Steam Coal Research Articles

Unveiling the political economy of fossil fuel extractivism in Colombia: Tracing the processes of phase-in, entrenchment, and lock-in

To increase the ambition and effectiveness of a global coal phase-out, it is central to understand how one extraction regime – fossil fuel extractivism (FE) — was phased in. Doing so may make it possible to confront the actors dependent on and strengthened by the associated natural resource rents. Characterized by the large-scale, high-impact, export-oriented extraction of fossil fuels such as steam coal, the present paper traces the processes that led first to the phase-in and then to the entrenchment of FE in Colombia. Taking the case of large-scale coal extraction (LSCE) as an example, the paper analyzes the causal mechanisms allowing this activity to take deep roots in politics, society and the economy, with grave implications for the environment and culture of affected communities and the country as a whole. Drawing on different data sources (20 stakeholder interviews, policy and press documents, scholarly research, etc.), the paper adapted Palley’s (2017) notion of policy lock-in and lock-out via hysteresis to propose an entrenchment spiral as a potential mechanism leading to the current degree of coal and fossil fuel extraction entrenchment in Colombia. The paper concludes that the phase-in of LSCE and FE was facilitated by the combination of masking and securitization strategies used by an incumbency regime closely associated with state capture. As power dynamics shifted, asymmetric dependency relationships between mining companies and affected individuals, communities and governments at local, regional and national levels were gradually generated, leading to this sector’s seemingly inexpugnable position. That said, knowledge is power. Knowing how phase-in and entrenchment occurred and still happens can be an initial step towards confronting and even reversing it.

Distributional Predictability and Extreme Spillovers of Clean Energy, Steam Coal and Technology: Evidence from a Quantile-Based Analysis

Distributional Predictability and Extreme Spillovers of Clean Energy, Steam Coal and Technology: Evidence from a Quantile-Based Analysis

Justification of the Reduction Possibility of Sulfur Oxides and Fly Ash Emissions during Co-Combustion of Coal and Waste from Woodworking Enterprises

In this work, we experimentally investigated the effect of widespread biomass (woodworking waste—pine sawdust) in the composition of mixed fuel, formed also using the widespread steam coals metalignitous (D) and lean (T), on the concentration of sulfur, nitrogen and carbon oxides in flue gases. Investigations of composite fuels with a mass of at least 5 g were carried out in a reactor with continuous recording of the composition of the flue gases formed during the thermal decomposition of the investigated fuels. Thermal decomposition of fuels was carried out in the temperature range from 293 K to 873 K. It was found that an increase in the proportion of wood components in mixed fuels based on two different coals from 10% to 50% leads to a significant decrease in the concentration of sulfur oxides from 11% to 95.8% relative to the concentration of the formation of sulfur oxides in a homogeneous coal, respectively. It was found that an increase in the proportion of the wood component in the mixture with grade D coal up to 50% leads to a significant increase in the content of calcium sulfates (45.1%) and aluminum (43.2%) in the blended fuel. The increase in the content of these salts in the ash of mixed fuels based on T coal and wood is 35.1% and 38.6%, respectively. The obtained research results allowed us to conclude that woodworking wastes are an effective addition to the coals of various deposits, which would help to reduce anthropogenic-induced gas emissions when they are co-combusting in the furnaces of power boilers.

Performance and boiler efficiency using low-grade coal on 400 MWe coal-fired power plant: case study of Suralaya Power Plant Unit 2

In a coal steam power plant, changes in coal quality significantly affect plant performance, especially in its boiler. A coal-fired power plant with a capacity of 400 MWe had been commissioned using coal with a calorific value of 5,242 kCal/kg. This study aims to determine the effect on unit performance and boiler efficiency due to changes in fuel use with the typical calorific value of 3,520 kCal/kg, 34,17% lower than the initial design. The performance tests were conducted using the heat loss method at loads: 50%, 65%, 75%, and 100%. The test result showed that using low-grade coal reduces boiler efficiency by 6.26%. There were four dominant boiler losses: heat loss due to moisture in dry flue gas, heat loss due to combustible in refuse, heat loss due to moisture in fuel, and heat loss due to hydrogen burning. Furthermore, the gross plant heat rate using low-grade coal was increased from 2,120 kCal/kWh to 2,718 kCal/kWh; however, the electric price becomes cheaper from 1.99 cent-USD/kWh becomes 1.31 cent-USD/kWh.

Forecasting of Steam Coal Price Based on Robust Regularized Kernel Regression and Empirical Mode Decomposition

Aiming at the problem of difficulties in modeling the nonlinear relation in the steam coal dataset, this article proposes a forecasting method for the price of steam coal based on robust regularized kernel regression and empirical mode decomposition. By selecting the polynomial kernel function, the robust loss function and L2 regular term to construct a robust regularized kernel regression model are used. The polynomial kernel function does not depend on the kernel parameters and can mine the global rules in the dataset so that improves the forecasting stability of the kernel model. This method maps the features to the high-dimensional space by using the polynomial kernel function to transform the nonlinear law in the original feature space into linear law in the high-dimensional space and helps learn the linear law in the high-dimensional feature space by using the linear model. The Huber loss function is selected to reduce the influence of abnormal noise in the dataset on the model performance, and the L2 regular term is used to reduce the risk of model overfitting. We use the combined model based on empirical mode decomposition (EMD) and auto regressive integrated moving average (ARIMA) model to compensate for the error of robust regularized kernel regression model, thus making up for the limitations of the single forecasting model. Finally, we use the steam coal dataset to verify the proposed model and such model has an optimal evaluation index value compared to other contrast models after the model performance is evaluated as per the evaluation index such as RMSE, MAE, and mean absolute percentage error.

Possibilities of Practical Use of Historical Distributions of Ash, Sulfur and Mercury Contents in Commercial Steam Coal of the USCB.

In the process of extracting hard coal, extensive databases are created on its quality parameters. A statistical assessment was made of the ash, sulfur, and mercury content of commercial coals produced in the Upper Silesian Coal Basin (USCB). The statistical methods applied: non-parametric tests of compatibility for two populations, parametric significance tests, and non-parametric tests of compatibility for the three populations, showed that the distributions of ash and sulfur content in 2014 and 2015 are comparable and the average values are similar. Statistical tests indicated significant differences in the mercury content distributions and their variances. This demonstrates the need for ongoing monitoring of mercury content in commercial coals, as a prediction of mercury content from historical data is hardly possible.

The future of coal investment, trade, and stranded assets

The future of coal investment, trade, and stranded assets

Geochemistry and Industrial Applications of Brown Coals of the Ogwashi-Asaba Formation in Parts of Anambra State, Nigeria

Geochemical studies have been carried out on brown coal of the Ogwashi-Asaba Formation in parts of Anambra State, Nigeria, using proximate and ultimate analytical results to evaluate its potentials for industrial utilization. An understanding of the physico-chemical characteristics such as moisture content , volatile matter content, fixed carbon content, and ash content are essential for establishing the quality of the coal. The chemical analysis of the brown coal samples results suggest that fixed carbon varies from 1.51 to 37.50 wt%, moisture content varies from 2.40 to 39.80 wt%, volatile matter varies from 2.44 to 39.92 wt%, and ash content ranges from 6.60 to 70.75 wt%, carbon content ranges from 11.59 wt% to 59.33 wt%, oxygen content ranges from 0.06 to 13.87 wt%, hydrogen content ranges from 0.13 to 4.59 wt%, sulfur content varies from 0.04 to 2.48 wt% and the nitrogen content varies from 1.30% to 1.85 wt%. The high-moisture content poses several challenges for the utilization of lignite, because it lowers the energy density of the fuel and makes its transportation uneconomic over long distances. The analytical results show that the coal cannot be employed in the steel industry for the generation of substantial heat for the working of the furnace but can be used as a steam coal. Proximate analysis and calorific data suggest that the coal belongs to the lowest rank i.e. lignite. The brown coal is less hazardous to the ecosystem because of its significantly low sulfur and nitrogen contents. Based on the results of the study, the brown coal can be used for power generation, gasification, production of industrial chemicals and cement production. Keywords: Coal, Proximate Analysis, Ultimate Analysis, Calorific values DOI: 10.7176/JNSR/12-12-03 Publication date: June 30 th 2021

Bituminous Coal Char-Derived Hard Carbon As a Low-Cost Anode Material for Sodium-Ion Batteries

Increasing demands in the global energy markets for large-scale electric energy storage systems have made it essential to improve current rechargeable battery technologies. Due to the high price and low safety of current commercial lithium-ion batteries, as well as potential resource limitations of lithium, there is a need to explore alternative ion intercalation battery technologies [1]. Sodium-ion batteries (SIBs), having a theoretical energy density comparable with lithium-ion, are a promising next-generation energy storage technology to replace lithium-ion batteries in large-scale, stationary energy storage applications. A current challenge in achieving high performance SIBs is improving capacity and reducing cost of anode materials. While carbons derived from coal tar pitch have been widely studied as intercalation materials, hard carbons derived from coal char (the solid component of bituminous and sub-bituminous coals) are only recently gaining attention as SIB anode materials with surprisingly high sodium storage capacity, good rate performance, and long cycle life [2]. Bituminous coal char is used primarily as a fuel source for power production, making it an extremely low-cost electrode material. The high mineral ash content of with bituminous coal char, however, is a significant challenge to achieving high anode capacities with this material.This work investigates the effect of pyrolysis conditions and deashing parameters on the material properties and sodium-ion intercalation capacity of hard carbons derived from bituminous, SUFCO mine coal char. SUFCO coal, known as steam coal, is a local Utah coal used for power generation. Pyrolysis temperature and atmosphere, as well as acid/base washing conditions, are varied to produce anode materials with varying carbon structure and ash content. Deashing conditions explored in this work include treating raw coal char with various basic and dilute acid (10%) solutions, as well as a high concentration mixture of H2SO4:HNO3 (30:70), at different temperatures (22°C and 80 °C) and for varying times. The structure and composition of the resulting carbons are characterized via scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and pore-size distribution measurements. Electrochemical behavior is investigated by assembling coin cells (half-cells using Na metal and NaClO4 electrolyte), in a nitrogen glove box (LC Technology Solutions Inc, <0.1 ppm H2O, <0.1 ppm O2) using an MTI CR20XX coin cell press. All coin cell testing is performed using a Gamry Interface 1000E potentiostat and a Gamry four-terminal coin cell holder. The results provide insight into process-structure-performance relationships for coal char-derived hard carbons as SIB anode materials, including charge-discharge capacity, cycle life, rate performance, and electrochemical impedance.This work is supported in-part by NSF Award #1742696.[1] P. Bai, Y. He, X. Zou, X. Zhao, P. Xiong, Y. Xu, Elucidation of the Sodium-Storage Mechanism in Hard Carbons, Adv. Energy Mater. 8 (2018) 1–9.[2] Yunming Li, Yong-Sheng Hu, Xingguo Qi, Xiaohui Rong, Hong Li, Xuejie Huang, Liquan Chen, Advanced sodium-ion batteries using superior low cost pyrolyzed anthracite anode: towards practical applications, Energy Storage Materials 5 (2016) 191–197. Figure 1

Selective Crushing of Run-of-Mine as an Important Part of the Hard Coal Beneficiation Process

To obtain commercial product of required quantitative and qualitative parameters, hard coal must be subjected to a number of processing operations. Preliminary stone removal from run-of-mine is one of them. Methods of such removal, including the method of selective crushing are described. Design solutions for a KOMAG-type device for dry stone removal of run-of-mine are presented. The results of laboratory tests for selective crushing susceptibility of steam coal and coke are presented, and a comparative analysis of the tested types of coal is made. Possibilities of increasing the production of commercial products by using a Bradford drum crusher is analyzed from the economical point of view.

Forecasting European thermal coal spot prices

This paper presents a one-year forecast of European thermal coal spot prices by means of time series analysis, using data from IHS McCloskey NW Europe Steam Coal marker (MCIS). The main purpose was to achieve a good fit for the data using a quick and feasible method and to establish the transformations that better suit this marker, together with an affordable way for its validation. Time series models were selected because the data showed an autocorrelation systematic pattern and also because the number of variables that influence European coal prices is very large, so forecasting coal prices as a dependent variable makes necessary to previously forecast the explanatory variables. A second-order Autoregressive process AR(2) was selected based on the autocorrelation and the partial autocorrelation function. In order to determine if the results obtained are a good fit for the data, the possible drivers that move the European thermal coal spot prices were taken into account, establishing a hypothesis in which they were divided into four categories: (1) energy side drivers, that directly relates coal prices with other energy commodities like oil and natural gas; (2) demand side drivers, that relates coal prices both with the Western World economy and with emerging economies like China, in connection with the demand for electricity in these economies; (3) commodity currency drivers, that have an influence for holders of different commodity currencies in countries that export or import coal; and (4) supply side drivers, involving the production costs, transportation, etc. Finally, in order to analyse the time series model performance a Generalized Regression Neural Network (GRNN) was used and its performance compared against the whole AR(2) process. Empirical results obtained confirmed that there is no statistically significant difference between both methods. The GRNN analysis also allowed pointing out the main drivers that move the European Thermal Coal Spot prices: crude oil, USD/CNY change and supply side drivers.

The death valley of coal – Modelling COVID-19 recovery scenarios for steam coal markets

This paper examines medium and long-term perspectives for global steam coal production and trade, considering the potential impacts of the COVID-19 pandemic and plausible recovery scenarios in its aftermath. We use an interdisciplinary approach to develop a range of stylized global coal demand scenarios until 2040 depicting the influence of the COVID-19 pandemic and resulting recovery stimuli. Additional insights are gained by adjusting trade restrictions of key countries within the coal sector model COALMOD-World to resemble plausible post-COVID-19 policy and market dynamics. Results indicate that the COVID-19 pandemic might cause an “L” or “\\” shape instead of the hoped for “V” or “U” shaped recovery of the coal industry. Regional effects vary, as the Atlantic market dries out first, causing shifts in trade patterns in the Pacific market. Moreover, announced trade restrictions could change dramatically the composition of the international steam coal trade. However, even significantly reduced coal consumption levels in low-coal post-COVID-19 scenarios would still be too high to comply with the global climate targets. This emphasizes the importance of concentrated policy efforts in the pandemic aftermath to manage a coal decline consistent with global climate targets while bringing just transitions efforts substantially forward, in particular in vulnerable coal-dependent countries and regions.

An ANN-based method for predicting Zhundong and other Chinese coal slagging potential

Conventional ash-component-based slagging indices and ash fusion temperatures (AFTs) successfully predict the slagging behavior of steam coals. However, these methods fail to tell the ZDc slagging potential accurately. In this paper, a back propagation artificial neural network (BP-ANN) is proposed to predict the slagging potential for both ZDc and other steam coals. Python is used for the training, verification and test of the BP-ANN. In training and verification, 12 ZDc, 2 lignite, 3 blend coal samples are analyzed and other 63 coals are collected as data. The result shows that the accuracy rate of the network based on ash components is 62.5%, close to the value of conventional slagging indices. It can only predict the slagging potential of certain coals. In contrast, modifying the network with coal properties can greatly increase the accuracy rate to 87.5%. The verification results of 14 samples are completely consistent with the actual slagging behavior, and that of 2 samples shows the slagging tendency. After that, 30 samples are collected from other papers for test. The results of 25 samples are completely consistent with the actual slagging behavior and that of 3 samples shows the slagging tendency, only 2 samples telling the wrong results.

Proposal and energy saving analysis of novel methanol–electricity polygeneration system based on staged coal gasification method

The coal gasification process is one of the main exergy destruction contributors in polygeneration systems and has considerable energy saving potential. In the present study, for improving the performance of the polygeneration system, the coal-steam gasification method was employed to integrate a novel methanol-electricity polygeneration system. The results indicated that the energy efficiency of the novel system was 63.3% with a chemical-to-power output ratio of 8.4, while the energy efficiency of the traditional system is 51.3% at the optimal unreacted syngas recycling ratio. Exergy analysis results revealed that the system exergy destruction in the coal–steam gasification process is 7.5% smaller than that in the GE gasification process, and eliminating the air separation unit can reduce the exergy destruction of the system by 4.3%. Additionally, the energy saving contributions of gasification process improvement and system integration were quantitatively evaluated. When the chemical-to-power output ratio increased from 1.9 to 11.9, the energy saving contributions of the system integration and gasification process improvement ranged from 9.8% to 15.1% and 11.9% to 12.9%, respectively.

Experimental study of the processes of reducing the formation of sulfur oxides during the co-combustion of particles of metalignitous coal and wood processing waste

This paper presents results of experimental research on thermal decomposition processes of a rather common D grade steam coal (metalignitous coal) and wood. The research aims to substantiate the previously formulated hypothesis on the mechanism of sulfur oxide sequestration in the combustion products of such mixtures. The elemental composition of the reference coal and wood biomass (pine sawdust) and the ash remaining after complete thermal decomposition of the studied mixtures was analyzed. The obtained results, along with results of the X-ray phase analysis of the ash composition, showed an increase in the proportion of calcium and aluminum sulfates in solid pyrolysis products. The performed experiments substantiate that the use wood as an additive for mixed metalignitous coal fuels reduces sulfur oxide yield during their combustion in power boilers in large-scale and small-scale power generation systems. It was established that pyrolysis of two-component fuels based on the D grade coal mixed with dispersed wood biomass contributes to reducing sulfur oxide concentration in gaseous products of their thermal decomposition. This effect can be attributed to formation of calcium and aluminum sulfates in the mixed fuel ash. They are formed as a result of reactions between the coal and wood pyrolysis products that occur if the content of wood components in the mixture is from 10% to 50%.

Price elasticity of demand for fuels by income level in Mexican households

The price elasticities demand of electricity, gas, oil fuel, gasoline and steam coal are estimated using household surveys from 1992 to 2014. The analysis uses alternative econometric techniques – OLS, SURE, and Quadratic Almost Ideal Demand System (QUAIDS) – the last of which is based on the methodology of Banks, Blundell and Lewbel considering socioeconomic characteristics of the households to account for the difference in demand of energy related goods. It is found that the demands for fuels are price inelastic, and the differences in elasticities between poor and non-poor households are small but statically significant. The income elasticity of demand is generally found to be positive and higher in absolute value than price elasticity, and the differences are greater between poor and non-poor. Consequently, there would be a differentiated reaction of consumers to changes in energy prices according to their poverty status. Steam coal and firewood, each of which could be considered inferior goods, stand as counterexamples in that the income elasticity is found to be negative. The contribution of this study helps policy makers to analyze household welfare when applying changes in energy prices in the face of fiscal and/or energy reforms, such as those Mexico is implementing.

Predicting changes in the sulfur content during steam coal preparation and the level of sulfur dioxide emissions when its combustion

Purpose. Development of a method and forecast estimation of sulfur dioxide emission reduction during combustion of steam coal by regulating its quality during coal preparation. Methodology. Study on sulfur content in coal using sieve, fractional analysis, analysis of ash and total sulfur content. Forecasting of sulfur content in concentrate according to the developed calculation method. Production tests at the coal preparation plant. Forecasting of the level of SO2 emissions during pulverized coal combustion according to the developed calculation method. Findings. The distribution of sulfur content of Ukrainian steam bituminous coal by size classes depending on ash content is investigated; the proximity of sulfur content to the linear dependance on the ash content of the run-of-mine coal, rock-free substance, rock and concentrate is proved. The calculations of the level of SO2 emissions during pulverized combustion of coal and its cleaned products taking into account their elemental composition is performed, and the linear dependence of the level of SO2 emissions on the total sulfur content to lower heating value (LHV) ratio is proved. Based on the obtained results, methods are developed for determining the expected sulfur content in the concentrate and the forecasted level of SO2 emissions during its combustion; the optimal depth of preparation for the coal from various mines is determined by the criterion of compliance of the SO2 emission level with the current environmental standards. Originality. Proximity of the sulfur content to the linear dependence on the ash content of the run-of-mine coal, rock-free substance, rock and concentrate is proved. The linear dependence of the level of SO2 emissions on the ratio of the total sulfur content to LHV during pulverized combustion of coal and its clean products is proved. Practical value. A method has been developed for determining the expected sulfur content in the products of coal preparation by jigging, taking into account the allowable content of the high-density fraction in the concentrate and adding dense slimes to the coal preparation products. A method has been developed for determining the predicted level of SO2 emissions during their combustion. The optimal depth of the coal preparation for coal from various mines has been determined by the criterion of compliance of the level of SO2 emissions with the current environmental standards.

Inland Hard Coal Transportation Costs in the European Union—A Model Based Approach

Although some EU countries have already ceased coal-fired electricity generation, coal will still be a relevant topic within the European electricity mix in the medium term. A hard coal power plant competes in the merit order mainly with other hard coal power plants and also with gas power plants. One of the main cost drivers of fuel supply is the transport costs of steam coal from import harbors to the power plant sites. These costs consist either of freight rates of the barges, charges for transport by train, or a combination of both, and additional transshipment costs that arise during transport. The resulting costs differ considerably depending on the country and the region within a country. This work aims at determining country-specific regional transport costs for hard coal to power plant sites in the European Union. The geographical resolution for this work is at the municipal level of each country, in which each municipality is characterized by specific costs, depending on distance and means of transport. In total, transport costs are modelled for 119,978 municipalities. The results show a clear ranking of preferred locations with regard to transport costs, starting with locations close to the open sea followed by inland locations near riverbanks. Locations remote from both sea and waterway access are the most expensive sites. The resulting data basis can be used as an input for energy system models.

Application of screening using a flip-flow screen and shallow groove dense-medium separation in a steam coal preparation plant

ABSTRACT Low-rank steam coal is an important coal resource, but has high water and ash content, which needs to be separated to improve its quality and calorific value. In this paper, the process of screening using a flip-flow screen and density separator using a shallow groove dense-medium separator for steam coal was proposed and applied to the Lijiahao coal preparation plant. Kinematics of the screen box and the surface of the flip-flow screen were investigated using an acceleration and laser displacement measurement and analysis system. The mechanism of the flip-flow screen to overcome aperture blocking and to enhance the screening performance for moist and fine coal was discussed. The results from an industrial experiment when screening at 3 mm showed that the screening efficiency was 82.51%, while the total misplaced materials were 5.91%. The commercial separation of a wide size range of coal using a shallow groove dense-medium separator was analyzed. The results showed that the system exhibited satisfactory separation performance for 100–3 mm coal, whereas the corresponding Ep value was found to be 0.06 g/cm3. Compared with the 6 mm separation system, the yield of clean coal increased by 8.50%, which remarkably increased the economic benefits for the company.

Understanding effect of phosphorus-based additive on ash deposition characteristics during high-sodium and high-calcium Zhundong coal combustion in drop-tube furnace

Zhundong coal as a high quality steam coal has not been widely utilized due to severe fouling and slagging problems during combustion. To promote clean utilization of Zhundong coal, combustion experiments of Zhundong coal were carried out in the drop tube furnace (DTF). The influence of novel phosphorus-based additive on ash deposition characteristics of Zhundong coal was studied. The appearance and phase composition of the raw coal and mixed coal ash deposits at different flue gas temperatures were researched respectively. The new prediction index of slagging tendency containing phosphorus was proposed, and the balance calculation were performed by FactSage thermodynamic software in different flue gas temperatures, including experimental temperatures selected. The results showed that the values of new indexes for predicting slagging tendency had obvious changes, and the phosphorus-based additive had a significant effect on the ash deposition behavior during the combustion process of Zhundong coal in DTF. Compared with the raw coal, the mixed coal with additive had higher ash fusion points and were in the form of loose, crisp, and porous powder, which was beneficial for soot blowing. When the flue gas temperature was 1000 °C or 1150 °C, there was much phosphate complex salt as the skeleton in the ash deposits of the mixed coal, such as Na2CaMg7(PO4)6. Phosphate captured Na and Ca, and effectively inhibited the low temperature eutectic mixtures of Ca with Si and Al, indicating that phosphorus-based additive had good effect on improving ash deposition characteristics of Zhundong coal.