Factors Influencing the Renewable Energy Consumption in Selected European Countries

The overcoming of the issues on energy crisis and inequality have become the priorities as far developing as developed countries are concerned. Moreover, energy inequality has increased due to the shortage of natural gas and rising energy prices in retaliation to the economic recovery affected by the COVID-19 pandemic. This study aims to verify the linkage between the growth of renewable energy consumption and the country’s economic advancement. In this context, this paper determines the main driving forces of renewable energy consumption in European countries during 2000–2018. The annual data for panel regression analysis are retrieved from the OECD. Stat and World Bank Open Data. This empirical analysis employed a set of estimation procedures such as the panel unit root test (Levin, Lin & Chu; Im, Pesaran, Shin W-Stat; ADF-Fisher Chi-square; and PP-Fisher Chi-square methods), the Pearson correlation, fixed- and random-effects models, generalized method of moments (GMM), Hausman and the robustness tests. The results from the Hausman test ratified that the fixed-effects regression model is more suitable for involved panel balanced data. The results of fixed-effects regression and GMM identified the statistically significant and positive relationship between the share of renewable energy consumption of total final energy consumption, GDP per capita, and CO2 emissions per capita for the overall sample. In turn, the total labor force, the gross capital formation, and production-based CO2 intensity are inversely related to renewable energy consumption. The identified effects could provide some insights for policymakers to improve the renewable energy sector towards gaining sustainable economic development.

PSXI-21 Soil emission of carbon dioxide and behavior of microorganisms in soils of Western Kazakhstan

Kazakhstan Western ecosystems are intensively used in agricultural production. Assessing greenhouse gas emissions from soils, especially CO2, is important. In the upper stages, microbiology, characteristics and condition of the soil change. Biological intensity indicators are soil respiration processes, numerous microbiocenoses species composition. Soil CO2 emissions were measured 5 times monthly during three years. The CO2 flow rate from soil surface is measured by a closed dynamic chamber method with Li-8100A field respirometer. Metagenomic soil testing used bacteria DNA, archaea, real-time PCR, 16SrRNA sequencing. The soil CO2 monthly dynamics fluxes varied among the lands, within the season. In 2020, the CO2 emissions soil peak noted in the pasture. There is a slight decline in summer with a decrease towards the cold season. Comparison between the CO2 flux pasture soils is less in virgin soil. The minimum CO2 flux was recorded in November - February; in the spring, the flux increases. The above CO2 emissions were recorded in summer. In soils, there is wide variety of microorganisms with opposite and incompatible properties for one habitat. The microbial communities structure identified at the family level. The taxonomic samples structure ominated by phylae - Actinobacteria, Proteobacteria, Chloroflexi, Acidobacteria, Gemmatimonadetes, Firmicutes, Actinobacteria. The spread explained by increased actinomycetes resistance characteristic to low moisture content with long dry period. For comparative evaluation microbial communities results comparing by cenoses of upper horizons with dark chestnut soil indicators. This violation caused microorganisms resistance to disturbing factors. On anthropogenically disturbed saline soils, the bacteria found were specific and resistant to critical conditions. CO2 emission in soil varied cenosis type. The CO2 intensity factors were precipitation deficit, high temperature. The profile microorganisms distribution corresponded to the soil horizons humus content. During summer soil drying, the deep soil horizons abundance occurred where moisture is retained.

Impact of nonintrusive load monitoring on CO2 emissions in Malaysia

Nonintrusive load monitoring (NILM) based energy efficiency can conserve electricity by creating awareness with the behaviour change and shrinking CO2 emissions to the environment. However, the lack of effective models and strategies is problematic for policymakers to forecast quantitatively CO2 emissions. This paper aims to study the impact of NILM on CO2 emissions in Malaysia. Firstly, the predictive models were established based on Malaysia open data from 1996 to 2018. After that, scenario simulations were conducted to predict CO2 emissions and NILM impact on environmental degradation in 2019-2030. The results revealed that a 12% reduction in electricity consumption due to NILM could contribute to a 10.2% shrinkage of the total CO2 emissions. The result also statistically confirmed Malaysia to achieve a 45% reduction of CO2 intensity in 2030. With NILM, the carbon reduction can be further enhanced to 60.2%. The outcomes provide valuable references and supporting evidence for policymakers in planning effective carbon emission control policies and energy efficiency measures. The work can be extended by developing a decision support system and user interfaces access via the cloud.

Recycling and Biomass Influence on the Production-Based CO2 Intensity Based on Circular Economy Concept

In a closed loop structure, the circular economy reflects a concept for converting material and energy wastes into capital for other purposes. The circular economy's key goal is to reduce energy and material waste. The best-case scenario will be to eliminate wastes and repurpose them, which is one of the key goals of the circular economy. The circular economy and sustainable development are inextricably linked. The framework reflects resource reuse and recycling in order to reduce waste and the use of biodegradable items that can be returned to the ecosystem after rejection. Many programs are being developed to incorporate the circular economy in order to apply the system's best practices. Recycling and reusing goods for the same or new items are the best practices for reducing waste and energy consumption. The main goal of the study was to analyze the effect of waste generation and recycling on production-based CO2 intensity based on circular economy concept. For such a purpose adaptive neuro fuzzy inference system (ANFIS) was implemented since the methodology is suitable for statistical investigation of strongly nonlinear data sample due to features of fuzzy logic system. Generated and recycled waste including biomass is the most influential factors for the production-based CO2 intensity based on circular economy concept. The obtained results could represent the best practices for implementation of circular economy concept.

The Color of Energy: The Competition to be the Energy of the Future

Energies may be described as brown, blue or green. Brown energies are CO2-emitting fossil fuels. Blue energies employ carbon capture and storage (CCS) technologies to remove the emitted CO2 from brown energies. Green energies are zero or low CO2-emitting renewable energies. Likewise, energy carriers such as electricity and hydrogen may be described as brown, blue or green if they are produced from brown, blue or green energy, respectively. The transition from a high carbon intensity to a low carbon intensity economy will require the decarbonization of three major sectors: power, transport and industry. By analyzing the CO2 intensity and levelized cost of energy (LCOE) of energy and energy carriers of different colors, we show that renewable energies are best used in replacing fossil fuels in the power sector where it has the most impact in reducing CO2 emission. This will consume the majority of new additions to renewable energies in the near to medium future. Consequently, the decarbonation of the transport and industry sectors must begin with the use of blue electricity, blue fossil fuels and blue hydrogen. To achieve this, implementation of large-scale CCS projects will be necessary, especially outside of USA and northern Europe. However, this will not happen until significant financial incentives in the form of carbon tax or carbon credit becomes available from national governments. Furthermore, private-public partnership and intergovernmental cooperation will be needed to implement these CCS projects.

The Impacts of Non-Renewable Energy Consumption and Education Expenditure on CO2 Emission Intensity of Real GDP in China

BackgroundWith the economic development, China has become the world's largest CO2 emitter. Given that climate warming has increasingly become the focus of the international community, Chinese government committed to reducing its CO2 emission intensity substantially. Prior studies find that the evolution of economic structure and technological progress can reduce CO2 emissions, but lack of considering CO2 emissions and output as a whole. In addition, the role of education expenditure is relatively overlooked. This paper contributes to the literature by examining the link of CO2 emission intensity, non-renewable energy consumption and education expenditure in China during 1971-2014. ResultsWe use the ARDL approach and find that in the long run, every 1% increase in non-renewable energy consumption results in a 0.92% increase in CO2 intensity, while every 1% increase in operational education expenditure reduces the CO2 intensity by 0.86%. In the short term, 36% of the deviation from the long run equilibrium is corrected in the next period.ConclusionsWe draw out two important conclusions and make important policy recommendations. First and foremost, as long as the increase in operational educational expenditure exceeds the increase in non-renewable energy consumption, CO2 intensity of real GDP will decrease in the long run. This means that in the development stage when economic activities are still highly dependent on non-renewable energy sources, the Chinese government should continue to vigorously increase expenditures on public education. Second, the increase in non-renewable energy consumption will result in an increase in CO2 intensity of real GDP. Therefore, gradually increasing the proportion of clean energy consumption in the energy nexus is another powerful starting point for China to achieve its goal of reducing CO2 intensity of real GDP.JEL ClassificationC32. I2. Q4. Q53. Q56.

Environmental Kuznets Curve Revisit: Role of Economic Diversity in Environmental Degradation

Background: Unlike the classical view, a new path of economic growth and development among the emerging and developing nations seems to have distinct impact on environment. Customary patterns of production and consumption have undergone significant changes and the new “growth with non-smoke-staks” has put the developing economies on a path that can change Environmental Kuznets Curve (EKC) fundamentally. With this view, the current study attempts to examine how these growth patterns among developing world have impacted the degradation of environment. We argue that including income per capita and share of manufacturing would not capture the full growth dynamic of developing and emerging countries and therefore it masks the real impacts on environmental degradation. To this end, we introduce the Economic Complexity Index (ECI) to the model to reflect the full impacts of new growth approaches on CO2 emission levels by using a panel data analyses of 100 emerging and developing countries over 1963-2018 period.Results: The results indicate that complexity of the economies of developing and emerging countries has added to the CO2 emission levels in absolute terms but it has helped to reduce the CO2 intensity. Conclusions: The implications of the findings for developing and developed countries could be quite significant. For advanced economies, a downwardly-shifted Kuznets curve implies that, on one hand, technology transfers have been successful in curbing the environmental degradation of developing economies and, on the other hand, the economic transformation strategies of developing world is working in a sustainable way.

Technology Focus: Drilling Automation and Innovation (February 2021)

Drilling automation and innovation continue as dominant trends despite market downturns and unprecedented challenges in the past year. In many ways, the drive toward new efficiencies and step changes in well-construction performance has taken on an even greater sense of urgency. Further advancements in automation and innovation in well construction are recognized globally as keys to unlocking new opportunities in the ever-changing world in which we live. OTC Live sessions in late 2020 included a fascinating session titled “Opportunities and Challenges in Frontier Basins and Emerging Offshore Areas.” Despite pandemic-induced uncertainty, a significant number of high-impact exploration efforts, including projects in deepwater Gulf of Mexico, Brazil, west Africa, the Mediterranean, and Asia were ongoing. Panelists agreed, given world population and energy consumption being forecast to grow 20% by 2040, that increased hydrocarbon supplies, in addition to renewables, are essential to meeting future demand. The discussion also highlighted increased emphasis on carbon footprint reduction. Leaders from Shell, Expro, Wood Mackenzie, and others spoke to a CO2-intensity/barrel of oil equivalent chart comparing relative values for deep water, unconventionals, oil sands, and liquefied natural gas. It is noteworthy that deepwater production represents the lowest carbon footprint of all hydrocarbon sources by a significant margin. This advantage, combined with the potential for large resource size, high flow rates, and low well count, suggest that deepwater assets will compete in long-term portfolios for many operators. Referring to the current selection of SPE drilling-related manuscripts, automation of land rigs within onshore unconventional basins remains a widely published subject. More specifically, automation of the directional drilling process continues to yield improvements in performance and efficiency. It is often noted that well costs have been reduced by more than 50% with advancements related to horizontal technology, digitalization of well construction, and rig automation. These technologies were largely initiated within onshore, unconventional projects, but application is now wide-spread for offshore, complex wells. Selected papers in this feature are chosen to highlight the latest achievements and near-term opportunities across the full spectrum of upstream projects. A consistent message from paper SPE 203251 regarding drilling automation in the digital age reads, “industry has yet to benefit on a large scale from these advancements and…significant value remains untapped.” This reoccurring theme appears across operator and geographical boundaries, revealing significant opportunity and the need for ongoing emphasis. Software and hardware evolution progresses along with more- comprehensive integration of rig equipment and functionality. Industry now is more focused on moving from automation of individual tasks toward automation of the full well-construction process from plan to completed borehole. This idea is presented in paper SPE 201763. Change management remains a key issue within the process to ensure adequate control, early buy-in from stakeholders, and strong leadership. In summary, impressive examples of ongoing innovation span domestic unconventional plays, remote/international locations, geologically complex thrustbelt fields, and deep water with managed-pressure drilling in narrow pore pressure/fracture gradient environments. The few selections that appear here are a reflection of many more published by SPE in the past year and are a powerful testament to the ingenuity and perseverance of those involved.