Non-fossil Energy Use Research Articles

Analysis of influencing factors of industrial green and low-carbon transformation under the background of “double carbon”: evidence from Sichuan province, China

Introduction: Industrial green and low-carbon transformation is the key to improve economic development and necessary process to achieve the goal of the carbon peaking and carbon neutrality. Few studies have been done on the decomposition of carbon emission factors in industries and sub-industries and the impact of green and low-carbon transformation about carbon emission in each industry quantitatively. However, the study of industries and sub-industries can comprehensively analyze the development path of green and low-carbon transformation from a more detailed perspective, and provide scientific reasons for the optimization of industrial structure and energy structure.Methods: The extended Kaya identity for industrial carbon emission is constructed to obtain four factors influencing industrial carbon emission: economic output effect, industrial structure effect, energy intensity effect, carbon consumption intensity in this paper. Then, the LMDI decomposition method is combined with the above identity to innovatively obtain the contribution value of carbon emissions from the perspective of overall, industrial sector and tertiary industry. Then, based on the results of factor decomposition, a multi-index scenario prediction model is constructed. On this basis, the extreme learning machine model optimized by particle swarm optimization (PSO-ELM) was used to predict the influence of the changes in the driving factors on the reduction of industrial carbon emissions. By setting the baseline and industrial green and low-carbon transformation scenarios, it is predicted that industrial carbon emission in Sichuan Province.Results and discussion: (1) Economic output effect always promotes the growth of industrial carbon emissions, and with the adjustment of industrial structure and energy structure, the other three factors begin to restrain the growth of carbon emissions. (2) Scenario prediction shows that without considering the economic costs of transformation, improving carbon emission reduction efficiency can be obtained through accelerating the rate of change of industrial structure of the secondary and tertiary industries, increasing the proportion of energy intensity reduction, and strengthening the proportion of non-fossil energy use.

Green economic recovery hindered by increased carbon intensity: Evidence from China

This study looks into how growing carbon intensity affects China's usage of non-fossil fuels and green economic recovery. We use an experimental methodology to use information from China's Natural Resource Growth and Miscalculation Improvement Framework from 2011 to 2022. This study examines how carbon intensity affects China's efforts to support a green economic rebound. We also want to clarify how non-fossil energy might help reduce carbon emissions. We find that expanding the use of non-fossil fuels and the green economic recovery are both hampered by growing carbon intensity. In particular, we find that in years with higher carbon intensity, the growth rate of non-fossil energy use is much lower. Additionally, our findings demonstrate that rising carbon intensity causes energy efficiency and carbon emissions to decline. We discover that provinces with high carbon emissions are more severely affected by the detrimental effects of increased carbon intensity on the green economic recovery. Our findings imply that for China to achieve a green economic recovery and reduce carbon emissions, carbon intensity must be addressed. Increased carbon intensity can have negative effects, but they can be lessened by policies that encourage the use of non-fossil fuels and boost energy efficiency.

TACKLING CARBON INTENSITY WITH GREEN FINANCE IN THE COVID-19-ERA: RECOMMENDATIONS FOR OECD ECONOMIES

Green financing has been examined in the literature. However, its impact on carbon intensity has not been fully investigated. This research sets out to fill this gap by using the dimensions of green loans, securities, insurance, and investment. In exploring the connections between green financing, nonfossil energy use, and carbon intensity, we utilized data from 2016 to 2020 to run an advanced quantile modeling. We applied the decision-making unit-method of data envelopment analysis for analyses. Our main findings are as follows. Rapid advances in the green finance sector in Organisation for Economic Co-operation and Development countries were coupled with an increase in nonfossil energy usage, resulting in a decline in carbon intensity. When the growth in nonfossil energy consumption was reduced, green investment was put on hold, and the green financing industry would be negatively impacted. The role of green financing and carbon intensity in nonfossil energy use is coupled with strong government policy interventions. Nonetheless, the effects of green finance initiatives often lag. Moreover, these effects are inconsistent. This research suggests new methods to increase the use of nonfossil energy, build a carbon trading market, and increase the consumption of green financing policies post COVID-19.

Will researching digital technology really empower green development?

The information industry has become a “new engine” driving the growth of the world economy. However, there are many controversies about whether digital technology can reduce the intensity of carbon emissions. Based on OECD data, KPWW method and multiple panel regression, this paper explores the impact and mechanism of digital technology innovation and technology spillover to the domestic carbon emission intensity. Through impulse response analysis and variance decomposition, the comprehensive impact of digital technology on carbon intensity is clarified. This paper concludes that technology innovation in the information industry will increase the intensity of carbon emissions, while cross-industry technology spillovers are persistent for reducing the intensity of domestic carbon emissions. Since the emission reduction effect of technology spillover is greater than the emission increase effect of technology innovation, the digital technology would empower domestic green development. Increasing the proportion of non-fossil energy use and optimizing the industrial structure are effective mechanisms for digital technology innovation to reduce carbon emission intensity.

Automatically Creating HVAC Control Strategies Based on Building Information Modeling (BIM): Heat Provisioning and Distribution

Building Information Modeling (BIM) data are typically exchanged using the Industrial Foundation Classes (IFC) standard. An IFC-based BIM model is a container for data that is created during the design and planning phase and is therefore a rich source of information for the commissioning phase, in which building services are brought to operation. This paper examines the use of BIM data for automated generation of control strategies for energy systems, thus simplifying and accelerating the commissioning phase. We present a methodology to create control strategies of a building heating system with several variations of renewable energy systems and include both heat provisioning and a distribution system. The control goals include favoring the use of non-fossil energy, which is provided by a combination of photovoltaic system (PV), heat pump (HP) and industrial excess-heat source. Thermal energy storages are integrated for load shifting purposes and the control of the heat distribution system is designed towards the requirements of building physics, occupancy and outside climate conditions. A validation of the approach is presented in a combined SIMULINK and TRNSYS simulation environment.

Nexus between green finance, non-fossil energy use, and carbon intensity: Empirical evidence from China based on a vector error correction model

Previous studies have considered the effect of financial development on carbon emissions; however, few studies have explored the role of green finance in carbon mitigation. To bridge this gap, the current study constructs a green finance development index based on four indicators: green credit, green securities, green insurance, and green investment. A vector error correction model is used to analyze relationships between the development level of green finance, non-fossil energy consumption, and carbon intensity using data from 2000 to 2018. We find that China’s green finance industry developed rapidly, and improvements in the green finance development index, as well as the increasing use of non-fossil energy, contributed to a reduction in carbon intensity. Simultaneously, an increase in carbon intensity inhibited the expansion of non-fossil energy use, impeded the investment flow to green projects, and ultimately led to a deterioration of green finance development. In addition, non-fossil energy consumption in China was primarily influenced by green finance and carbon intensity, with clear policy-driven effects. However, the impacts of green finance policies continually fell short and lacked continuity. This study proposes ways in which to improve the effect of green finance policy implementation, expand the consumption of non-fossil energy, and develop a carbon trading market.

Revisiting the role of natural gas as a transition fuel

The objective of this paper is to assess the potential of natural gas as a transition fuel towards a low- and zero-carbon economy. We use the previously established global energy market model (GEM) to first provide a close match of the historical energy mix and the associated carbon levels. The model is then used to make simulations of how the energy mix and carbon quantities would evolve in the long distant future—the year 2150—if past dynamics were an indication of the future. A similar GEM modeling exercise was carried out in a previous work, using historical data up to the year 2005, showing that natural gas would help slow global carbon growth in the next 50–100 years, thus paving the way towards a low carbon future dominated by non-fossil energy use. The present study uses the most recent statistics, from 2005 to 2017, to verify the accuracy of the original GEM projections. Our findings show continued penetration of natural gas in the energy mix until the mid-twenty-first century and an eventual reduction of carbon levels starting around that time.

Energy-water nexus in China's energy bases: From the Paris agreement to the Well Below 2 Degrees target

China's energy bases suffer from serious water shortages. To analyse the energy-water nexus under China's Nationally Determined Contribution (NDC) and the Well Below 2 Degrees (WBD2) target with a more detailed spatial resolution, a five-region China TIMES-W model incorporating water issues is developed. The results show the following: 1) Strict climate targets will require significant increases in non-fossil energy use. 2) Water withdrawal for energy use in the energy bases is expected to be 9.8 billion m3 in 2050 in the WBD2 scenarios. The increased water withdrawal will mainly be caused by the deployment of water-intensive carbon mitigation technologies, such as coal/gas-fired power plants with CCS, concentrating solar power plants and biomass power plants, the water withdrawal for which will be 5.5 billion m3. 3) The carbon intensities for the power sector will be in the range of 0.04–0.15 kg CO2/kWh while the water withdrawal intensities 0.33–1.38 m3/kWh by 2050 in the WBD2 scenario in different energy bases. Not only renewable energy potential but also available water resources should be considered in the development plan for energy bases. In addition, more R&D efforts on CCS with air cooling and concentrating solar power with air cooling should be encouraged.

Transport biofuels in global energy–economy modelling – a review of comprehensive energy systems assessment approaches

AbstractThe high oil dependence and the growth of energy use in the transport sector have increased the interest in alternative nonfossil fuels as a measure to mitigate climate change and improve energy security. More ambitious energy and environmental targets and larger use of nonfossil energy in the transport sector increase energy–transport interactions and system effects over sector boundaries. While the stationary energy sector (e.g., electricity and heat generation) and the transport sector earlier to large degree could be considered as separate systems with limited interaction, integrated analysis approaches and assessments of energy–transport interactions now grow in importance. In recent years, the scientific literature has presented an increasing number of global energy–economy future studies based on systems modelling treating the transport sector as an integral part of the overall energy system and/or economy. Many of these studies provide important insights regarding transport biofuels. To clarify similarities and differences in approaches and results, the present work reviews studies on transport biofuels in global energy–economy modelling and investigates what future role comprehensive global energy–economy modelling studies portray for transport biofuels in terms of their potential and competitiveness. The results vary widely between the studies, but the resulting transport biofuel market shares are mainly below 40% during the entire time periods analysed. Some of the reviewed studies show higher transport biofuel market shares in the medium (15–30 years) than in the long term (above 30 years), and, in the long‐term models, at the end of the modelling horizon, transport biofuels are often substituted by electric and hydrogen cars.

Windfall gains or eco-innovation? ‘Green’ evolution in the Swedish innovation system

This paper therefore looks closer into climate gas emission and the shift to non-fossil energy in Sweden. What types of organizations are behind the shift to non-fossil energy use, what are the relative effects on emissions, to what extent can these interactive dynamics be considered eco-innovations? Do these effects vary between public and private organizations, and if so, can they be related to specific institutions and policies? Methods include statistical survival analyses, in particular Cox regression. These analyses inform us why energy sources shift. Results indicate that wood fuel and solid waste increase as sources of energy while fossil oil has decreased between 2003 and 2010. This result is in line with industrial and environmental policies of the Swedish governments that present these facts as institutionally and policy-related ‘green innovation’. However, our analysis contests such a conclusion and it is noticed that the shift to non-fossil sources of energy has not led to verifiable decreases in green-house gas emissions. Results instead suggest that ‘green’ innovation of non-fossil energy was mostly the effect of low-tech innovation in public organizations with no fundamental effect on CO2 emissions.

Estimate of China's energy carbon emissions peak and analysis on electric power carbon emissions

China's energy carbon emissions are projected to peak in 2030 with approximately 110% of its 2020 level under the following conditions: 1) China's gross primary energy consumption is 5 Gtce in 2020 and 6 Gtce in 2030; 2) coal's share of the energy consumption is 61% in 2020 and 55% in 2030; 3) non-fossil energy's share increases from 15% in 2020 to 20% in 2030; 4) through 2030, China's GDP grows at an average annual rate of 6%; 5) the annual energy consumption elasticity coefficient is 0.30 in average; and 6) the annual growth rate of energy consumption steadily reduces to within 1%. China's electricity generating capacity would be 1,990 GW, with 8,600 TW h of power generation output in 2020. Of that output 66% would be from coal, 5% from gas, and 29% from non-fossil energy. By 2030, electricity generating capacity would reach 3,170 GW with 11,900 TW h of power generation output. Of that output, 56% would be from coal, 6% from gas, and 37% from non-fossil energy. From 2020 to 2030, CO2 emissions from electric power would relatively fall by 0.2 Gt due to lower coal consumption, and relatively fall by nearly 0.3 Gt with the installation of more coal-fired cogeneration units. During 2020–2030, the portion of carbon emissions from electric power in China's energy consumption is projected to increase by 3.4 percentage points. Although the carbon emissions from electric power would keep increasing to 118% of the 2020 level in 2030, the electric power industry would continue to play a decisive role in achieving the goal of increase in non-fossil energy use. This study proposes countermeasures and recommendations to control carbon emissions peak, including energy system optimization, green-coal-fired electricity generation, and demand side management.

Pledges for climate mitigation: the effects of the Copenhagen accord on CO2 emissions and mitigation costs

The UN Framework Convention of Climate Change 15th Conference of the Parties Copenhagen Accord has been followed up by national pledges of greenhouse gas emissions reductions in the year 2020 without specifying measures to enforce actions. As a consequence, the capacity of parties to fulfil their obligations is of basic interest. This article outlines the effects of full compliance with pledges on greenhouse gas emissions, economic growth, and trade. The study is based on the global computable general equilibrium model global responses to anthropogenic changes in the environment (GRACE) distinguishing between fossil and non-fossil energy use. Global emissions from fossil fuels in 2020 turn out to be 15 % lower than in a business as usual scenario and 3 % below the global emissions from fossil fuels in 2005. China and India increase their emissions to 1 % and 5 % above business as usual levels in 2020. India and Russia increase their net export of steel corresponding to around 30 and 45 % of their production levels in 2020. In spite of some leakage of energy intensive production also to China, we find that structural change remains the dominant factor behind the rapid reduction of CO2 emission intensity in China towards 2020.

Technology growth curves: a new approach to reducing global CO 2 emissions

An alternative approach to relying on fixed national caps and deadlines for reducing carbon dioxide emissions and alleviating global warming is offered. The new proposal relies instead on a universal logistic growth curve to establish, for each year, the minimum fraction of each country's emissions that can arise from non-fossil fuels. Since developing countries presently rely more (i.e. greater percentage) on non-fossil sources, the proposed will tend to require the developed countries to take actions earlier to increase their efficiency and the use of non-fossil energy.

Energy substitution to reduce carbon dioxide emission in China

Energy consumption per capita in China is very low, less than one-half of the average level of the world. But China has a large population and coal consumption dominates total energy consumption (the share of coal was 76% in 1989). Therefore, the amount of CO 2 emitted is very large (11% of the total world emission in 1990). Many people are concerned about what measures can be taken to reduce CO 2 emission in China. Proposed measures include energy-efficiency improvement, energy substitution, etc. Energy substitution is one of the most effective measures of reducing CO 2 emission in China. We give a detailed analysis of the exploitable potential of hydropower, nuclear power and the new energy sources (including solar, wind, geothermal, and tidal energy) from 1990 to 2020. Estimated reductions in CO 2 emission due to enhanced use of non-fossil energy are also given. About 330 × 10 6tce (we use for coal 7000 kcal/kgce) of non-fossil energy will be produced and about 239 × 10 6mt of C can be eliminated in 2020 (about 38% of China's total CO 2 emission in 1990).