From 2011 to 2014, one of the most severe and intense droughts in Texas recorded history led to widespread wildfires across the state, with unknown effects on atmospheric nutrient and pollutant deposition. The objectives of this research were to: (1) characterize the frequency, magnitude, and spatiotemporal distribution of Texas wildfires (2011-2014); (2) identify smoke occurrence and source regions at eight Texas National Atmospheric Deposition Program (NADP) National Trends Network (NTN) sites (2011); and (3) quantify the influence of wildfire on weekly rainwater chemistry and deposition in 2011 at three NADP sites (Sonora, LBJ Grasslands, Attwater Prairie NWR). Data on large wildfires, smoke occurrence, and rainfall chemistry and deposition were coupled with principal component and back-trajectory analysis to address these objectives. Between 2011-2014, 72% of all wildfires occurred in 2011, accounting for 90% of the total area burned. In total, there were 17 extreme wildfires (i.e., in the 95th percentile of hectares burned), of which 11 occurred in 2011. Wildfire activity was concentrated in West Texas ecoregions and consumed primarily shrub/scrub and grassland/herbaceous land cover. Although West Texas experienced the most wildfires, smoke at the NADP locations in 2011, the "high-fire year," was more frequent in East Texas due to regional …

Digital twins are virtual renditions of the actual world that include real-world assets, connections, activities, and processes. Recent developments in technologies play a key role in advancing the digital twin concept in urban planning, designing, and monitoring. Moreover, the latest developments in remote sensing technology have resulted in accurate city-scale light detection and ranging (LiDAR) data, which can be used to represent urban objects (buildings, vegetation, roads, and utilities), enabling the creation of digital twin of urban landscapes. This study aims to build a digital twin of the University of North Texas (UNT) using LiDAR and GIS data. In this research, LiDAR point clouds are used to create 3D building and vegetation modeling along with other GIS data (bicycle racks and parking areas) in creating a digital twin model. 3D Basemap solutions of ArcGIS Pro and ArcGIS Online Scene Viewer, respectively, are used to create an initial 3D urban model and build the ultimate digital twin of UNT. The emergency management floorplans of UNT buildings are incorporated into the digital twin to increase emergency management efficiency. Moreover, solar power potential for individual buildings at UNT has been estimated using the Digital Surface Model (DSM) and integrated into the digital twin …

This research investigates particulate matter (PM) deposition to rock pigeons (Columba livia) in urban environments within Denton County, Texas. Pigeon habitat was characterized within a 2-km radius at eight locations using the 2016 National Land Cover Database (NLCD). In summer 2020, feathers were sampled from 10 rock pigeons at two locations (n = 20) differing in degree of urban development. Birds were captured using walk-in funnel traps baited with bird seed. Based on molt pattern and appearance, four old flight feathers were identified and sampled from each bird. New primary feathers were obtained from each population as reference samples. Feathers were washed three times with double deionized water and acetone, and the solution vacuum filtered through a glass microfiber filter to collect all particles >1.5 µm in diameter. Particulate matter mass was determined by gravimetric analysis and calculated per unit feather surface area. Relative PM accumulation rates were significantly different between the populations. Characteristics of urban land cover, proximity to and types of emissions sources, wind exposure, and building density were drivers of variability in PM deposition to feather surfaces. The results from this study should be useful for subsequent research to help identify best practices for using feathers collected …

My research examines how primary stakeholders interact with Texas' most harvested big game animals: white-tailed deer, which are increasingly impacted by chronic wasting disease (CWD), and feral hogs, which impact the landscape but effectively have no management strategy. Drawing on literature on wildlife governance in Texas, managing property and the commons, and disease landscapes, and broadly framed by themes of political and historical ecology, my research asks: (1) how do management goals for deer and feral hogs compare to hunting practices and hunting culture in Texas? (2) How are deer commodified by the Texas deer breeding industry? (3) How does the commodification of deer by breeders impact deer hunting practices in Texas? To examine how local stakeholders manage CWD and feral hogs, I conducted interviews among 21 stakeholders, including hunters, game wardens, game ranch managers, and deer breeders in Texas, as well as conducting participant observation at three deer conferences. Analysis shows that contrary to my expectations, not all participants viewed feral hogs negatively, with some viewing them as profit-making ventures. Inversely, how stakeholders contend with and understand CWD varies by a stakeholder's ability to generate profit from deer breeding. Furthermore, the majority of participants identified deer breeding operations as …

Low-cost sensors have the potential to create dense air monitoring networks that help enhance our understanding of pollution exposure and variability at the individual and neighborhood-level; however, sensors can be easily influenced by environmental conditions, resulting in performance inconsistencies across monitoring settings. During summer 2020, 20 low-cost particulate sensors were deployed with a reference PM2.5 monitor in Denton, Texas in preparation for calibration. However, from mid to late-summer, dust transported by the Saharan Air Layer moved through the North Texas region periodically, influencing the typical monitoring pattern exhibited between low-cost sensors and reference instruments. Traditional modeling strategies were adapted to develop a new approach to calibrating low-cost particulate sensors. In this study, data collected by sensors was split according to a novel dust filter into dust and non-dust subsets prior to modeling. This approach was compared with building a single model from the data, as is typically done in other studies. Random forest and multiple linear regression algorithms were used to train models for both strategies. The best performing split-model strategy, the multiple linear regression models split according to dust and non-dust subsets (combined R2 = 0.65), outperformed the best performing single-model strategy, a random forest model (R2 = 0.49). …

In recent decades, the global impacts of unsustainable consumption and production patterns have become a leading topic of sustainability, and more recently, climate action discourse. At the policy level, green consumerism – an element of green capitalism – has been positioned as the pathway to more sustainable consumption and production (SCP) practices. Within this model, eco-labeling schemes are used to communicate various sustainability attributes, or conditions of production, to the consumer. This study set out to investigate whether SCP is achievable through green consumerism using a two-part case study that centers around the egg industry and specific hen welfare standards. The case study examines the effectiveness of egg eco-labeling schemes and related statements and images placed on egg packaging in informing consumers' purchasing decisions. It also examines the impacts of green consumerism on organic egg production in the presence of strong consumer demand for enhanced hen welfare standards. The results of the case study demonstrate that in the egg industry, green consumerism is not highly effective because consumers' purchasing decisions are often informed by vague and misleading information about conditions of production. Moreover, the presence of strong consumer demand has not resulted in enhanced hen welfare standards in organic production. …