservation of total energy is obtained using a suitable approximation of the electric field. An H-theorem is proved in the semi-discrete case, while the entropy decay is illustrated numerically for the fully discretized problem. Numerical experiments that include investigation of Landau damping phenomenon and bump-on-tail instability are performed to illustrate the efficiency of the new schemes.
•New stabilized Runge-Kutta methods for Vlasov-Fokker-Planck equation.•New second and fourth order discretizations of the Fokker-Planck operator.•Exact conservation of mass, momentum, and energy.•Proof of an H-theorem for the semi-discrete problem.
This study aims to measure the association of real economic growth per capita, renewable energy consumption, and financial development with ecological footprints (EFP) across the 155 countries of ...four different income groups over the period of 1990–2017. For the analysis, the unit root tests allowing cross-sectional dependency, Westerlund cointegration test, common correlated effect of mean group, augmented mean group, mean group, and Dumitrescu–Hurlin panel causality test are used. The results verify both the environmental Kuznets curve (EKC) and renewable energy environment Kuznets curve (RKC) hypotheses in the high-income group; however, other groups have not shown reliable results. Moreover, it is observed that the existence of RKC is a turning point for high-income countries, and it takes place before the turning point of the forthcoming EKC. Besides, empirical outcomes endorse the presence of long-run equilibrium and indicate that financial development has a negative and significant effect on the EFP in the case of the high-income group. In contrast, upper–middle– and lower–middle–income groups show the insignificant relationship with the dependent variable. Likewise, financial development has a positive and significant association with EFP for the low-income group. Conversely, biomass energy has a negative relationship with EFP in high- and lower–middle–income groups, while a positive association has been observed for the remaining two groups. We suppose that the study outcomes would guide the policymakers in decision-making regarding the development and usage of renewable energy to prevent environmental damages.
Considering the necessity of achieving economic development by keeping the quality of the environment, the aim of this paper is to study the impact of economic growth on GHG emissions in a sample of ...Central and Eastern European (CEE) countries (V4 countries, Bulgaria and Romania) in the period of 1996–2019. In the context of dynamic ARDL panel and environmental Kuznets curve (EKC), the relationship between GHG and GDP is N-shaped. A U-shaped relationship was obtained in the renewable Kuznets curve (RKC). Energy consumption, domestic credit to the private sector, and labor productivity contribute to pollution, while renewable energy consumption reduces the GHG emissions. However, more efforts are required for promoting renewable energy in the analyzed countries.
The complex transverse water proton magnetization subject to diffusion-encoding magnetic field gradient pulses in a heterogeneous medium can be modeled by the multiple compartment Bloch–Torrey ...partial differential equation (PDE). In addition, steady-state Laplace PDEs can be formulated to produce the homogenized diffusion tensor that describes the diffusion characteristics of the medium in the long time limit. In spatial domains that model biological tissues at the cellular level, these two types of PDEs have to be completed with permeability conditions on the cellular interfaces. To solve these PDEs, we implemented a finite elements method that allows jumps in the solution at the cell interfaces by using double nodes. Using a transformation of the Bloch–Torrey PDE we reduced oscillations in the searched-for solution and simplified the implementation of the boundary conditions. The spatial discretization was then coupled to the adaptive explicit Runge–Kutta–Chebyshev time-stepping method. Our proposed method is second order accurate in space and second order accurate in time. We implemented this method on the FEniCS C++ platform and show time and spatial convergence results. Finally, this method is applied to study some relevant questions in diffusion MRI.
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