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Browsing by Author "Ross, Matthew R. V., committee member"

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    Advances in Bayesian spatial statistics for ecology and environmental science
    (Colorado State University. Libraries, 2024) Wright, Wilson J., author; Hooten, Mevin B., advisor; Cooley, Daniel S., advisor; Keller, Kayleigh P., committee member; Kaplan, Andee, committee member; Ross, Matthew R. V., committee member
    In this dissertation, I develop new Bayesian methods for analyzing spatial data from applications in ecology and environmental science. In particular, I focus on methods for mechanistic spatial models and binary spatial processes. I first consider the distribution of heavy metal pollution from a mining road in Cape Krusenstern, Alaska, USA. I develop a mechanistic spatial model that uses the physical process of atmospheric dispersion to characterize the spatial structure in these data. This approach directly incorporates scientific knowledge about how pollutants spread and provides inferences about this process. To assess how the heavy metal pollution impacts the vegetation community in Cape Krusenstern, I also develop a new model that represents plant cover for multiple species using clipped Gaussian processes. This approach is applicable to multiscale and multivariate binary processes that are observed at point locations — including multispecies plant cover data collected using the point intercept method. By directly analyzing the point-level data, instead of aggregating observations to the plot-level, this model allows for inferences about both large-scale and small-scale spatial dependence in plant cover. Additionally, it also incorporates dependence among different species at the small spatial scale. The third model I develop is motivated by ecological studies of wildlife occupancy. Similar to plant cover, species occurrence can be modeled as a binary spatial process. However, occupancy data are inherently measured at areal survey units. I develop a continuous-space occupancy model that accounts for the change of spatial support between the occurrence process and the observed data. All of these models are implemented using Bayesian methods and I present computationally efficient methods for fitting them. This includes a new surrogate data slice sampler for implementing models with latent nearest neighbor Gaussian processes.
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    Conservative solute transport processes and associated transient storage mechanisms: a comparison of streams with contrasting channel morphologies, land use, and land cover
    (Colorado State University. Libraries, 2021) Emanuelson, Karin, author; Covino, Timothy, advisor; Ross, Matthew R. V., committee member; Morrison, Ryan R., committee member
    Land use within a watershed impacts stream channel morphology and hydrology and therefore in-stream solute transport processes. In this study, I selected two stream sites with contrasting channel morphology, land use and land cover: Como Creek, CO, a relatively undisturbed, high-gradient, forested stream with a gravel bed and complex channel morphology and Clear Creek, IA, an incised, low-gradient stream with low-permeability substrate draining an agricultural landscape. At these sites, I performed conservative stream tracer experiments to address the following questions: 1) How does solute transport vary between streams with differing morphologies and watershed land use?, and 2) How does solute transport at each stream site change as a function of discharge? I analyzed in-stream tracer time series data and compared results quantifying solute attenuation in surface and subsurface transient storage zones. I found significant differences in solute transport metrics between sites and significant trends in these metrics with varying discharge conditions at the forested site but not at the agricultural site. In the relatively undisturbed, forested stream there was a broad range of transport mechanisms and evidence of substantial exchange with both surface and hyporheic transient storage. In this forested site, changing discharge conditions activated or deactivated different solute transport mechanisms and greatly impacted advective travel time. Conversely, in a simplified, agricultural stream there was a narrow range of solute transport behavior across flows and predominantly surface transient storage at all measured discharge conditions. These results demonstrate how channel simplification resulting from land use change inhibits available solute transport mechanisms across varying discharge conditions.
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    Constraints on mechanical fuel reduction treatments in USFS Wildfire Crisis Strategy priority landscapes
    (Colorado State University. Libraries, 2024) Woolsey, George, author; Hoffman, Chad M., advisor; Tinkham, Wade T., advisor; Battaglia, Mike A., committee member; Ross, Matthew R. V., committee member
    The US Forest Service recently launched a Wildfire Crisis Strategy outlining objectives to safeguard communities and other values at risk by substantially increasing the pace and scale of fuel reduction treatment. This analysis quantified layered operational constraints to mechanical fuel reduction treatments including existing vegetation, protected areas, steep slopes, and administrative boundaries in prioritized landscapes. A Google Earth Engine workflow was developed to analyze the area where mechanical treatment is allowed and operationally feasible under three scenarios representing a range of management alternatives under current standards. Results suggest that a business-as-usual approach to mechanical fuel reduction is unlikely in most landscapes to achieve the 20-40% of high-risk area treatment objective using mechanical methods alone. Increased monetary spending to overcome physical constraints to mechanical treatment (e.g., steep slopes and road access) opens sufficient acreage to meet treatment objectives in 18 of 21 priority landscapes. Achieving treatment objectives in the remaining landscapes will require both increased spending and navigating administrative complexities within reserved land allocations to implement fuels treatments at the pace and scale needed to moderate fire risk to communities. Broadening the land base available for treatment allows for flexibility to develop treatment plans that optimize across the multiple-dimensions of effective landscape-scale fuel treatment design. Spatial identification of the constraints to mechanical operability allows managers and policymakers to effectively prioritize mechanical and managed fire treatments.
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    Metals export to streams during base flow and storm events in the 416 Fire, southwest Colorado
    (Colorado State University. Libraries, 2021) Pulver, Bryce A., author; Kampf, Stephanie K., advisor; Ross, Matthew R. V., committee member; Leisz, Stephen J., committee member
    With approximately two thirds of the Western U.S. relying on fresh water from forested areas, it is vital to understand how wildfires can affect the release of metals into soil water and streams. Moderate to high intensity fires can alter the physical and chemical properties of soil, allowing elevated release of sediment, organic matter, and nutrients to streams. While many studies have focused on how fires affect sediment loading, nutrient export, and organic matter; less research has been conducted on how wildfire impacts the export of metals. This study examines metals export from the 2018 416 fire near Durango, CO during baseflow and storm events. Six tributaries (3.88-38.8 km2) and five sites on Hermosa Creek (152-435 km2) were sampled and analyzed for metal concentrations. We examine how metal concentrations relate to burn severity and watershed characteristics under different flow conditions using both univariate correlation analysis and multivariate models. Metal concentrations were significantly greater in burned baseflow samples compared to unburned locations for As, Ca, K, Mg, Mo, Si, Sr, and Zn. Concentrations of As in baseflow exceeded the Environmental Protection Agency's (EPA's) primary drinking water maximum contaminant level (MCL). Metal concentrations in baseflow were positively correlated with percentage of watershed burned, burn severity, and basin slope, and negatively correlated with basin elevation, drainage area, and average annual precipitation. Metal concentrations increased significantly (mean factor change = 20.6) in storm samples compared to pre-storm samples for Al, As, Ba, Ca, Cr, Fe, K, Li, Mg, Mn, Si, and Zn with Al, As, Ba, Be, Cd, Cr, Fe, Mn, Ni, and Pb being above an EPA or World Health Organization (WHO) MCL. Although storm samples were limited, metal concentrations were correlated with watershed burn severity (r ~ 0.8), indicating elevated metal concentrations likely came from burned areas. Overall, this study demonstrated that wildfires cause elevated metal concentrations in both baseflow and stormflow, but with the exception of As, only the stormflow metal concentrations posed water quality concerns, with 10 metals exceeding both EPA and WHO MCL's for drinking water.
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    The dual lens of sustainability: economic and environmental insights into novel carbon reduction technologies using systems modeling, data science, and multi-objective optimization
    (Colorado State University. Libraries, 2024) Limb, Braden Jeffery, author; Quinn, Jason C., advisor; Simske, Steven J., advisor; Gallegos, Erika E., committee member; Ross, Matthew R. V., committee member
    In an era marked by escalating climate change and increasing energy demands, the pursuit of sustainable solutions in energy production and environmental management is more critical than ever. This dissertation delves into this challenge, focusing on innovative technologies aimed at reducing carbon emissions in key sectors: power generation, wastewater treatment, and aviation. The first segment of the dissertation explores the integration of thermal energy storage with natural gas power plants using carbon capture, a crucial advancement given the dominant role of fossil fuel-based power plants in electricity generation. Addressing the economic and operational drawbacks of current carbon capture and storage (CCS) technologies, this study evaluates various thermal storage configurations. It seeks to enhance plant performance through energy arbitrage, a novel approach to offset the large heat loads required for carbon capture solvent regeneration. By optimizing these technologies for current and future grid pricing and comparing their feasibility with other production methods, this research aims to strike a balance between maintaining reliable power generation and adhering to stringent environmental targets. Results show that resistively charged thermal storage can both increase CCS flexibility and power plant profits through energy arbitrage when compared to power plants with CCS but without thermal storage. Beyond electrical systems, addressing climate change also necessitates improving the energy efficiency of water treatment technologies. Therefore, the dissertation investigates the potential of nature-based solutions as sustainable alternatives to traditional water treatment methods in the second section. This section probes into the efficacy of green technologies, such as constructed wetlands, in reducing costs and emissions compared to conventional gray infrastructure. By quantifying the impact of these technologies across the U.S. and evaluating the role of carbon financing, the research highlights a pathway towards more environmentally friendly and economically viable water treatment processes. Results show that nature-based water treatment technologies can treat up to 37% of future nutrient loading while both decreasing water treatment costs and emissions compared to traditional water treatment techniques. The transportation sector will play a key role in addressing climate change as it is the largest contributor to greenhouse gas emissions. While most of the transportation sector is expected to transition to electric vehicles to decrease its carbon footprint, aviation remains hard to decarbonize as electric passenger aviation is expected to be range limited. Therefore, the final segment of the dissertation addresses the challenge of meeting the U.S. Department of Energy's Sustainable Aviation Fuel (SAF) goals. It involves a comprehensive analysis of various bioenergy feedstocks for SAF production, using GIS modeling to assess their economic and environmental impacts across diverse land types. The study employs multi-objective optimization to strategize the deployment of these feedstocks, considering factors like minimum fuel selling price, greenhouse gas emissions, and breakeven carbon price. Furthermore, agent-based modeling is used to identify policy incentives that could encourage farmer adoption of bioenergy crops, a critical step towards meeting the SAF Grand Challenge goals. This dissertation offers a comprehensive analysis of novel carbon reduction technologies, emphasizing both economic viability and environmental sustainability. By developing integrated models across key sectors affected by climate change, it explores the benefits and trade-offs of various sustainability strategies. Incorporating geospatial and temporal dimensions, the research uses multi-objective optimization and systems thinking to provide targeted investment strategies for the greatest impact. The results provide important insights and actionable plans for policymakers and industry leaders, contributing to a sustainable and low-carbon future in essential areas of the global economy.