Master of Science (MS), Ohio University, 2024, Civil Engineering (Engineering and Technology)

The goal of this thesis is to compare the current methods to generate pigment from AMD, test the pigments for their chemical and elemental compositions, and determine whether the pigments generated meet ASTM and market standards. The pigments were also evaluated to find their associated color numbers and compared to existing pigments collected from pigment companies. Iron oxide sludge was generated and collected from Truetown, OH by oxidizing and settling AMD. This sludge was tested for quality with the intent of making pigments from dried iron oxide. The sludge was dewatered or washed to represent potential treatment methods, then dried and ground into a fine powder. The powder was tested for iron oxide, sulfates, lead, organic coloring matter, moisture content, and ignition loss using ASTM standard methods. It was tested for its X-ray patterns using X-ray diffraction and for 31 elements using X-ray fluorescence. It was finally tested for its performance as an oil paint and its color spectrophotometry. These experiments were repeated for several examples of pigments from existing industry, including artistry and concrete dyeing. The results of these experiments showed that AMD pigments are generally lower in impurities than artist pigments, but higher than expected in sulfates. They are also amorphous but contain no toxic levels of metals. The experiments consistently showed that pressing was more effective than washing for removing impurities. The AMD pigments were also determined to be a different color than any of the collected pigments on the market, and would need to be identified as its own, separate color. Based on these conclusions and its derivation from AMD, it is suspected to be the iron oxide mineral known as Shwertmannite.

Committee: Guy Riefler (Advisor); John Sabraw (Committee Member); Lei Wu (Committee Member); Daniel Che (Committee Member) Subjects: Art Education; Chemical Engineering; Chemistry; Civil Engineering; Environmental Engineering; Environmental Science; Environmental Studies

Master of Science (MS), Ohio University, 2007, Environmental Studies (Arts and Sciences)

Forests are preferred as a post-mining land use in the eastern United States. In Ohio, early reforestation included Pinus spp. monocultures which may not conserve the flora and fauna of historic hardwood communities. American Chestnut, Castanea dentata (Marsh.) Borkh., is an historic keystone species of eastern deciduous forests. We evaluated the growth and survival of 1-year-old Castanea dentata seedlings in field and garden conditions representing mine spoil from previously strip mined lands in eastern Ohio. Pure and hybrid bareroot seedlings were grown at three selected field sites ranging in mean pH from 3.6 to 7.7. Hybrid seedlings were inoculated with the mycelium Pisolithus tinctorius (Pers.) Coker and Couch, (‘Pt'). Soil was analyzed for Al, Mn, Fe, and S, as well as base nutrients and other edaphic qualities. A garden experiment supplemented field analysis with a controlled mycorrhizae x pH x nutrient interaction. Field growth variables were measured for 2005 and 2006. Garden seedlings were harvested and biomass allocation was measured for 2006. Field parameters were significantly (P < 0.05) accelerated by Pt inoculation, except for height. Pure non-inoculated seedlings displayed tall slender stems, while hybrid inoculated seedlings showed bushier growth with greater stem diameter, and lower branching. Field sites displayed significant (P < 0.05) differences, with overall seedling performance being best on bare, un-reclaimed spoil, compared to grass or forb cover. This may be consistent, based on prior studies, with historic disturbance regimes. Growth was lowest in association with herb cover, suggesting that aggressive grasses and legumes such as those used in modern reclamation practices, may inhibit establishment of seedlings early-on. Garden controls revealed that in contrast to prior studies of container grown Fagaceae, chestnut growth was not positively influenced, and showed ca. 70% mortality from addition of controlled release fertilizer (CRF) into (open full item for complete abstract)

Committee: Brian McCarthy (Advisor) Subjects:

Master of Science, The Ohio State University, 2024, Food, Agricultural and Biological Engineering

Waste coal in abandoned mine lands poses significant environmental challenges, affecting nearby communities, rivers, and streams. Effective management of these piles is essential due to concerns such as acid mine drainage, soil and water contamination, coal fires, and methane emissions. Various strategies have been proposed for managing waste coal, including potential utilization for rare earth element recovery, soil amendment, construction aggregates, and energy generation. However, the implementation of these strategies remains uncertain due to the lack of precise location and volume data on waste coal piles. Traditional methods for gathering these data rely on field visits and Global Navigation Satellite System surveying, which are costly and labor-intensive. Advances in satellite technologies and the availability of digital elevation models (DEMs) offer an opportunity to estimate waste coal volume on a regional scale in a timely and cost-effective manner. Thus, the objective of this thesis was to develop a robust data analytical framework to locate and estimate the volume of waste coal piles on a regional scale, using the Muskingum River Basin (MRB) in Ohio as the study area. Initially, a prototype was developed to determine the most effective machine learning (ML) model to map waste coal piles in a historical coal mine site within the MRB. While all four ML models effectively identified dominant classes such as Grassland and Forest, the Random Forest (RF) model demonstrated superior performance in classifying the more complex waste coal class, with a precision of 86.15% and recall of 76.71%. Subsequently, the greatest disturbance and reclamation mapping of these waste coal piles were conducted using the LandTrendr algorithm to distinguish waste coal piles in abandoned mine lands from those in active mining areas. Moreover, this study utilized publicly available elevation models to estimate waste coal volume in the MRB. However, since historical terrain mo (open full item for complete abstract)

Committee: Ajay Shah (Advisor); Sami Khanal (Advisor); Tarunjit Singh Butalia (Committee Member) Subjects: Artificial Intelligence; Engineering; Geographic Information Science; Remote Sensing; Sustainability