Geology topics

Agnieszka Drobniak

Publications and source records attributed to Agnieszka Drobniak.

5 recordsLinked to original sources

USGS2025

Component identification of solid biomass fuels using reflected light microscopy: Interlaboratory study 2

As nations transition toward sustainable energy systems , biomass has become a vital component of global energy portfolios. Derived from organic materials such as wood, agricultural residues, forestry byproducts, and organic waste, biomass is a renewable energy source with significant environmental and economic benefits. Responsible biomass energy production can improve waste management, reduce emissions of greenhouse gases, and mitigate environmental pollution. However, as the diversity of biomass-derived fuels increases, robust quality assessment methods are essential to ensure their efficiency, safety, and minimal environmental impact. Reflected light microscopy (RLM) is one such technique with the potential to complement conventional physico-chemical analyses by enabling a rapid identification of material constituents and impurities. To refine this methodology and evaluate the reproducibility of solid biomass component identification using RLM, an interlaboratory study (ILS) was conducted. The study involved the recognition of 58 components across 45 photomicrographs, with the participation of 65 scientists and students from 25 countries. The participants faced high difficulty identifying some of the marked components, and as a result, the percentage of correct answers ranged from 19.0 % to 98.3 %, with an average correct identification rate of 62.7 %. The most challenging aspects of the identification process included distinguishing between woody and non-woody (agro) biomass, accurately identifying petroleum-derived materials, and differentiating agro biomass from inorganic matter. The results suggest that while RLM is an important tool for characterizing solid biomass, further development of methodology guidelines and training are necessary to enhance its effectiveness. Future research should prioritize preparing detailed, image-rich, microscopic morphological descriptions of biomass fuel components, which could improve the accuracy and reliability of using RLM in biomass fuel characterization.

International Journal of Coal Geology↗

USGS2024

Atlas of microscopic images of biochar using reflected light microscopy in biochar characterization

Derived through the thermochemical conversion of biomass, biochar is a carbon-rich substance recognized for its significance in environmental applications and sustainable agriculture. As interest in its utilization continues to rise, it becomes crucial to comprehend how the source material and pyrolysis parameters influence the properties of biochar and, consequently, to research the suitability of various analytical methods for characterizing it. Despite the current utilization of numerous physical and chemical methods, the untapped potential of reflected light microscopy warrants further exploration. While a few recent studies suggest a correlation between certain microscopic characteristics and selected physical and chemical properties of biochar, the data are limited and difficult to compare. This is primarily due to variations in the types of original biomass used and lack of information about pyrolysis conditions. Moreover, because only a limited number of photographs taken under a reflected light microscope are publicly available to-date, it is difficult to evaluate morphological differences between various biochars and other organic materials such as inertinites from coal, charcoal, etc. To address limited availability of publicly available data, this “Atlas of Microscopic Images of Biochar” presents a collection of more than 300 images contributed by researchers from Poland, the United States, Canada, Australia, Brazil, and Denmark. These photomicrographs capture optical characteristics of a diverse array of biochar, demonstrating its unique morphological and structural features. This visual documentation can serve as a valuable resource for researchers, industry professionals, educators, and enthusiasts interested in investigating the complexities of biochar forms.

Indiana Journal of Earth Sciences↗

USGS2023

Interlaboratory study: Testing reproducibility of solid biofuels component identification using reflected light microscopy

Considering global market trends and concerns about climate change and sustainability, increased biomass use for energy is expected to continue. As more diverse materials are being utilized to manufacture solid biomass fuels, it is critical to implement quality assessment methods to analyze these fuels thoroughly. One such method is reflected light microscopy (RLM), which has the potential to complement and enhance current standard testing, leading to improving fuel quality assessment and, ultimately, preventing avoidable air pollution. An interlaboratory study (ILS) was conducted to test the reproducibility of biomass fuels component identification using a reflected light microscopy technique. The exercise was conducted on thirty photomicrographs showing biomass and various undesired components (like plastics or mineral matter), which were purposely added (by the ILS organizers) to contaminate wood pellets and charcoal-based grilling fuels. Forty-six participants had various levels of difficulty identifying the marked components, and as a result, the percentage of correct answers ranged from 52.2 to 94.4%. Among the most difficult components to distinguish were petroleum products and inorganic matter. Various reasons led to the misidentification, including insufficient morphological descriptions of the components provided to participants, ambiguities of the nomenclature, limitations of the analytical and exercise method, and insufficient experience of the participants. Overall, the results indicate that RLM has the potential to enhance the quality assessment of biomass fuels. However, they also demonstrate that the petrographic classification used in this exercise requires further refinement before it can be standardized. While a new simplified classification of solid biomass fuels components was created as an outcome of this study, future research is necessary to refine the nomenclature, develop a microscopic morphological description of the components, and verify the accuracy of component identification with a follow-up ILS.

International Journal of Coal Geology↗

USGS2022

Machine learning and data augmentation approach for identification of rare earth element potential in Indiana Coals, USA

Rare earth elements and yttrium (REYs) are critical elements and valuable commodities due to their limited availability and high demand in a wide range of applications and especially in high-technology products. The increased demand and geopolitical pressures motivate the search for alternative sources of REYs, and coal, coal waste, and coal ash are considered as new sources for these critical elements. This research evaluates the REY potential of coals from Indiana (USA). However, although coal data revealed REY potential, it suffered from sparse samples with complete REY measurements. Therefore, we explore the applicability of machine learning (ML) models and data augmentation techniques to demonstrate their applicability to evaluate REY potential in Indiana, and other areas in coal basins, using selected coal parameters (Al2O3, Fe2O3, C, Ash, S, P, Mo, Zn, and As contents) as covariates (indicators). Due to the relatively small sample size with complete REY data in the Indiana Coal Database, two data augmentation techniques (Random Over-Sampling Examples and Synthetic Minority Over-Sampling Technique) were used. Four machine learning algorithms (linear discriminate analysis, support vector machine, random forest, and artificial neural networks) were applied for modeling REY potential as a classification problem. The results show that application of Synthetic Minority Over-Sampling Technique prior to development of the support vector machine (SVM) models generated the best REY classification with an accuracy of 95%. The encouraging results based on Indiana coal data may suggest that a similar approach can be used for other coal basins for screening the locations with REY potential. Those locations then can be targeted for more detailed geochemical surveys to identify most promising areas and evaluate overall REY resources.

Indiana↗

USGS2021

Geochemical data for Illinois Basin coal samples, 2015–2018

Researchers at the U.S. Geological Survey (USGS) and their collaborators conducted a study of the geochemical properties of coals currently produced for electric power generation in the Illinois Basin in Illinois and Indiana. The study follows from recommendations by an expert panel for the USGS to investigate the distribution and controls of trace constituents such as mercury (Hg) in Illinois Basin coals and the behavior of these constituents in coal preparation. A total of 72 new samples were collected by USGS collaborators between 2015 and 2017. These samples include raw coals, prepared coals, and waste coals from coal preparation. To understand the geochemistry and cleaning behavior of these coals, these samples were subjected to an integrated series of analyses described here, including microanalysis of coal constituents and bulk sample chemical analysis. Of the procedures used, whole-sample Hg analysis quantified overall mercury contents and its reduction by coal preparation. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) of pyrite in coal quantified Hg and other potentially harmful elements contained in pyrite, the most likely host of these constituents. Trace elements investigated include those whose emissions are regulated under the U.S. Environmental Protection Agency Mercury and Air Toxics Standards. This report and the corresponding data release, serve as an archive for geochemical data obtained in our study of the geochemistry of Illinois Basin coals. Material included in this report also define approaches used by the USGS over the period of study to characterize coal samples, requiring combined use of results from USGS and non-USGS laboratories.

Illinois↗