Satellite mapping reveals extensive industrial activity at sea.

The world's population increasingly relies on the ocean for food, energy production and global trade1-3, yet human activities at sea are not well quantified4,5. We combine satellite imagery, vessel GPS data and deep-learning models to map industrial vessel activities and offshore energy infrastructure across the world's coastal waters from 2017 to 2021. We find that 72-76% of the world's industrial fishing vessels are not publicly tracked, with much of that fishing taking place around South Asia, Southeast Asia and Africa. We also find that 21-30% of transport and energy vessel activity is missing from public tracking systems. Globally, fishing decreased by 12 ± 1% at the onset of the COVID-19 pandemic in 2020 and had not recovered to pre-pandemic levels by 2021. By contrast, transport and energy vessel activities were relatively unaffected during the same period. Offshore wind is growing rapidly, with most wind turbines confined to small areas of the ocean but surpassing the number of oil structures in 2021. Our map of ocean industrialization reveals changes in some of the most extensive and economically important human activities at sea.

The Energy Potential of Harvested Wood Fuel by Refugees in Northern Uganda.

For the last three decades, Uganda has lost considerable natural vegetation cover in the refugee settlements and buffer zones due to the high demand for wood fuel and timber. It is worthy to note that the supplies of wood fuel are more likely to dwindle in the near future. This study explored the determinants of harvested wood-fuel choices and their energy potential. It also examined the implemented energy conservation measures and constraints faced by the refugees both in Palorinya and Imvepi refugee settlements in Northern Uganda. The data were collected by conducting household interviews and collection of wood species samples for energy potential laboratory analysis. Findings indicate that the major sources of wood fuel were firewood, charcoal, briquettes, and biomass fuels. The major refugee choices that determined wood-fuel collection included the family size of the house hold, culture, method of cooking, type of food cooked, high poverty levels, and availability of family labour (P ≤ 0.05). The sampled wood tree species had the highest energy potential were Celtis durandii (5,837 kcal/kg), Parkinsonia aculeata (5,771 kcal/kg), Delonix regia (5,153 kcal/kg), and Bligihia unijugata (5,034 kcal/kg). Access to wood fuel by the households was mainly constrained by limited household income levels, long distances trekked, and inadequate awareness about wood fuel sources and availability. To conserve wood fuel, the refugees deploy several measures including the use of mobile solar gadgets for cooking and lighting, taking up agroforestry, use of briquettes, adoption of energy-saving cooking stoves, and establishment of new woodlots. Therefore, to reverse this trend, the Ugandan government and development partners should prioritise energy investments by supporting cheaper energy alternatives such as mobile solar gadgets and energy-saving cooking technologies, and establishment of woodlots.

Estimating a social cost of carbon for global energy consumption.

Estimates of global economic damage caused by carbon dioxide (CO2) emissions can inform climate policy1-3. The social cost of carbon (SCC) quantifies these damages by characterizing how additional CO2 emissions today impact future economic outcomes through altering the climate4-6. Previous estimates have suggested that large, warming-driven increases in energy expenditures could dominate the SCC7,8, but they rely on models9-11 that are spatially coarse and not tightly linked to data2,3,6,7,12,13. Here we show that the release of one ton of CO2 today is projected to reduce total future energy expenditures, with most estimates valued between -US$3 and -US$1, depending on discount rates. Our results are based on an architecture that integrates global data, econometrics and climate science to estimate local damages worldwide. Notably, we project that emerging economies in the tropics will dramatically increase electricity consumption owing to warming, which requires critical infrastructure planning. However, heating reductions in colder countries offset this increase globally. We estimate that 2099 annual global electricity consumption increases by about 4.5 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in global mean surface temperature (GMST), whereas direct consumption of other fuels declines by about 11.3 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in GMST. Our finding of net savings contradicts previous research7,8, because global data indicate that many populations will remain too poor for most of the twenty-first century to substantially increase energy consumption in response to warming. Importantly, damage estimates would differ if poorer populations were given greater weight14.

Greenhouse gas emissions intensity of food production systems and its determinants.

It is estimated that about 1/4th of all greenhouse gas (GHG) emissions may be caused by the global food system. Reducing the GHG emissions from food production is a major challenge in the context of the projected growth of the world's population, which is increasing demand for food. In this context, the goal should be to achieve the lowest possible emission intensity of the food production system, understood as the amount of GHG emissions per unit of output. The study aimed to calculate the emission intensity of food production systems and to specify its determinants based on a panel regression model for 14 countries, which accounted for more than 65% of food production in the world between 2000 and 2014. In this article, emission intensity is defined as the amount of GHG emissions per value of global output. Research on the determinants of GHG emissions related to food production is well documented in the literature; however, there is a lack of research on the determinants of the emission intensity ratio for food production. Hence, the original contribution of this paper is the analysis of the determinants of GHG emissions intensity of food production systems. The study found the decreased of emission intensity from an average of more than 0.68 kg of CO2 equivalent per USD 1 worth of food production global output in 2000 to less than 0.46 in 2014. The determinants of emission intensity decrease included the yield of cereals, the use of nitrogen fertilizers, the agriculture material intensity, the Human Development Index, and the share of fossil fuel energy consumption in total energy use. The determinants of growth of emission intensity of food production systems included GDP per capita, population density, nitrogen fertilizer production, utilized agriculture area, share of animal production, and energy use per capita.

Beta decoupling relationship between CO2 emissions by GDP, energy consumption, electricity production, value-added industries, and population in China.

The credible sources of fossil energy efficiently are a vital cause of economic growth and considerable influence on adequate security. Whereas radiant energy positively enhances or ostensibly promotes socio-economic stability and the controlled environment. The fossil energy sources supply has become progressively stern in China and reconnoitering the beta decoupling relationships between CO2 emissions, GDP, energy consumption, electricity consumption, value-added industries, and population. The results will be favorable for illustrative the security of the valuable resources. This study adopts the extended stochastic model (STIRPAT) with Beta Decoupling Techniques (BDT). This modern technique merely employs the decoupling situation by the alpha and beta effects from 1989 to 2018 and calculates the % change in CO2 emissions by GDP growth and energy consumption. The estimated results represent negative and economic growth depends on coal and natural gas. First, CO2 emissions annually increasing cause of rapid growth, energy consumption, and electricity production, and the structural contradiction of energy remained static. Second, the Value-added industries estimated that CO2 emissions reduce by primary industries. Third, the decoupling states of CO2 emissions and population show an inverse relationship. This paper tentatively suggests China is sustainable, naturally strengthens energy output, transmutes the energy consumption structure, and advances development policies under environmental circumstances.

Past world economic production constrains current energy demands: Persistent scaling with implications for economic growth and climate change mitigation.

Climate change has become intertwined with the global economy. Here, we describe the contribution of inertia to future trends. Drawing from thermodynamic principles, and using 38 years of available statistics between 1980 to 2017, we find a constant scaling between current rates of world primary energy consumption [Formula: see text] and the historical time integral W of past world inflation-adjusted economic production Y, or [Formula: see text]. In each year, over a period during which both [Formula: see text] and W more than doubled, the ratio of the two remained nearly unchanged, that is [Formula: see text] Gigawatts per trillion 2010 US dollars. What this near constant implies is that current growth trends in energy consumption, population, and standard of living, perhaps counterintuitively, are determined by past innovations that have improved the economic production efficiency, or enabled use of less energy to transform raw materials into the makeup of civilization. Current observed growth rates agree well with predictions derived from available historical data. Future efforts to stabilize carbon dioxide emissions are likely also to be constrained by the contributions of past innovation to growth. Assuming no further efficiency gains, options look limited to rapid decarbonization of energy consumption through sustained implementation of at least one Gigawatt of renewable or nuclear power capacity per day. Alternatively, with continued reliance on fossil fuels, civilization could shift to a steady-state economy, one that devotes economic production exclusively to maintining ongoing metabolic needs rather than to material expansion. Even if such actions could be achieved immediately, energy consumption would continue at its current level, and atmospheric carbon dioxide concentrations would only begin to balance natural sinks at concentrations exceeding 500 ppmv.

Consumption substitution and change of household indirect energy consumption in China between 1997 and 2012.

With the rapid growth in the Chinese economy in recent decades, household incomes as well as consumption of goods and services have also steadily increased. This has resulted in growing demand for energy consumption across the economy. It has been suggested that consumption upgrades in tandem with substitutions might exert an impact on mitigating this growth. The input-output method was applied in this study to analyze variations in household indirect energy consumption between 1997 and 2012. The impact of consumption substitution on change was also determined using a two-tier structural decomposition analysis, in which the second-tier is a further decomposition based on first-tier results. The results show that the indirect energy use caused by household consumption makes up between 75% and 78% of total household energy demand and that this increased 161.2% over the study period. First-tier decomposition results reveal that this change was mostly caused by household consumption scale and energy intensity effects. Second-tier decomposition results reveal strong evidence for consumption substitution between energy-intensive industries and non-energy-intensive ones and that this can have an impact on reducing household indirect consumption. Household consumption therefore plays a prominent role in total energy consumption. Transforming to non-energy-intensive or services led consumption patterns should therefore be encouraged by the Chinese government in order to achieve conservation goals.

A preliminary assessment of the impact of COVID-19 on environment - A case study of China.

The coronavirus disease (COVID-19) is seriously threatening world public health security. Currently, >200 countries and regions have been affected by the epidemic, with the number of infections and deaths still increasing. As an extreme event, the outbreak of COVID-19 has greatly damaged the global economic growth and caused a certain impact on the environment. This paper takes China as a case study, comprehensively evaluating the dynamic impact of COVID-19 on the environment. The analysis results indicate that the outbreak of COVID-19 improves China's air quality in the short term and significantly contributes to global carbon emission reduction. However, in the long run, there is no evidence that this improvement will continue. When China completely lifts the lockdown and resumes large-scale industrial production, its energy use and greenhouse gas (GHG) emissions are likely to exceed the level before the event. Moreover, COVID-19 significantly reduces the concentration of nitrogen dioxide (NO2) in the atmosphere. The decline initially occurred near Wuhan and eventually spread to the whole country. The above phenomenon shows that the decreasing economic activities and traffic restrictions directly lead to the changes of China's energy consumption and further prevent the environment from pollution. The results in this study support the fact that strict quarantine measures can not only protect the public from COVID-19, but also exert a positive impact on the environment. These findings can provide a reference for other countries to assess the influence of COVID-19 on the environment.

The impact of climate change on residential energy consumption in urban and rural divided southern and northern China.

In different regions of China, climate change has various influences on urban and rural residential energy consumption, which also shows that the research on it could be profoundly vital in order to formulate the energy-saving and emission-reducing policies. Based the provincial panel data from 2000-2016, the extended stochastic impacts by regression on population, affluence, and technology (extended STIRPAT) model was utilized to evaluate the impacts of climate change on residential energy consumption in different Chinese regions. The results show that: (1) during 2000 to 2016, the urban and rural energy consumption enlarged by 878.83 billion kWh and 488.98 billion kWh, respectively. In addition, electricity and oil have occupied more proportion in urban energy consumption, while coal still plays an important role in rural residential energy consumption (28.2%). (2) Heating degree day (HDD) and cooling degree day (CDD) have positive influences on urban and rural residential energy consumption in different areas, and the elastic coefficients are 0.028-0.371 and 0.066-0.158, respectively. (3) The elastic coefficient of CDD in urban areas of southern regions (0.158) is much larger than that in northern regions (0.068).

Urban concentration, non-renewable energy consumption, and output: do levels of economic development matter?

The accelerated urbanization process generates a significant increase in energy, whose sources are mainly polluting. The harmful effects of both processes are reflected in climate change. This article examines the equilibrium and causality relationship among urban concentration, non-renewable energy consumption, and the real per capita output in 110 countries during 1971-2017. Using data from the World Bank's World Development Indicators (2018), we classify countries into four groups according to their level of development. Our evidence suggests that urban concentration has a negative effect on real per capita output in high-income countries, while non-renewable energy consumption has a positive effect on all groups of countries. The cointegration tests show that there is short- and long-term equilibrium in all groups of countries. The results of the DOLS and PDOLS models indicate that the strength of the cointegration vector is weak in most of the countries and groups analyzed. The Granger-type causality tests show that there is bidirectional causality from the real per capita output to the urban concentration in high and middle-low-income countries. There is unidirectional causality from the population concentration towards the real per capita output in the low-income countries; from the non-renewable energy consumption to the real per capita output in high-income countries; from the real per capita output to the non-renewable energy consumption in the countries of medium-high and medium-low income; and from urban concentration to non-renewable energy consumption in high- and medium-high-income countries. Our results highlight the importance of promoting policies of urban planning and generation and consumption of renewable energy without limiting the expansion of the output.

Economic growth, financial development, and trade in nexuses of CO2 emissions for Southeast Asia.

In energy economics literature, we found few studies on the association between environmental quality energy consumption and financial development. The current study is an attempt to contribute in literature by examining the link between carbon dioxide (CO2) emissions, financial development, energy consumption, and economic growth, in South East Asian economies for the period 1980-2017 using annual time series data. For empirical analysis, Bound tests for cointegration and error correction approach are used. The estimated results confirm that financial development has positive impact on environmental quality. On the other hand, in the long run, the rise in energy consumption economic growth and trade openness is unfavorable for environment quality. Our results confirm U-shaped relationship between economic growth and environmental quality that is a proof of environmental Kuznets curve (EKC). Additionally, the government needs to design different modes of energy consumption to solve the problem of environmental degradation. Moreover, the major conclusion extends new insight for authority to make a comprehensive trade and financial policies to improve environmental quality.

Determinants of Decoupling Economic Output from Carbon Emission in the Transport Sector: A Comparison Study of Four Municipalities in China.

Quantitative analysis on decoupling between economic output, carbon emission, and the driving factors behind decoupling states can serve to make the economy grow without increasing carbon emission in China's transport sector. In this work, we investigate the decoupling states and driving factors of decoupling states in the transport sector of China's four municipalities (Beijing, Shanghai, Tianjin, and Chongqing) through combining the Tapio decoupling approach with the decomposition technique. The results show that (i) the decoupling state of Beijing, Shanghai, and Tianjin improved; Beijing stabilized in weak decoupling; Shanghai and Tianjin appeared to have strong decoupling, but the decoupling state of Chongqing deteriorated from decoupling to negative decoupling. (ii) The energy-saving effect was the primary contributor to decoupling in these four municipalities, promoting transport's economic growth strongly decouple from carbon emission. The economic scale effect was not optimized enough in Chongqing, facilitating expansive coupling, and expansive negative decoupling emerged. But it had a rather positive impact on decoupling process in Beijing, Shanghai and Tianjin, promoting economic growth to weakly decouple from carbon emission. (iii) The carbon-reduction effect promoted strong decoupling, which emerged in Shanghai's transport sector, more so than in the other three municipalities, in which weak decoupling emerged. Finally, several relevant policy recommendations were offered to promote the decoupling of carbon emission from economic growth and low-carbon transport.

Nexus between financial development, energy consumption, income level, and ecological footprint in CEE countries: do human capital and biocapacity matter?

In recent decades, climate change and environmental pollution have been at the center of global environmental debates. Nowadays, researchers have turned their attention to the linkage between real output and environmental quality and test the environmental Kuznets curve. Majority of the studies focus on a single pollutant aspect and measure the deterioration of the environment through carbon emission (CO2) only. In contrary, the current study uses a comprehensive proxy, ecological footprint, to measure the environmental quality of the sixteen Central and Eastern European Countries (CEECs). The aim of this paper is to discover the impact of financial development, economic growth, and energy consumption (renewable and non-renewable) on the environment. In addition, for the first time, the current study includes biocapacity and human capital in the growth-energy-environment nexus in the case of CEECs. In doing so, we used annual data of sixteen CEE countries in perspective of the One Belt One Road (OBOR) initiative and cover the period of 1991-2014. For reliable findings, this study focuses on second-generation econometric approaches to check stationarity, cross-sectional dependency, and co-integration among the model parameters. The long-run estimations of the "Dynamic Seemingly Unrelated-co-integration Regression" (DSUR) signify that the effect of economic growth on ecological footprint is not stable and validate N-shaped relationship for cubic functional form between per capita income and ecological footprint (environmental quality). Empirical evidence divulges that financial development and energy use significantly contribute to environmental degradation while renewable energy improves environmental quality by declining ecological footprint significantly. Moreover, the significant effects of biocapacity and human capital are positive and negative on the ecological footprint, respectively. In robustness check through the "Feasible Generalized Least Square" (FGLS) and "Generalized Method of Moment" (GMM) models, we found consistent result. Lastly, the "Dumitrescu-Hurlin (D-H) Panel Causality Test" demonstrates that two-way causal relationship exists between EF and GDP, EF and FD, EF and EU, EF and BC, and EF and HC, while one-way causality is running from RE to EF. This study puts the present scenario of CEE economies in front of the policymakers and suggests that they should consider the vital role of renewable energy and human capital to get sustainability.

Feasibility of peaking carbon emissions of the power sector in China's eight regions: decomposition, decoupling, and prediction analysis.

Carbon emissions in the power sector are an important part of China's total carbon emissions and have a significant impact on whether China can achieve the 2030 carbon peak target. Based on the three perspectives of decomposition, decoupling, and prediction, this paper studies the feasibility of carbon emission peaks in eight major regional power sectors in China. First, the generalized Divisia index model (GDIM) is used to decompose the carbon emissions of the eight regional power sectors, and the driving factors and their effects on carbon emissions in the power sector of each region are compared. Then, the decoupling index based on the generalized Divisia index model (GDIM-D) is used to study the decoupling relationship between the carbon emissions of the eight regional power sectors and economic growth. Finally, the carbon emissions and decoupling indices of the power sector from 2017 to 2030 are predicted. The results show the following. First, the gross domestic product (GDP) and output scale are the main factors contributing to the carbon emissions of the eight regional power sectors. The carbon intensity of the power sector in GDP (C/G) and output carbon intensity(C/E) are the main factors that contribute to the reduction. Second, the carbon emissions of the southern coast, the middle Yellow River, and the Southwest peaked in 2013 and have been decoupled from economic growth, while those in the other regions have not peaked or decoupled. Third, if the carbon emissions of the power sector in the Northeast, northern coast, eastern coast, middle Yangtze River, and Northwest reach a peak in 2030, they will face many emission reduction pressures. This paper provides a reference for studying the carbon emissions of China's regional power sectors and their relationship with economic growth and has important implications for peak carbon emissions at the national level.

A new methodology for assessing the energy use-environmental degradation nexus.

The international community is more than ever before worrying about the unremitting global warming and climate change and the responsibility of extensive energy use for that situation. This article contributes to the existing literature by examining whether energy consumption predicts CO2 emissions during the past 50 years in the five most polluting nations in the world. To do this, we have been using the recently developed predictability test of Westerlund and Narayan (Journal of Banking and Finance, 36, 2632-2640, 2012, Journal of Financial Econometrics, 13, 342-375, 2015). We take thereby into account the problem of endogeneity and persistence in the explanatory variable. Likewise, this test has the advantage of treating the problem of heteroscedasticity. Using several predictive evaluation measures and assuming the historical average as a benchmark, we find that the basic model of the predictability test of Westerlund and Narayan (2012, 2015) surpasses the benchmark model. These findings reveal that primary energy consumption predicts CO2 emissions in the world and all countries, for different forecast horizons. Further, the in-sample evidence of predictability has been supported by the out-of-sample analysis.

Economic growth and energy consumption in Brazil: cointegration and causality analysis.

Energy is a crucial part of any economy and holds a central position in enhancing social development in the world. Energy consumption and the economy in Brazil have both increased in the past decade. In this paper, time series statistics from 1980 to 2017 will be used to analyze the relationship between real GDP per capita and energy consumption to will examine how energy use in the country affects economic growth using causality models. This is established through testing for stationarity using Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test for trend stationarity. A cointegration relationship is found between the two variables.

A sustainable solution for electricity crisis in Pakistan: opportunities, barriers, and policy implications for 100% renewable energy.

This study aims to explore the potential of renewable energy resources to attain a 100% renewable electricity system in Pakistan. Currently, most of the electricity supply comes from fossil fuel, which is imported because Pakistan lacks its own resources. The imports of fossil fuel cost a huge amount and therefore afflict the already fragile economy. Further, the policy to rely on fossil fuel has significantly failed to address the energy crisis that has been lingering for the past two decades, and an acute shortage of electricity hinders the progress of various sectors of the economy. In addition, the global climate index has listed Pakistan among the top 10 climate-vulnerable countries, which makes it pertinent for the country to take precautionary measures for climate change mitigation. Pakistan has abundant renewable energy resources, which are more than sufficient to meet 100% of the present and future electricity demands. On the basis of the existing literature and the dilemma of the energy crisis and climate vulnerability, this study argues that transition to a 100% renewable electricity system is not only an option but also an urgent requirement. Further, we list the potential barriers, in the context of Pakistan, and put forward the policy implications for a swift transition to an entirely renewable electricity system.

Research on Total Factor Productivity and Influential Factors of the Regional Water-Energy-Food Nexus: A Case Study on Inner Mongolia, China.

With the supply of water, energy and food facing severe challenges, there has been an increased recognition of the importance of studying the regional water-energy-food nexus. In this paper, Inner Mongolia, including 12 cities in China, was selected as a research case. A super-efficiency slack based measure (SBM) model that considered the undesirable outputs was adopted to calculate the regional total factor productivity (TFP) and the Malmquist-Luenberger index was used to investigate the change trend of the TFP from 2007 to 2016 based on understanding the water-energy-food nexus. Finally, influential factors of the TFP were explored by Tobit regression. The results show that the 12 Inner Mongolia cities are divided into higher, moderate and lower efficiency zones. The higher efficiency zone includes Ordos, Hohhot, Xing'an, and Tongliao, and the lower efficiency zone includes Chifeng, Xilin Gol, Baynnur, Wuhai and Alxa. There is a serious difference in TFP between Inner Mongolia cities. During the study period, the TFP of the water-energy-food nexus in Inner Mongolia cities shows a rising trend, which is mainly driven by the growth of technical progress change. However, the average ML values of the lower and moderate efficiency zones were inferior to the higher efficiency zone in six of the ten years, so the difference between Inner Mongolia cities is growing. According to the Tobit regression, the mechanization level and degree of opening up have positive effects on the TFP, while enterprise scale and the output of the third industry have negative effects on the TFP. Government support does not have any significant impact on the TFP. Finally, suggestions were put forward to improve the TFP of the water-energy-food nexus in Inner Mongolia cities.

Nexus of FDI, population, energy production, and water resources in South Asia: a fresh insight from dynamic common correlated effects (DCCE).

The purpose of this study is to explore the empirical relationship between foreign direct investment (FDI), population, energy production, and water resources in South Asia. The newly developed approach dynamic common correlated effects (DCCE) by Chudik and Pesaran (Journal of Econometrics 188:393-420, 2015a) for measuring co-integration has been applied in the present study. This procedure provides significant robust outcomes in the presence of cross-sectional dependence among the cross-sectional units. The findings confirmed that earlier models, such as mean group (MG), pooled mean group (PMG), and augmented mean group (AMG), which have been used in the literature for long data, provide misleading results in the presence of cross-sectional dependence among the cross-sectional units. A statistically significant and negative result has been observed between FDI, population, energy production, and water resources in South Asia. The governments of South Asian economies must encourage green FDI initiatives for water management, ensuring water security, securing natural resources for enhancing the sustainable development of regional economies.

Economic growth, energy consumption, and carbon emission nexus: fresh evidence from developing countries.

The developing countries and emerging economies are crucially contributing to global economic development, energy transition, and climate governance. This paper employs panel cointegration technique to investigate the long-run relationship between carbon emissions and five impacting factors (per capita GDP, primary energy consumption, international trade, fossil proportion, and quadratic per capita GDP) in 50 representative developing countries during 1995-2017. The empirical findings confirm the existence of long-run equilibrium, and the regressing coefficients of fully-modified OLS (FMOLS) indicate that (a) impacting features of the inverted U-shaped curve of Environmental Kuznets Curve (EKC) theory appear in a few countries, such as Mexico, Croatia, Kazakhstan, Iran, Algeria, Indonesia, and Thailand; (b) the energy consumption has statistically positive and significant impacts on boosting the carbon emissions; (c) the negative effect of international trade emerges in the developing nations enjoying trade surpluses; and (d) fossil energy share poses a mixed impact. This paper reveals that the vast and inspiring contribution of developing countries to global carbon emission reduction should attract more international attention and assistance.