Search Results (30)

With the proposal of the dual carbon goals, it is of great significance to identify the causes of carbon emissions and reduce carbon emissions directly. There is a lack of analysis on the causes of carbon emissions considering the coupling effect of multiple factors and regional heterogeneity. The causes of carbon emissions are examined from multiple perspectives utilizing the panel data spanning from 1997 to 2022, encompassing 30 provinces in China. To further analyze the causes of carbon emissions, an enhanced feature and regularized gradient boosting tree (EG-Tree) model is constructed, and a scoring method for the tree structure is proposed. The coupling effect of multiple factors are analyzed such as coal, coke, crude oil, gasoline, kerosene, diesel oil, fuel oil, liquefied petroleum gas, natural gas, etc., on the carbon emission intensity of various industries and their regional heterogeneity. The results show that: (1) The EG-Tree model constructed in this study could accurately analyze the causes of carbon emissions under the coupling of multiple factors based on the cumulative iterative feature branching contribution values (impact factors), with an average model fitting precision of 0.30. This means the carbon emission intensity values were predicted by various industries in different regions based on different energy consumption levels and industry-specific carbon emissions, compared with the carbon emission intensity values calculated using the carbon emission measurement dataset. (2) The consumption of coal and coke has a significant impact on the average carbon emission factors of various industries, with values of 7139.95 and 7217.05, respectively. The consumption of natural gas and liquefied petroleum gas has a smaller impact on the average carbon emission intensity of various industries under the EG-Tree model with corresponding carbon emission intensity impact factors of 5057.90 and 2789.57, respectively. (3) The Northeast region is a low-carbon area, while the East region is a high-carbon area, with total carbon emissions of 2,238,646.60 million tons and 5,566,314.00 million tons of CO₂, respectively. The Northeast region has the lowest pollution intensity for heating and cooling, with carbon emissions of 155,661.73 million tons of CO₂; the industrial carbon emissions in the East region are relatively high at 1,623,835.62 million tons of CO₂. The research findings of this study are beneficial for relevant departments to focus on the main impact factors of carbon emissions in different regions and industries, and to develop targeted emission reduction policies. Full article

The growing global interest in mitigating climate change implies an increased importance of sustainable development to achieve greenhouse gas emission reductions. The paper analyses the impact of key economic and environmental factors, such as the share of renewable energy, gross domestic product (GDP), fossil fuel consumption, final energy consumption in households and industry, and forest area, on greenhouse gas (GHG) emissions in the European Union (consisting of 27 members) and Poland for comparison—for the period from 1990 to 2023. The study fills a gap in identifying the cross-sectoral determinants of greenhouse gas emissions in the EU, focusing specifically on Poland and the whole EU region since the beginning of the European Union. The research involved the implementation of statistical analyses, dynamic analyses, correlation analyses, and regression analyses. The results showed an increase in the share of renewable energy, GDP, and forest area, which was negatively correlated with the volume of GHG emissions. In contrast, final fossil fuel consumption and final energy consumption in industry and households (to a slightly lesser extent) were also significantly but positively correlated. It is worth noting that the strength of calculated relationships differed for the EU and Poland. The study revealed trends and correlations that affect GHG and are relevant to policy implications for EU climate goals. Considering the various determinants of GHG emissions and Poland’s unique situation (high dependence on coal and a large share of heavy industry), conclusions were formulated for Poland’s and the EU’s climate policies in the context of the European Green Deal. Full article

An alternative combustion technology to replace conventional start-up and flame stabilization using fuel oil or natural gas in pulverized coal-fired boilers has been investigated. In this study, a novel plasma burner design is proposed as a replacement for traditional auxiliary burners, operating by generating plasma through the ionization of air using microwave energy. The burner features an internal combustion system and a multi-stage ignition process to enhance flame stability, improve combustion efficiency, and enable more controlled pulverized coal burning within the plasma. Supported by a magnetron generating microwave energy at 915 MHz with a 75 kW output, the burner directly ignites approximately 22% of the coal–air mixture in the plasma zone, forming a stable flame that ensures complete combustion of the remaining coal. An experimental system was established, and tests were conducted by burning up to 3000 kg/h of pulverized coal in an industrial-scale setup at Unit-1 of the 22 MW_e Soma A Power Plant to optimize burner parameters. The specific microwave energy consumption was calculated as 0.055 kWh/kg of coal, demonstrating high energy efficiency and low operational cost. These results confirm that the microwave-assisted plasma burner is a technically viable, energy-efficient, and environmentally friendly alternative to conventional auxiliary burners. Full article

The study investigates the impact of water use in energy production in industrial plants, considering the interdependence between water and energy, or the water–energy nexus, to promote sustainable water and energy management. More specifically, it focuses on the industrial sector, particularly on electricity production in thermoelectric power plants, which require large amounts of water for cooling in its production cycle. The field of analysis is set in Italy, referring to the applications of the European Industrial Emissions Directive and Italian regulations that govern water and energy usage. The focus is on large combustion plants, which need to be monitored by national authorities. The Italian situation is outlined, exposing consumption data from major thermoelectric power plants in 2021 through 2023, highlighting the water usage trend and electricity production. In 2023, total water use for these installations was 9,892,719,965 m³—mainly from seawater—with an overall production of electric energy of 117,239,954 MWh, with a relevant fuel consumption from natural gas (18,544,742,774 Sm³). It also analyzed the application of best available techniques to reduce water consumption, recycle water flows, and minimize the environmental impact of power plants. Finally, the main fuels used in these plants, such as natural gas, coal, and biomass, are presented, along with the environmental performance of the power plants based on water use per unit of energy produced. Full article

The prolonged operation of thermal power plants inevitably leads to component aging and a gradual decline in performance. This deterioration increases the gross heat rate and reduces electrical output, resulting in higher fuel consumption and lower electricity production. Consequently, these issues can cause significant financial losses and threaten the plant’s competitiveness. This paper presents a comprehensive methodology for improving the performance of existing plants. The methodology consists of two crucial elements: steam turbine testing and numerical simulation of the process. The tests should be comprehensive to ensure accurate measurements and reliable conclusions. The developed method for process simulation enables the calculation of overall performance, like specific heat rate and thermal efficiency, as well as the performance of individual components under various operational conditions. Comparing numerical results with experimental data can effectively identify operational problems. Based on these findings, targeted overhauls and other corrective measures can substantially improve the plant’s thermal efficiency and financial performance. The system was demonstrated through a case study of a 120 MW coal-fired steam turbine. The test revealed that it consumes more than 10% additional heat compared to its original design specifications. The analysis identified operational issues and recommended improvement measures, focusing exclusively on the steam turbine set while excluding the boiler. Full article

Energy resources are a material basis for regional sustainable development and ecological security. However, this issue has not been adequately studied in Northwest China. Here, we consider the five northwestern provinces of China and break down the change in energy use intensity. Results show that the total energy intensity in the five northwestern provinces decreased from 2.389 tons/10⁴ Chinese yuan (CNY) in 2000 to 0.92 tons/10⁴ CNY in 2021. The main influencing factors for the decline in energy intensity are the industrial energy intensity followed by the industrial structure and the energy structure. There are eight industrial sub-sectors that contributed to the decrease in industrial energy intensity. Conversely, there are seven sub-sectors that increased industrial energy intensity. In addition, there are six sub-sectors with an energy intensity of more than 1 ton/10⁴ CNY. The convergence parameters demonstrate that the energy intensities of the five northwestern provinces did not converge to the same steady-state level, and their gap did not narrow in the short term. While the region’s overall energy intensity has shown a consistent downward trajectory, sectors heavily reliant on traditional fossil fuels—such as coal chemical processing, petroleum refining, and coking—have experienced a paradoxical upward trend in energy consumption. To address this, governments must implement targeted sector-specific measures, including upgrading technical capabilities through advanced coal gasification technologies, optimizing heat integration systems in petroleum refining processes, and streamlining intermediate production stages to minimize energy waste. Full article

The global energy sector has been profoundly reshaped by the COVID-19 pandemic, triggering diverse reactions in energy demand patterns, accelerating the transition toward renewable energy sources, and amplifying concerns over global energy security and the digital safety of energy infrastructure. Five years after the pandemic’s onset, this study provides a taxonomy-based lesson-learned analysis, offering a comprehensive examination of the pandemic’s enduring effects on energy systems. It employs a detailed analytical framework to map short-, medium-, and long-term transformations across various energy-related sectors. Specifically, the study investigates significant shifts in the global energy landscape, including the electric and conventional vehicle markets, the upstream energy industry (oil, coal, and natural gas), conventional and renewable energy generation, aerial transportation, and the broader implications for global and continental energy security. Additionally, it highlights the growing importance of cybersecurity in the context of digital evolution and remote operations, which became critical during the pandemic. The study is structured to dissect the initial shock to energy supply and demand, the environmental consequences of reduced fossil fuel consumption, and the subsequent pivot toward sustainable recovery pathways. It also evaluates the strategic actions and policy measures implemented globally, providing a comparative analysis of recovery efforts and the evolving patterns of energy consumption. In the face of a global reduction in energy demand, the analysis reveals both spatial and temporal disparities, underscoring the complexity of the pandemic’s impact on the energy sector. Drawing on the lessons of COVID-19, this work emphasizes the need for flexible, forward-thinking strategies and deeper international collaboration to build energy systems that are both resilient and sustainable in the face of uncertainties. Full article

This article presents an analysis of the relationship between air pollution and the type of fuel used in households in the Małopolskie Voivodeship from 2010 to 2021. For this article, they are marked as HEU-C (coal), HEU-L (liquid), and HEU-O (other). The analysis area was selected due to the constantly occurring problem of air pollution with PM₁₀ and PM_2.5. Using regression, the relationships between energy consumption in households and specific components of air pollution recorded in the Małopolskie region were established. The developed models were used to determine the potential of individual groups of fuels to generate pollution. The primary finding suggests that the derived regression models offer an appropriate predictive framework. Studies show significant reductions in pollutants like BbF, Cd, Pb, and PM_2.5. Increasing the use of HEU-O fuel is key to cleaner air in the Małopolskie Voivodeship. However, HEU-O may emit more NO_x and NO₂ than HEU-C. The selected thematic emphasis differentiates this article from others examining air quality issues within the Małopolskie Voivodeship. Full article

The co-gasification of coal and biomass offers numerous benefits, including improved gasification efficiency, reduced pollution emissions, and the utilization of renewable resources. However, there is a lack of comprehensive research on the synergistic effects of, and influence parameters on, coal–biomass co-gasification. This study employs Aspen Plus simulations to investigate the co-gasification behavior of coal and corn straw, focusing on the synergistic effects and the impact of various operating conditions. A synergistic coefficient is defined to quantify the interactions between the feedstocks. Sensitivity analyses explore the effects of gasification temperature (800–1300 °C), coal rank (lignite, bituminous, anthracite), biomass mass fraction (0–50%), oxygen-to-carbon ratio, and steam-to-carbon ratio on the synergistic coefficients of effective syngas content (CO + H₂), specific oxygen consumption, specific fuel consumption, and cold gas efficiency. The results reveal an optimal biomass mass fraction of 10% for maximizing cold gas efficiency, with the syngas primarily consisting of H₂ (36.8%) and CO (61.6%). Higher gasification temperatures (up to 1200 °C) improve syngas quality and process efficiency, while higher-rank coals exhibit better gasification performance compared to lignite. Optimal oxygen-to-carbon and steam-to-carbon ratios are identified for maximizing syngas yield and quality. These findings provide valuable guidance for the design and optimization of industrial coal–biomass co-gasification processes, enabling the maximization of syngas quality, process efficiency, and resource utilization. Full article

Modern electrical power systems integrate renewable generation, with solar generation being one of the pioneers worldwide. In Latin America, the greatest potential and development of solar generation is found in Chile through the National Electric System. However, its energy matrix faces a crisis of drought and reduction of emissions that limits hydroelectric generation and involves the definitive withdrawal of coal generation. The dispatch of these plants is carried out by the system operator, who uses a simplified mechanism, called “economic merit list” and which does not reflect the real costs of the plants to the damage of the operating and marginal cost of the system. This inefficient dispatch scheme fails to optimize the availability of stored gas and its use over time. Therefore, a real-time redispatch model is proposed that minimizes the operation cost function of the power plants, integrating the variable generation cost as a polynomial function of the net specific fuel consumption, adding gas volume stock restrictions and water reservoirs. In addition, the redispatch model uses an innovative “maximum dispatch power” restriction, which depends on the demand associated with the automatic load disconnection scheme due to low frequency. Finally, by testing real simulation cases, the redispatch model manages to optimize the operation and dispatch costs of power plants, allowing the technical barriers of the market to be broken down with the aim of integrating ancillary services in the short term, using the power reserves in primary (PFC), secondary (SCF), and tertiary (TCF) frequency control. Full article

Aiming at the problem that the energy consumption of the boiler system varies greatly under the flexible peaking requirements of coal-fired units, an energy consumption prediction model for the boiler system is established based on a Least-Squares Support Vector Machine (LSSVM). First, the Mean Impact Value (MIV) algorithm is used to simplify the input characteristics of the model and determine the key operating parameters that affect energy consumption. Secondly, the Snow Ablation Optimizer (SAO) with tent map, adaptive t-distribution, and the opposites learning mechanism is introduced to determine the parameters in the prediction model. On this basis, based on the operation data of an ultra-supercritical coal-fired unit in Xinjiang, China, the boiler energy consumption dataset under variable load is established based on the theory of fuel specific consumption. The proposed prediction model is used to predict and analyze the boiler energy consumption, and a comparison is made with other common prediction methods. The results show that compared with the LSSVM, BP, and ELM prediction models, the average Relative Root Mean Squared Errors (aRRMSE) of the LSSVM model using ISAO are reduced by 2.13%, 18.12%, and 40.3%, respectively. The prediction model established in this paper has good accuracy. It can predict the energy consumption distribution of the boiler system of the ultra-supercritical coal-fired unit under variable load more accurately. Full article

Household energy consumption is influenced by a variety of factors, including climate, demographics, and socio-economic conditions. This study is a review based on clustering analysis of data from the 2019 Household Budget Survey in Turkey, and explores the role of dwelling structure, household habits, and possessions as indicators of energy patterns and preferences within distinct household groups contributing to Sustainable Development Goals 1, 7, and 12. The data analysis identifies three distinct clusters with specific features that set them apart. The Urban Majority cluster represents densely populated urban areas where natural gas is a preferred fuel source, and parquet and ceramic tiles are common flooring materials. The Deprived-like Remote Residents cluster portrays areas with less access to natural gas, where wood and coal are frequently used for heating, and the Urban Comfort-Seekers cluster highlights urban areas with high comfort levels, featuring natural gas, floor heating, and various amenities. These clusters reflect energy consumption patterns and social aspects related to poverty and habits. They indicate that Turkey’s energy preferences are closely linked to accessibility, user-friendliness, and affordability. Urban households prioritize comfort, while rural areas are more resource-constrained, and contextual factors like location and possessions play a vital role in energy preferences. Full article

Supported ozone catalysts usually take alumina, activated carbon, mesoporous molecular sieve, graphene, etc. as the carrier for loading metal oxide via the impregnation method, sol–gel method and precipitation method. In this work, a Mn-modified fly ash catalyst was synthesized to reduce the consumption and high unit price of traditional catalyst carriers like alumina. As a solid waste discharged from coal-fired power plants fueled by coal, fly ash also has porous spherical fine particles with constant surface area and activity, abd is expected to be applied as the main component in the synthesis of ozone catalyst. After the pretreatment process and modification with MnOx, the obtained Mn-modified fly ash exhibited stronger specific surface area and porosity combined with considerable ozone catalytic performance. We used sodium acetate as the contaminant probe, which is difficult to directly decompose with ozone as the end product of ozone oxidation, to evaluate the performance of this Mn-modified fly. It was found that ozone molecules can be transformed to generate ·OH, ·O₂⁻ and ¹O₂ for the further oxidation of sodium acetate. The oxygen vacancy produced via Mn modification plays a crucial role in the adsorption and excitation of ozone. This work demonstrates that fly ash, as an industrial waste, can be synthesized as a potential industrial catalyst with stable physical and chemical properties, a simple preparation method and low costs. Full article

With an increase in energy consumption globally, Fischer-Tropsch (FT) synthesis is a good alternative for producing fuels and chemicals from coal, natural gas or biomass. Among them, coal to liquids has been put into production in countries that have large coal reserves. In this process, Fe-based catalysts are commonly used due to their earth abundance, comparatively wide operation range and ready availability to handle low H₂/CO ratio from coal. Despite their extensive applications, the kinetic and mechanistic understandings of Fe carburization and FT reaction on Fe-carbides are relatively limited due to the complexity of the phase composition of the applied catalysts. This review summarizes the current state of knowledge of FT synthesis on Fe-carbide with an emphasis on the underlying mechanism. Specifically, the employment of a model catalyst, such as Raney Fe, could provide a convenient way to furnish kinetic information regarding Fe carburization and subsequent FT reaction. A major challenge for further understanding catalytic reactions occurring at the Fe-carbide surface is correlating FT activity and selectivity to a specific active site. To address this issue, the advancements of both DFT calculations and surface science techniques are highly demanded. Full article

The brick kiln industry is one of the largest and most highly unregulated industrial sectors in developing countries. Most of the kilns use low-quality coal as primary fuel along with small quantities of bagasse, rice husk, and wooden chips. As a result of inefficient methods of combustion in conventional brick kilns, such as fixed chimney Bull’s trench kilns (FCBTKs), harmful pollutants are emitted in high quantities, which ultimately deteriorate the environment and are widely in operation in Pakistan. The most prominent harmful pollutants include carbon dioxide (CO₂), carbon monoxide (CO), sulphur dioxide (SO₂), black carbon (BC), and particulate matter less than 2.5 microns (PM_2.5). Over the years, new technologies have been adopted by developed countries for the reduction of environmental burdens. One of these technologies is induced draught zigzag kilns (IDZKs), or zigzag kilns (ZZKs), technology, which effectively improves the combustion across the path of bricks stacked in a zigzag pattern. For the mass adoption of this technology, environmental assessment and comparison of both technologies is a crucial step. Both types of kiln sites are investigated for the analysis of their emissions and their environmental impact in this work. Carbon mass balance equations are used for the calculation of emission factors. Collected inventory data is then used for the life cycle assessment of both types of kilns using open LCA (version 1.10.3) and the Eco-invent database. According to the study, ZZK technology outperforms FCBTK in all aspects. The analysis of the specific energy consumption (SEC) of fired bricks for each kiln type reveals that ZZKs require 30% less energy than the conventional FCBTK. This implies that ZZKs demand lesser fuel than FCBTKs. The zigzag technology adoption scenario, in particular, can lead to approximately 30% lower CO₂ emissions, which can be further reduced by up to 80% when taking into account black carbon (BC) emissions. Additionally, the adoption of zigzag technology can result in a 35% decrease in PM_2.5 emissions. The study shows that adopting ZZK technology significantly reduces impact categories, such as particulate matter formation (PMF), photochemical oxidant formation (POF), and terrestrial acidification (TA) by 63%, 93%, and 95%, respectively. Full article