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In terms of cataloged debris produced, the anti-satellite test carried out by Russia, in November 2021, at an altitude of about 480 km, leading to the destruction of the old satellite Cosmos 1408, was the second worst to date and represented the third worst fragmentation in orbit. It generated more than 1/4 of the cataloged debris produced over 55 years by all such tests and almost twice as many as were produced by all previous Soviet tests. After placing this event in its historical context, this paper analyzes in detail how the evolution of the Cosmos 1408 debris cloud affected the environment below 600 km in the first seven months, focusing on the two operational space stations and the Starlink large constellation of satellites. During the first six months following the test, the Cosmos 1408 cloud of fragments nearly doubled the average flux of cataloged objects on the International Space Station and increased by about 3/4 that on China's Tiangong. In the same period, the Starlink large constellation saw an average increase in the flux of cataloged objects of about 20%. Some orbital planes, the "counter-rotating" ones with respect to the Cosmos 1408 debris cloud, were more affected than others, and the affected planes gradually changed over time, due to the differential precession of cloud and constellation nodes. However, being the Starlink constellation 70 km higher up, the flux of Cosmos 1408 cataloged debris steadily decreased over the period analyzed, due to the cloud orbital decay, reducing to just over a quarter of its extrapolated initial value after seven months. • A review of ASAT tests as a source of orbital debris was presented. • The impact of the Cosmos 1408 destruction was put into context. • The cataloged debris flux increase on space stations was computed and discussed. • The debris flux increase and evolution on Starlink orbit planes was analyzed. • A moratorium on this type of ASAT tests was recommended, including low LEO. [ABSTRACT FROM AUTHOR]

The first-order grey model is appropriate for monotonic time series, while the grey Verhulst model is appropriate for periodic time series. The grey Verhulst model is widely used for predicting practical nonlinear time series that contain fluctuations. Despite the successful application of the grey models in practice, researchers show that grey models still have room for improvement. Moreover, recent research shows that grey models are sensitive to initial conditions. In many practical problems, the value of initial conditions is not accurate and suffers from noise or approximation errors, resulting in inaccurate prediction. To address these difficulties, an improved grey Verhulst method using particle swarm optimization is proposed in this paper. The proposed model consists of two stages. In the first stage, a second-order polynomial with unknown coefficients is used to approximate the 1- AGO. In the second stage, the initial element of the time series is modified to improve the accuracy of the prediction. The particle swarm optimization method is used to search for the unknown coefficients. It is found that PSO is a suitable optimization method for the proposed method because it is stable and generates a sequence of points that converges to a globally optimal solution. To demonstrate the efficiency and stability of the proposed method, it was applied to five practical problems, namely, gas production in China, the number of hazardous chemical accidents, CO2 emissions in Russia, the number of domestic tourists in China, and traffic flows in Canada. Numerical results show that the method is more accurate and robust than existing methods. • The proposed method needs only four elements for predicting the future elements of time series. • The paper proposes a second order polynomial for approximating 1-AGO. • The method makes more accurate prediction than existed methods. • The proposed method is applied on various practical forecasting problems successfully. [ABSTRACT FROM AUTHOR]

Meeting energy needs and ensuring ecological sustainability are important tasks for policymakers. In particular, changing the energy mix used in daily electricity generation can have a major effect on ecological conditions, and this is a previously neglected research topic. Therefore, this paper aims to investigate the influence of daily electricity generation from nuclear power and renewables on the achievement of carbon neutrality targets in the four largest nuclear power countries (i.e., the U.S., China, France, and Russia). The study applies the wavelet-transform coherence (WTC), quantile-on-quantile regression (QQR), and Granger causality in quantiles (GCQ) approaches for the period from January 2, 2019 to December 29, 2022. The outcomes present that electricity generation from nuclear energy reduces carbon (CO 2) emissions only in Russia, while hydropower generation does not contribute to CO 2 emission reduction in any country. Solar electricity generation decreases CO 2 emissions in different quantiles in the U.S. and Russia, while electricity generation from wind power reduces CO 2 emissions in the U.S. and France. The empirical outcomes also reveal that expanding solar, wind, and nuclear power in the energy mix can enhance the potential of the U.S., France, and Russia to achieve carbon neutrality and secure a sustainable future. However, China is using nuclear and renewables inefficiently regarding carbon neutrality. Therefore, the empirical evidence for China is highly controversial compared to former studies. [Display omitted] • The study examines renewable and nuclear electricity effect on carbon neutrality. • The study focuses on top four major nuclear power countries. • The study applies nonlinear approaches by using high-frequency (daily) data. • Renewable and nuclear electricity have time, frequency, & quantile-varying effect. • The best electricity source change according to each country. [ABSTRACT FROM AUTHOR]

Abstract The Belt and Road Initiative (BRI) forms the core of China's foreign policy and future foreign cooperation, and energy cooperation is an important component of the BRI. Energy security is closely related to the interdependent relations between countries. The present paper investigates energy interdependent relations between China and the countries along the Belt and Road using data collected in the BP Statistical Review of World Energy , between 2000 and 2015. The main results are as follows: (1) Abundant proven reserves of energy resources exist in these countries, which were equivalent to 758.73 billion tons of standard coal in 2015, accounting for 52.27% of the world. The distribution of these resources presents a pattern with two centers—one in Russia, and one in West Asia and the Middle East. (2) Established interdependence relations exist between China and the countries along the Belt and Road in terms of energy cooperation. China has imported 437.21 million tons of standard coal from these countries and their guarantee degree to China's energy security is 58.42%, of which 13.56% refers to coal, 73.37% to oil, and 13.06% to gas. Meanwhile, their dependence degree in energy exports to China was 13.56%, or 11.15% for coal, 14.92% for oil, and 10.55% for gas. An interdependence relation thus exists between China and these countries, and the degree of mutual dependence between them was 0.23 (0.22 for coal, 0.13 for oil, and 0.38 for gas), locating China in a relatively passive position with respect to the countries along the Belt and Road as a whole, but a relatively active position in relation to individual countries (with the exception of Russia). Our findings are useful to the tasks of identifying the spatial distribution pattern of energy in countries along the Belt and Road, assisting in the promotion of energy cooperation between China and these countries, and the future construction of the BRI. Highlights • Energy cooperation relationships between China and the countries along the Belt and Road are examined. • The indicators of guarantee degree, dependence degree, and mutual dependence degree are selected for this study. • Energy resources present a pattern with two centers; one in Russia and one in West Asia and the Middle East. • Countries along the Belt and Road maintained an energy GD of 58.42% for China; their DD on China was 13.56%. • The MDD between China and the countries of the Belt and Road was 0.23, and China's position in the relation was passive. [ABSTRACT FROM AUTHOR]

Abstract The uncertainties in gas demand levels and geopolitical issues may lead to significant changes in global gas trade. This paper uses an agent-based model to simulate the alternative market futures under two demand trajectories: a baseline following current policy pledges until 2060 and another where demand shifts to a lower level in 2030. Endogenously generated capacity investments are driven by long-term bilateral contracts between importers and exporters, where investors are assumed to evaluate the potential risks of demand changes while making their decisions. The results suggest that, when the demand decreases in 2030, the Middle East takes the dominant position in Eastern Asia, whereas this role is occupied by North America in the current policy scenario. In addition, the impacts of a 25% tariff by China on U.S. natural gas are studied for both scenarios. The revenue of North American gas trade is only marginally affected by this tariff. Under the normal demand trajectory, the tariff influences the Chinese market more notably in the longer term when global supply is tightened by decommissioning. In the case of lower global gas demand, the market share of Russia in Western Europe could be threatened by increasing North American export there. Highlights • A global gas model considering investment under demand uncertainty is presented. • The trade and revenue impact of low gas demand and a China-US gas trade tariff are studied. • The tariff may increase the Chinese gas import price more notably after 2045. • North America is not affected significantly due to sales to East Asia and Europe. • Russia is negatively affected by increasing competition with North America on gas. [ABSTRACT FROM AUTHOR]

In-situ monitoring system is absolutely necessary for a long-distance linear pipeline infrastructure in permafrost regions due to the complicated interaction between buried pipeline and its harsh permafrost environment. To study this complex problem, a comprehensive in-situ monitoring system has been designed and established along the China–Russia Crude Oil Pipeline (CRCOP), which is one of vital energy channels for importing crude oil from Russia to China. This monitoring system can record the meteorological data, ground temperature and water content within the permafrost foundation, vertical settlement of the oil pipe, ground surface deformation on the pipeline right-of-way (on-ROW), as well as the thaw bulb around the pipeline at four sites with different engineering geological conditions. In this paper, the layout and instrumentation of the whole monitoring system and monitoring methods are described in detail, and then the thermal regime of permafrost on-ROW and off-ROW and cooling performance of the mitigative measures on foundation soils are evaluated. Results show that heat dissipated from the CRCOP lead to the rapid degradation of permafrost on-ROW and produce different sizes of thaw bulb around the oil pipelines. The mitigative measures, including insulation layer, two-phase closed thermosyphon and U-shaped air-ventilated pipes, are effective to minimize permafrost degradation and ensure the thermal stability of permafrost foundation along the CRCOP. Some recommendations are proposed for future research and for the monitoring system to be improved. This monitoring system can provide multi-field data to clarify the interaction between pipeline and permafrost degradation under different geological conditions, and guide the design and maintenance of the buried warm pipeline in permafrost regions. • An in-situ monitoring system is set up along the CRCOP in permafrost regions. • The geological characteristics and layout of instrumentation at four monitoring sites are reported. • The integrated monitoring method for pipeline-permafrost interaction are presented. • Thermal effect of buried warm oil pipe on underlying permafrost is observed. • Cooling performance of the insulation layer, thermosyphon and U-shaped air-ventilated pipes is evaluated. [ABSTRACT FROM AUTHOR]

The accurate and reasonable prediction of natural gas consumption is important for enhancing national energy security and alleviating the environmental problems caused by energy consumption. Starting with the traditional nonlinear grey Bernoulli model, in this paper, we expand the development coefficient a and grey action quantity b, propose a new self-adaptive time-varying grey Bernoulli prediction model, deduce the time response formula of the model, and explore the relationship between model parameters and model accuracy. Then, the nonlinear parameter and power parameter coefficient of the new model are optimized by a genetic algorithm, and the effectiveness of the model is analyzed by the natural gas consumption of China, the United States, and Russia. The results show that, compared with other traditional grey prediction models, the new model has a better simulation effect, higher prediction accuracy, and stronger applicability. Meanwhile, the model was used to forecast the natural gas consumption of China, the United States, and Russia in the period from 2022 to 2026. The prediction results show that China's natural gas consumption will continue to steadily increase in the future, which is consistent with the global goal of adhering to the orderly development of natural gas. The prediction results can provide a theoretical basis for relevant departments to formulate relevant natural gas policies. [ABSTRACT FROM AUTHOR]

Rapid permafrost thawing triggered by heat release from the buried warm-oil pipeline would result in the instability of the pipeline, posing a potential risk of an oil spill in permafrost regions. Therefore, how to precisely control the ground temperature to mitigate pipeline foundation permafrost from thawing is of significant importance. Thermosyphon is a widely-accepted and extensively-used countermeasure against permafrost thawing in permafrost engineering. This paper presents 3-year (2015–2018) monitored data of ground temperature and geophysical survey results conducted by electrical resistivity tomography in April 2018, to investigate the thermal stabilizing effect of thermosyphons installed nearby the China-Russia crude oil pipeline (CRCOP) and the influencing factors. Furthermore, numerical simulation tests were conducted to evaluate their long-term cooling applicability and to optimize their layout parameters. Field observations show that the thermosyphons can cool down and even freeze the thawed soil layers around the CRCOP, prohibiting the infiltration of water into the thawing front to some extent and effectively mitigating the rapid thawing of permafrost beneath the pipeline. The performance of the thermosyphons is greatly influenced by the method and time of thermosyphon installation, as well as layout parameters including the number and longitudinal spacing. Two pairs of thermosyphons with a shorter spacing are unable to control the thawing of the underlying permafrost due to the non-anticipated higher oil temperature, the thermal erosion of water ponding, and climate warming. The simulated results indicate that thermosyphons perform well in the first 5 years after installation. Thermosyphon lowers the mean annual temperature of soils surrounding it by about 2 and 1.4 times when the evaporator section length is increased by 50% and the longitudinal spacing is decreased by 0.5 m, respectively. The application of thermosyphons has proven its strength for thermally stabilizing the pipeline foundation permafrost along the CRCOP. • 3-year ground temperature data and geophysical survey results are presented. • Thermosyphon can mitigate the rapid thawing of permafrost beneath the pipeline. • Thermosyphons performs most significantly in the first five years. • Lengthening thermosyphon and decreasing spacings are favorable for the better cooling effect. [ABSTRACT FROM AUTHOR]

• We consider some indicators that have not been considered in previous studies, such as the impact of historical and social factors, which are very important and necessary in measuring national space exploration capabilities. • We introduce a more reasonable quantity (Equity Evaluation Index) to measure global equity, which is more objective for both stronger and weaker countries in space exploration. • The optimization model takes different aspects of the space industry into consideration (e.g., funding, technology, scientific research), providing suggestions for countries at different developing levels to take advantage of its strengths and cover its weaknesses. In this paper we introduce an equity evaluation index (EEI) to measure the global equity on asteroid mining, and present a global equity evaluation model by applying the analytic hierarchy process (AHP), entropy weight method and the technique for order preference by similarity to ideal solution (TOPSIS). Based on multi-objective optimization, we provide a global cooperative decision model to allocate the inputs and outputs among countries based on their strengths and demands. Furthermore, we analyze the the trends of EEI of each country under the influence of the outbreak events by using the autoregressive integrated moving average model. Our results show that among all countries with foundations in aerospace, China has the highest EEI while Russia ranks the lowest. Humans mining minerals in a cooperative manner will achieve a win-win situation. [ABSTRACT FROM AUTHOR]

In permafrost regions, the soil settlement disaster owing to permafrost degradation has become one of the important reasons for buried warm-oil pipelines failure. In this paper, the 3D sequential thermo-mechanical coupled model is carried out to investigate the interaction between buried warm-oil pipeline and surrounding permafrost. The effects of parameters, including thaw-settlement coefficient, length of transition zone, diameter-thickness ratio and internal pressure, on the pipeline mechanical behavior are numerically investigated. Among them, the thaw-settlement coefficient and length of transition zone present more significant effects on the peak strain of the pipeline. In addition, the effects of insulation layer and two-phase closed thermosyphon (TPCT) on pipeline–soil interaction are investigated in thermal and mechanical fields. With no protective measure, the permafrost layer under pipeline will completely degrade in about 20 years with 0.33m/a. The pipeline is considered to reach failure limitation even within 10 years. However, under the influence of combined measure, the permafrost degradation rate is only about 1/10 of that without protective measure. The peak compressive strain is significantly lower than the critical compressive strain, and the pipeline remains safe for 50 years. Therefore, the combined measure is an ideal method for ensuring pipeline safety in permafrost regions. • Permafrost layer is well protected by the combined measure. • The TSC and the LTZ show significant effects on the peak strain of pipeline. • Pipeline remains safe for 50 years under the influence of combined measure. [ABSTRACT FROM AUTHOR]

This paper takes both value-added trade and trade-implied CO 2 emission reduction responsibility into account, which constructs a unified conceptual framework to recalculate CO 2 emission reduction responsibility from the perspective of value-added trade. This allows policymakers to trace worldwide CO 2 emissions at multiple levels of trade, production, consumption, and shared principle alongside the world trade network. This paper employs the gross export decomposition methodology and the World Input-Output Database for calculations. Firstly, compared with traditional trade statistics, measuring embedded emissions in value-added trade can deduct the double-counted terms of CO 2 emissions due to intermediate products crossing several borders repeatedly. Secondly, the worldwide inter-country CO 2 emission footprints embedded in exports, imports, and net flows of value-added trade are traced in a geographical world map. It occurs that, China, the USA, Russia, and the EU are the top four largest emitters. Thirdly, network analysis is further utilized to capture bilateral implicit CO 2 emission relationships, e.g., the EU members' environmental impacts depend on intra-regional trade within the union. Finally, a comparison is made under three burden-sharing principles based on value-added trade. The shared responsibility offers a compromise between the producer's and the consumer's principle, which is considered to be fairer and more effective. • This paper calculates trade-implied CO 2 emission reduction responsibility from the perspective of value-added trade. • A gross export decomposition model is applied to deduct double-counted terms of implicit carbon embedded in traditional trade. • The worldwide inter-country CO 2 emission footprints are visualized. • Network analysis is conducted to identify the major carbon emitters and their complex relations. • Three burden-sharing criteria are computed through the statistics of value-added trade. [ABSTRACT FROM AUTHOR]

Testing ecological models involves using independent data on model performance, which can be difficult or practically impossible to obtain. Individual based models of forest dynamics, or gap models, simulate the change of forests by computing the annual growth, birth and death of each tree at a location in a forest. The models are relatively simple and simulate results that can be translated to multiple response scales: Individual plant growth, population birth-death processes, stand environmental dynamics ( e.g ., evapotranspiration, element cycling, heat flux, etc .), landscape processes, and regional and global change. This paper reviews some of the approaches applied to testing gap models. Then, it demonstrates the testing of the performance of an individual-based gap model of forest dynamics, FAREAST, through comparison against independent data from China and across Russia. As part of this model testing, biomass simulation output for 93 locations is compared to independent field-collected inventory-data from 44 Russian forests, which span a broad range of forest types across Russia. FAREAST captures biomass dynamics and stabilization at specific locations bracketing the measured values. At Changbai Mountain, the model accurately predicts the community dynamics of complex mixed forest types present along an elevational gradient, as well as the broad regional compositional patterns across China and Russia. Validation of regional detailed landscape dynamics shows the model performs with fidelity with an average R2 value of 0.74 for 87 comparisons and an average root mean square error of 10.8 tC ha −1. Performance of the model for historical conditions implies the model's applicability across a broad region and suggests the usefulness of a detailed model for evaluating forest change to management and changing climate. [ABSTRACT FROM AUTHOR]

As the industrial structure adjusts and driving effects change in different countries, the regional pattern of industrial driving effects is reshaped, and the new pattern is bound to lead to changes in energy consumption. Therefore, this paper uses multiregional input-output analysis, complex network theory, and panel quantile regression model to explore the impact of the topological structure of the global industrial driving network on energy intensity. The empirical results show that China's ability to drive economic activity is becoming stronger, but its level of dependence is also increasing. The industrial dependence of Russia is also relatively high, but over time it has been gradually decreasing. Countries with high energy intensity should reduce their role in driving others and rely less on external resources. For countries with low energy intensity, they could conduct trade cooperation with more countries, but the driving effect strength with other countries cannot be too high. Understanding the relationship between industrial driving effects and energy intensity is of great significance for the government in the implementation of trade policies and industry policies, which have a large impact on energy intensity. • The relationship between industrial driving effect and energy intensity is studied. • Panel quantile regression is adopted in the analysis. • The industrial driving effects of various countries are changing over time. • The roles played by countries have different impacts on energy intensity. • Industrial driving effect should be considered for trade policies. [ABSTRACT FROM AUTHOR]

This paper analyzes the competitiveness and bilateral trade complementarities of BRICS countries (i.e., Brazil, Russia, India, China, and South Africa) with respect to their fossil energy trade and explores the reasons for changes in fossil energy complementarities. By introducing the logarithmic mean divisia index (LMDI) method, this study links the revealed comparative advantage (RCA) index with the trade complementarity index (TCI), attributing the change in complementarities to export and import revealed comparative advantages associated with both sides. The results show that, in the coal trade among BRICS countries, China's competitiveness is declining annually while Russia shows an opposite trend. The cooperation between China and Russia has steadily expanded in the crude oil trade. Although India and Russia are highly complementary in the crude oil trade, its drivers are not stable. Finally, in the natural gas trade among BRICS countries, Russia always has a stable and outstanding supply capacity. • Relationships in fossil energy trade among BRICS countries were examined. • Relative competitiveness and complementarity in trade were focused upon. • Changes of trade potential were attributed to competitiveness of both sides. • China and Russia play opposite roles in the coal trade among BRICS. • India and Russia have not formed a long-term, stable, cooperative relationship. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of oil supply and demand shocks on the current account balances of China and Russia for the period between the first quarter of 1993 and the third quarter of 2018 using a time-varying parameter vector autoregression (TVP-VAR) model with stochastic volatility. To facilitate comprehension of the results and to anchor them in well-known events, this analysis focuses on two countries with different oil trade characteristics—Russia as an oil exporter and China as an oil importer. We find that identifying their sources plays an important role in understanding the impact of oil price shocks on trade balances. The results indicate that oil demand shocks have a much larger effect on trade balances and are more attributable to oil price shocks than oil supply shocks. Due to their different positions in the global oil market—one an oil exporter and the other, an oil importer—China's and Russia's individual responses differ substantially. In line with findings regarding impulse responses, the time-varying forecast error decompositions demonstrate that both oil supply and demand shocks have their greatest influence during and immediately after periods of crisis. • The effects of oil shocks on the current accounts of China and Russia is investigated. • Time-varying parameter vector autoregression model (TVP-VAR) with sign restrictions is employed. • The oil demand shocks have a positive effects on the trade balances of Russia but negative on those of China. • The oil supply and demand shocks are found to have their maximum effects during and immediately after crisis periods. [ABSTRACT FROM AUTHOR]