Poster Sessions

Assistant Prof In Hong Yang 

Professor Terry Xu

Postdoctoral Fellow Tyler Adams 

Highways are considered a major source of pollution to stormwater and its runoff can introduce various contaminants including nutrients, Indicator bacteria, and heavy metals which can have negative impacts on receiving waters. Also, the roadside soil gets compacted over time and can’t infiltrate the stormwater through it. The situation becomes worse if it is clay soil resulting in increased runoff. This study assessed the ability of biochar, a carbon-rich byproduct generated from the pyrolysis of biomass, the removal of contaminants and to improve the water-holding as well as infiltration capacity of soil biochar mixture. For this, commercially available biochar was strategically selected. Lab scale batch testing was done to find the preliminary estimate of contaminants removal along with saturated hydraulic conductivity, and water retention capacity. Furthermore, from the preliminary results, the bench scale filtration columns were designed to evaluate the performance of biochar in the long term. Based on specific infiltration capacity soil biochar column packing was done. The testing has been conducted for nutrient, heavy metal, and indicator bacteria analysis over a year, which includes different weathering conditions. The results from saturated hydraulic conductivity show that biochar was able greatly improve the infiltration capacity which is attributed to the high porosity of the biochar soil mixture. The data from the column testing shows that biochar has the ability to significantly remove different contaminants. Overall, this study demonstrates that biochar could be efficiently applied with clay soil to improve the soil's hydraulic characteristics as well as to remove the pollutants from stormwater runoff.

In today's landscape, informatization and automatization have emerged as prevailing trends within the architecture-engineering construction and facility management (AEC/FM) industries (Zhang et al., 2022). Among these, artificial intelligence (AI) stands out as a potent technology, progressively revealing its diverse capabilities across various sectors (Regona et al., 2022). Despite the existence of the concept of AI for several decades, the level of understanding and awareness of AI among FM professionals remains unclear. Limited research and knowledge exist regarding how well FM professionals grasp AI concepts, deploy its use, comprehend its potential benefits, and understand the challenges associated with its implementation. Research This research aims to delve into the current landscape of AI understanding and awareness among Facility Management (FM) professionals. The study also endeavors to assess the present utilization of AI within FM practices and explore potential future applications. Additionally, it aims to scrutinize the factors influencing the adoption and implementation of AI in FM settings, analyzing comparative differences across diverse geographic regions or facility types. A survey was designed to collect information on facility managers’ awareness and understanding of selected popular AI tools and resources. This instrument was then pilot-tested by the SMEs to ensure its relevance. In November 2023 an invitation to participate in the survey was sent electronically via Qualtrics to more than 2,000 FM professionals. Over 400 individuals responded to the survey, reflecting a 15% response rate. The survey data was analyzed using a combination of statistical techniques including descriptive frequency counts, charts, and crosstabulations of responses for variables of interest. Preliminary Results: Among the respondents surveyed, 28% are not aware of the use of AI in facility management, 35% have a limited understanding of AI and 18% express a high level of understanding of the concept. Interestingly, only 4% reported formal AI-focused training participation, with an equal percentage expressing disinterest due to its perceived irrelevance in their current roles. However, 78% of those without AI training expressed keenness in engaging with such programs if presented with the opportunity. In practical implementation, only 23% affirmed integrating AI-driven technologies into their facility management practices. Overall, most facility managers (70%) expressed strong support and advocacy for the adoption of AI in facility management. The impact of this research serves as a pivotal catalyst for fostering broader systemic changes in workplace awareness of the integration of AI. Firstly, the findings provide data on the level of understanding of AI among FM professionals. Thereby, acting as a clarion call for organizations to reevaluate preconceived notions on their workforce understanding of AI. The research outcomes provide empirical evidence to support the necessity of providing the workforce with training and educational programs focused on AI applications. Beyond the corporate sphere, the study's implications reach educational institutions, encouraging the incorporation of AI-based curricula that prepare future FM professionals for technologically driven workplaces. 

Microplastics are a major environmental concern, and wastewater treatment plants are key entry points for these pollutants into ecosystems. The treatment process usually involves primary and secondary stages. In primary treatment, solids settle and are removed. Afterwards, the lighter materials and wastewater depart and enter the secondary treatment chamber. In secondary treatment, biological processes are utilized to further purify the water and remove additional solids. These settled solids, known as biosolids, can be processed, and used as fertilizers for agricultural use. However, this reuse can lead to microplastic contamination in agricultural soils, posing risks to food safety. This research focuses on quantifying microplastics in treatment stages and finding removal strategies to prevent environmental contamination. It examines the size and concentration of microplastics in primary and secondary solids to assess removal efficiency in wastewater treatment. The study uses a thorough protocol for microplastic analysis, including wet peroxide digestion, density separation, and staining, with digital microscopy and the Fourier Transform Infrared (FTIR) spectrometry for identification and quantification. Initial findings show secondary sludge has more microplastics, with smaller particle sizes than primary solids. This suggests secondary clarifiers may accumulate more microplastics, highlighting the need for further study into treatment mechanisms. The disparity in concentrations between stages points to the need for targeted mitigation strategies in treatment facilities to reduce pollution. The research outcomes could impact environmental policies and management of wastewater treatment and biosolid use. A better understanding of microplastic behavior can improve mitigation efforts, protecting ecosystems and human health.

Detecting SARS-CoV-2 in wastewater provides a cost-effective alternative to expensive methods like random group testing and individual clinical tests, potentially identifying asymptomatic cases. Electronegative Membrane Filtration (EMF) is a widely used, cost-effective tool for large-volume wastewater virus concentration. However, there's limited research on efficient RNA extraction methods. This study aimed to achieve efficient RNA extraction kits for wastewater surveillance by integrating them with the EMF method of virus concentration. Raw wastewater samples from three treatment plants were collected in Mecklenburg County. Two RNA extraction protocols, the 'QIAamp Viral RNA Mini Kit' and the 'Zymo Quick RNA Viral Kit,' utilizing lysis buffer principles, were modified to enhance RNA yield by adjusting buffer ratios and by removing inhibitions. These optimized methods were compared with two different extraction methods, the ‘RNeasy Power Water Kits’ and the ‘AllPrep Power Viral DNA/RNA Kit,’ utilizing bead-beating principles. The Zymo Quick RNA Viral Kit outperformed the other three kits significantly in Cq value (29-31), copies per reaction, and copies per liter (100,000 to 350,000, P<0.01). It also exhibited a better recovery of 10% of the surrogate Bovine Coronavirus (BCoV). Moreover, the ‘Zymo kit’ was found to be cost-effective at $159.5 for 50 preps compared to other extraction methods. This suggests that the ‘Zymo Quick RNA Viral Kit’ is more efficient at extracting and purifying viral RNA, enabling accurate virus quantification. It informs public health decisions and supports the development of sensitive diagnostic tests, crucial for early virus detection and control.

Autonomous shuttles represent a promising solution to revolutionize public transportation networks, offering the potential to enhance accessibility, reduce traffic congestion, and improve overall urban mobility. The proclivity of users to adopt autonomous shuttles is influenced by several factors, including perceptions of safety, comfort, trust, familiarity with autonomous shuttles, and various socioeconomic indicators. The study employs Structural Equation Modeling (SEM) to decode this complex problem and discern the relationships among these variables. SEM allows for the simultaneous examination of multiple dependent relationships and the inclusion of latent variables, which are not directly observed but are inferred from other observed variables. Specifically, the study utilizes a MIMIC model within SEM to elucidate the relationship between latent variables (safety, comfort, trust) and their indicators while considering the direct influence of observed variables on latent ones. The primary dependent variable, 'willingness to use,' is influenced by three latent variables: safety, comfort, and trust. Measured variables, such as age, annual household income, frequency of public transportation use, and familiarity with autonomous shuttles, also impact the willingness to use autonomous shuttles. The study will be beneficial for practitioners and industry experts to include autonomous shuttles in the long range transportation planning.

The emergence of antibiotic-resistant bacteria (ARB) has become a major global health threat. The principal factor for antibiotic resistance development in bacteria is the increased use of antibiotics in healthcare and agriculture. Due to the misuse of antibiotics, bacteria recognize the mode of action of the antibiotics and develop defensive mechanisms to survive. While discovering new antibiotics is a long-term journey, the rising antibiotic resistance makes the conventional strategies challenging to combat the situation, necessitating innovative antimicrobial solutions. Nanoparticles posing unique characteristics, particularly silver nanoparticles (AgNPs), have gained the attention of researchers for their antimicrobial potential. AgNPs have been studied and reported as a potential candidate to combat ARB. In addition, the photodynamic inactivation (PDI) process has shown a promising cytotoxic effect on microbial cells. This study aims to investigate the combined effect of silver nanoparticles (AgNPs) and photodynamic inactivation (PDI) on ARBs. We hypothesize that integrating AgNPs with PDI will result in a synergistic effect that leads to enhanced activity against ARBs. The effectivity of AgNPs as an antimicrobial agent is related to Ag+ release. The oxidation process induced by PDI will eliminate the ARBs by multiple cytotoxic mechanisms along with increased release of Ag+ from AgNPs. This dual action approach will facilitate overcoming the limitation of adopting individual strategies and provide a robust solution to address the growing concern of ARB. 

This study represents a crucial step in developing sustainable and effective solutions to mitigating the adverse effect of antibiotic resistance on public health. The findings could contribute to the development of advanced antimicrobial agents with broad applications in healthcare, agriculture, and various other sectors, for instance - in water treatment plants.

Historically, traditional concrete tests such as slump and strength tests have proven to be very poor predictors of long-term concrete properties. Hence, the need to develop novel tests, to provide a greater degree of correlation to the future performance of concrete. Performance Engineered mixtures (PEM) tests have emerged as a promising solution and has already been implemented on highway pavements, revealing promising results. However, the viability of these tests for relatively thicker airfield pavements has yet to be determined, birthing this research initiative. Interviews with experts in the industry were conducted and their feedback was used to inform the project objectives. The main objective is to establish a practical mixture design tool that contractors and project managers can use to produce airfield pavement mixtures with a 3 response to vibration and incorporate this tool into code for ease of adoption at Airfields nationwide. Ongoing investigations have been focused on identifying the most promising mixtures, using the new PEM tests followed by field validation through shadow testing. Finally, Specifications will be developed for implementing the mixture design tool and tests will be recommended for implementation in the Federal Aviation Administration (FAA P-501) and the military Tri-Services UFGS airfield pavement specifications, underscoring the project’s national significance. By providing tools that can accurately predict the performance of concrete, this project will help contractors, project managers, aviation operators, and the wider community to improve the quality, longevity, and sustainability of millions of acres of airfield pavement. The use of PEM for airfield pavements has the potential to revolutionize the aviation industry as it provides a platform to determine concrete properties before it is even poured on our airfields.

Highways are considered a major source of pollution to stormwater and its runoff can introduce various contaminants including nutrients, Indicator bacteria, and heavy metals which can have negative impacts on receiving waters. Also, the roadside soil gets compacted over time and can’t infiltrate the stormwater through it. The situation becomes worse if it is clay soil resulting in increased runoff. This study assessed the ability of biochar, a carbon-rich byproduct generated from the pyrolysis of biomass, the removal of contaminants and to improve the water-holding as well as infiltration capacity of soil biochar mixture. For this, commercially available biochar was strategically selected. Lab scale batch testing was done to find the preliminary estimate of contaminants removal along with saturated hydraulic conductivity, and water retention capacity. Furthermore, from the preliminary results, the bench scale filtration columns were designed to evaluate the performance of biochar in the long term. Based on specific infiltration capacity soil biochar column packing was done. The testing has been conducted for nutrient, heavy metal, and indicator bacteria analysis over a year, which includes different weathering conditions. The results from saturated hydraulic conductivity show that biochar was able greatly improve the infiltration capacity which is attributed to the high porosity of the biochar soil mixture. The data from the column testing shows that biochar has the ability to significantly remove different contaminants. Overall, this study demonstrates that biochar could be efficiently applied with clay soil to improve the soil's hydraulic characteristics as well as to remove the pollutants from stormwater runoff.