Aquatic Ecology

Impacts of climate change on the future of Laurentian Great Lake water systems

Poster #1

Author: Huy Dang, Yadu Pokhrel 

Author Bio: Huy Dang is a Postdoctoral Research Associate at Michigan State University, specializing in the impacts of water hazards in relation to climate change and human activities. He holds a Ph.D. in Civil Engineering from MSU and has been working on hydrodynamic modeling, flood risk assessment, and international collaboration on water resource management projects. During his time at MSU, he received a number of awards including Engineering Distinguished Fellowship, William W. and Evelyn M. Taylor Endowed Fellowship for International Engagement in Coupled Humans and Natural Systems, and Jianguo (Jack) Liu Graduate Award in Sustainability fellowship among others.

Contact: huydang@msu.edu 

The increasing demand for water, food, and energy is intensifying global climate change and placing tremendous stress on freshwater systems. The Laurentian Great Lakes Basin (GLB), which holds one-fifth of Earth’s fresh surface water, is abundant with this resource and is less prone to rapid changes due to extreme climate events compared to other US regions. However, even relatively minor fluctuations in both long- and short-term lake water levels can lead to the widespread of major floods or droughts, consequently impacting the region’s food security and water supply for over 30 million people. Despite its importance to both the U.S. and Canada, a comprehensive long-term assessment of future changes in GLB hydrodynamics and their implications for regional agricultural production is still lacking. To address this gap, we employ a modeling framework coupling an ensemble of global climate and hydrology models from ISIMIP3 with CaMa-Flood, a large-scale hydrodynamic model, to project the GLB hydrodynamics changes under multiple climate scenarios. Initial results suggest that there is an overall increase in water availability across the entire GLB by the end of this century. This trend leads to a decrease in drought severity while floods are more extreme and prolonged. Moreover, our results indicate substantial changes in the seasonal hydrologic regime of the GLB, with major shifts in the timing of winter and spring peak flows. Further analysis will include an in-depth analysis of GLB lake water levels and the implications of these hydrodynamics changes on the GLB agricultural production. By advancing our understanding of long-term climate change impacts on the GLB, this study aims to inform future water management strategies and policies, ultimately contributes to this region’s resilience in the face of a changing climate.

Evaluation of Cation-Bridging Sorption of Per- and Polyfluoroalkyl Substances by Soils from Water

Poster # 2

Author: Andrew Huang, Wei Zhang, Brian J. Teppen, Hui Li 

Bio: 

Contact: huangan7@msu.edu

Per- and poly-fluoroalkyl substances (PFAS) are widespread contaminants posing potential threats to human health, and the sorption of PFAS in soils influences the mobility and bioavailability in the environment. Research has indicated that the sorption of PFAS in soil is affected by cations in soil and water, which could be enhanced by cation-bridging interaction with multivalent cations on soil surfaces. In this study, sorption experiments of PFAS with carboxylic head groups and sulfonic head groups (PFNA and PFOS) in K+- and Ca2+-saturated soils were carried out to verify the possible cation-bridging interaction between PFAS and soil. Several low-molecular-weight ligands were applied to evaluate the strength of cation-bridging by blocking the Ca2+ binding sites via the same interaction with PFAS. We found that Ca2+ enhanced PFNA and PFOS adsorption while applying ligands increased the Ca desorption and reduced the PFAS adsorption. In addition, a speciation model was also developed to fit the collected empirical sorption data and calculate the distribution coefficients. This study will further evaluate the contribution of cation-bridging interaction to enhanced PFAS sorption by soils, providing new insight into the effects of divalent cations as a key factor in PFAS transport in the environment.

Unveiling the Traits of Great Lakes Bloom-Forming Cyanobacteria

Poster #3

Author: Elena Litchman, Carol Waldmann Rosenbaum

Bio: Elena Litchman is an MSU Research Foundation Professor studying aquatic ecology and harmful algal blooms (HABs). She has led many large scale international projects on studying aquatic ecosystems around the globe and is a recipient of several major awards, including the NSF CAREER award, PECASE award, the Hutchinson Award from the Association for the Sciences of Limnology and Oceanography, The Peterson Foundation Excellence Professorship from Germany and is an ASLO Fellow.

Contact: waldma21@msu.edu

Cyanobacterial harmful algal blooms (cHABs) are a major environmental problem that threatens water quality, ecosystem and human health, and coastal communities’ livelihoods. The frequency and severity of cHABs have increased worldwide, including in the Laurentian Great Lakes (LGLs). Despite diverse environments across the LGLs, the same bloom-forming taxa are present in all five lakes, suggesting that these cyanobacterial genera have adapted to a broad range of conditions. Although only a few genera compose most of the regional blooms, there is great inter- and intraspecific genetic and functional diversity within these genera, which may aid cyanobacterial adaptation to local conditions. We investigate how temperature and nutrient traits such as temperature optima and width and phosphorus and nitrogen affinities vary across and within cyanobacterial populations in the LGLs. We measured growth rates for 80 cyanobacterial strains isolated from Lakes Superior, Michigan, Huron, and Erie in 2022 and 2023. We found that Lake Superior strains have lower temperature optima and lower maximal growth rates. Additionally, Lake Superior’s strains have higher phosphorus affinity and larger cell sizes in comparison to Erie and Michigan strains. Our results contribute to evidence of great inter- and intraspecific functional diversity within and across cyanobacterial LGLs' populations and suggest that cyanobacterial strains in Lake Superior are likely limited by temperature. Further assessing nutrient and genetic traits would contribute to mechanistic explanations of community dynamics and helps us understand species abundance and succession across environmental gradients such as in the LGLs.

Augusta Creek, Michigan: A Long-term Ecologically Significant but Hydrologically Mysterious Catchment in a Glaciated, Low-relief, and Wetland-Dominated Landscape

Poster #4

Author: Caroline Weidner, Jay Zarnetske 

Bio: "I am a 5th year PhD candidate in Earth & Environmental Sciences at MSU. My research over my graduate degree has focused on the biogeochemistry of streams and wetlands in southwestern Michigan. Most of my research involves field studies in the Augusta Creek Catchment, in proximity to MSU’s Kellogg Biological Station. In my future career I hope to continue researching hydrology and water chemistry, with additional focus on wetland protection and water resource management.”

Contact: weidne11@msu.edu

The Augusta Creek catchment, located in southwestern Michigan, is a low-relief, third order stream catchment draining ~98 km2 of wetland, agricultural, and forested land. This catchment is unique due to its stable, groundwater-dominated hydrology, even being denoted as the “stable” stream example in the Natural Flow Regime Paradigm (Poff et al., 1997). Augusta Creek contains subsurface hydrogeologic heterogeneities and minimal overland flow, both of which influence streamflow generation and contribute to the catchment's puzzling hydrology. Due to its proximity to Michigan State University’s W.K. Kellogg Biological Station, this catchment has been the focus of various biogeochemical and ecohydrologic studies since the 1970s. Additionally, the USGS monitoring station located on this stream has been collecting discharge data since 1989. Currently, we have several projects in Augusta Creek including a high-frequency sensor network for water quality parameters including dissolved oxygen, conductivity, dissolved organic carbon, and nitrate, and a synoptic sampling campaign that collects surface water samples for carbon, nitrogen, and major ions across the catchment every two weeks and has generated over 1300 samples since 2021. Although Augusta Creek has been the focus of various research studies, stable groundwater-fed streams in low-relief catchments have generally been underrepresented in catchment sciences, leading to limited understanding of how hydrologic processes work in these catchments. Our current studies in this catchment allow for exploration into how hydrologic and solute patterns differ from high-relief, forested catchments that are more commonly studied. We have found distinctive patterns in Augusta Creek, attributed to the heterogeneous nature of the catchment, which is dominated by wetlands and with headwaters that originate from lakes and wetlands, emphasizing the importance of conducting studies across different catchment characteristics and complex hydrology.

Genetic Tracers of Land Use Captured in the Environmental DNA of Aquatic Microbial Communities of the Saginaw Bay Watershed

Poster #5

Author: Nicole Smith, Matthew Schrenk, Sherry Martin 

Bio: Nicole Smith is a masters student in Microbiology, Genetics, and Immunology at Michigan State University. She completed her bachelors at Michigan State in Environmental Biology with a concentration in Microbiology. Her work in Dr. Matthew Schrenk’s geomicrobiology lab intertwines hydrology, microbiology, and spatial mapping to understand anthropogenic impacts on the Saginaw Bay Watershed. She is driven by her love of the environment and the importance of water for sustaining life on earth.

Contact: smit3363@msu.edu

The Saginaw Bay Watershed is the largest drainage basin in Michigan and the microbial communities populating the surface water play a major role in ecosystem services such as nutrient cycling of carbon and nitrogen. However, with the urbanization and industrialization of four major urban centers in the watershed, the development of formerly-forested land into animal farming operations, agricultural fields, and population centers influence the biogeochemistry of the watershed. In this study, surface water samples from the Kawkawlin River and additional drains within the Saginaw Bay Watershed were analyzed for connections between surface microbial community composition, nutrient levels, hydrology, and land usage. Using ModelMyWatershed, the 23 sampling sites were coordinated with subwatersheds, and environmental metadata about land usage, soil type, animal farming operations, and hydrological qualities were gathered for each sampling subwatershed. This information was combined with microbial biodiversity data from 16S rRNA amplicon sequencing, nutrient, and anion abundances from the surface water samples. Correlation analysis revealed that stream order strongly influenced the alpha diversity of microbial communities in the surface water while the presence of cropland had a strong influence on the nutrient composition of the watershed. As stream order decreased, the microbial communities were shown to increase in richness and evenness. In subwatersheds with high percentages of agriculture, higher levels of total nitrogen, nitrate, chloride, and sulfate were found within the surface water. By understanding the connections between land usage and watershed characteristics, improved land management strategies can be established within the Saginaw Bay Watershed to limit deleterious impacts on the aquatic ecosystem.

Irrigation Water Use over the Mississippi River Basin

Poster #6

Author: Aman Shrestha, Yadu Pokhrel

Bio: “I am currently a second-year PhD student in the department of Civil and Environmental Engineering specializing in Hydrology and Water Resources. My research focuses on advancing sustainable water resource management through modeling and data-driven approaches.”

Contact: shrest66@msu.edu

Irrigation for agriculture is the most water-intensive sector in the United States, where the High Plains Aquifer (HPA) and the Mississippi Embayment contributes 35,000 million gallons per day to irrigate agricultural land within the Mississippi River Basin (MRB). This region is a major contributor to US crop production, particularly maize, soybean, and wheat. Accurately modeling surface and groundwater availability, as well as consumptive use, is critical to guide sustainable water management and policymaking. We estimate the irrigation water withdrawals from surface water and groundwater over the entire MRB from 1980-2020 using a state-of-the-art land surface model, Community Land Model version 5 (CLM5) at a ~5km spatial resolution. Modeled irrigation water withdrawal rates are compared against irrigation withdrawal estimates from the United States Geological Survey (USGS) to evaluate model performance. Preliminary results suggest that current rates of irrigation withdrawal, particularly over the central and southern HPA, are fundamentally unsustainable. Further analysis will assess modeling capabilities of CLM5, and provide insights to support region-wide water adaptation strategies.

Enhancing Agricultural Water Sustainability through Phosphorus Capture and Regeneration using iron-enhanced alumina-based sorption media

Poster #7

Author: Soni Kumari, Younsuk Dong

Bio: Dr. Soni Kumari is a postdoctoral research associate in the Department of Biosystems and Agricultural Engineering at Michigan State University. With a PhD in Environmental Science and Engineering from IIT Dhanbad, India, Dr. Kumari specializes in developing cost-effective and sustainable strategies for wastewater treatment and nutrient recovery, aligning with the core philosophy of creating "wealth out of waste." Her current research focuses on capturing dissolved phosphorus from controlled tile drainage in the Western Lake Erie Basin (WLEB). Dr. Kumari has authored several peer-reviewed publications and book chapters, contributing significantly to the advancement of strategies to mitigate nutrient pollution and promote sustainable water management. 

Contact: Soni Kumari (kumariso@msu.edu) 

Agricultural runoff, particularly from subsurface drainage systems, is a major contributor to phosphorus (P) loss from farmlands, exacerbating eutrophication and harmful algal blooms (HABs) in downstream aquatic ecosystems. Dissolved reactive phosphorus (DRP), the most bioavailable form of P, is a key driver of these environmental challenges. Traditional mitigation strategies often fail to effectively capture DRP, highlighting the need for novel approaches in sustainable agricultural water management. This study explores the application of Alcan media, an iron-enhanced alumina-based sorbent, for DRP removal and recovery from agricultural subsurface drainage water (ASDW).

Laboratory-scale adsorption studies optimized critical parameters, including adsorbent dose, contact time, pH, and initial P concentration, for efficient DRP sequestration. The highest phosphate removal efficiency (94.4%) was achieved with a 3 g/L dose of Alcan media at a 6-hour contact time and an initial phosphate concentration of 2 mg/L. Isotherm modeling demonstrated that the Freundlich model (R² = 0.99) best described the adsorption process, indicating multilayer adsorption, while kinetic studies confirmed pseudo-second-order kinetics (R² = 0.99), suggesting chemisorption as the dominant mechanism. Additionally, the Alcan media exhibited strong regeneration potential, maintaining adsorption efficiency with minimal loss after six cycles of alkaline regeneration using 0.1 M KOH, making it a cost-effective and sustainable option for nutrient recovery.

By integrating circular economy principles, this research highlights the potential for Alcan media to transform agricultural water management practices, reducing nutrient pollution at the source and mitigating the ecological consequences of HABs. The adoption of such innovative sorbent technologies not only enhances sustainability in agriculture but also contributes to a closed-loop approach in water treatment, aligning with global efforts to protect freshwater resources.

Regional Groundwater Modeling in the Great Lakes: A Basin-Scale Approach

Poster #8

Author: Madeline R. Sigler Anthony D. Kendall

Bio: Madeline Sigler is a Graduate Research Assistant pursuing an MS in Geological Sciences at Michigan State University. Her research focuses on regional groundwater flow modeling in the hydrogeologically diverse Great Lakes Basin. She has been an active student member of Michigan AIPG since 2022 and served as Wayne State University’s student chapter president from 2022-2023. Madeline holds a BA in Comparative Cultures and Politics from Michigan State University and a BS in Geology from Wayne State University. She has been accepted to pursue a PhD at Michigan State University in fall 2025.

Contact: siglerm2@msu.edu

The Great Lakes Basin (GLB) contains over 20% of the world's fresh surface water, comprising 95% of the U.S. freshwater supply. While a critical resource, the region’s groundwater dynamics remain insufficiently understood. Although previous studies with the region have incorporated groundwater within sub-basin watershed investigations or coupled surface-groundwater models, a comprehensive basin-scale characterization of groundwater as a regional resource at the basin scale has yet to be established.

The primary objective of this study is to represent groundwater in the GLB as a regional resource in its entirety, congruent with the extent of the basin watershed. This will be accomplished through the construction of a groundwater model for the region. The model will incorporate complex subsurface representation, including multiple layers and refined hydraulic conductivity data. Utilizing groundwater wells on both sides of the international border to achieve cohesive basin representation in calibration, this steady-state model will provide a representation of groundwater conditions in the GLB. This approach minimizes the constraints imposed by surface water calibrations in coupled models.

Preliminary results indicate a conceptual alignment between simulated groundwater heads and the associated geology, with areas of the model where bedrock is at the surface exhibiting higher head values, which is consistent with expectations. The model effectively captures the elevation of groundwater across the entire basin, successfully representing it as a regional resource. The results from this study will contribute to our understanding of groundwater’s role in the GLB’s hydrologic system and advance our conceptualization of a regional-scale water balance. These simulations will provide essential information for further investigations into groundwater storage, discharge volumes to streams, and baseflow contributions to the lakes. Designed to be open-source, the model serves as a foundational tool for future research on groundwater in the Great Lakes Basin.

Water and Health

Review of Procedures for Laboratory Study of Sulfamethoxazole Remediation by Duckweed

Poster #9

Author: Katherine McCullen, Dr. Dawn Dechand

Bio: Katie received her B.S. for Plant Biology from MSU, and is now a M.S. student with the department of Biosystems and Agricultural Engineering. As her educational trajectory would suggest, she is very interested in integrating natural sciences and engineering. Her research and professional goals are centered on finding nature-based solutions for the emerging problems facing our society and world. Her thesis work is examining duckweed phytoremediation of the antibiotic Sulfamethoxazole through a metabolic lens.

Contact: mccul124@msu.edu

Many emerging contaminants (ECs) of concern such as antibiotics, pesticides, cyanotoxins, and PFAS pose a threat to human and environmental health. Plants and their associated microbial communities can metabolize or sequester some contaminants in their environments, rendering them less biologically available. This process, which we refer to as phytoremediation, is a promising avenue for the treatment of ECs, since it can be coupled to traditional treatment systems or used as stand-alone onsite treatment. Understanding the metabolic processes involved is essential to the optimization and implementation of phytoremediation as an effective treatment system for EC’s. The plant family Lemnaceae, otherwise known as duckweeds, are small, free-floating, aquatic plants commonly studied for phytoremediation. Duckweeds are considered adaptable to many conditions, and are native to all continents except Antarctica, making them ideal candidates for on-site remediation across the world. Despite their reduced structure, small genome, and status as a model organism, duckweed metabolomic analysis is lacking when compared to other model plants like Arabidopsis or Zea mays (corn). 

As a case study to illustrate the importance of elucidating duckweed metabolism, we present a literature review of duckweed removal of the antibiotic sulfamethoxazole (SMX) from growth media. Of the five studies available, SMX removal from the growth media ranged from 18% to 96%. The studies varied widely in design, and the metabolic scope was limited. SMX removal from media was quantified, but potential transformation products were not. Duckweed physiology was not considered by all studies, and when it was reported, it was limited to growth rate and other visual observations. There are many factors that could have resulted in the wide spread of removal rates. For example, our prior results indicate that exudate profiles of duckweed depend on species, environmental source, microbial community, and the growth media used. With this presentation, we aim to highlight key differences in procedure from prior research that could contribute to the differences in result of SMX-duckweed research.

Evaluating HF183 and Bacteroides thetaiotaomicron Human Markers for Microbial Source Tracking in Freshwater Systems

Poster #10

Author: Anika Ashraf, Rebecca Riggi 

Bio: Anika Ashraf holds a Bachelor of Science in Microbiology from BRAC University, Bangladesh. She has extensive experience in environmental microbiology, with a particular focus on air quality research in Dhaka, where she studied airborne microorganisms. Currently, she is exploring Ph.D. opportunities in the United States in environmental microbiology and public health. She collaborates with the Rose Lab at Michigan State University, learning about microbial source tracking (MST) and SARS-CoV-2 surveillance in environmental waters.

Contact: meg.aka.anika@gmail.com

Introduction
This study examines the performance of human-specific HF183 and Bacteroides thetaiotaomicron-specific alpha 1-6, mannanase (Btheta) genetic markers used in microbial source tracking (MST) to identify human sources of fecal contamination in surface waters. Understanding the statistical differences in marker occurrence and concentrations is crucial for improving water quality management and minimizing health risks associated with contaminated water. 

Methods and Materials
Droplet digital PCR (ddPCR) MST data for HF183 and B. theta concentrations were analyzed from 352 paired data points within a total of 477 freshwater samples collected in Michigan, USA between 2017 and 2024. Samples were concentrated by membrane filtration, and DNA was extracted using bead beating before analysis on the Bio-Rad ddPCR platform. Marker occurrence in paired data was assessed for percentage detection, statistical differences in marker concentration across the full dataset and data subsets, and statistical differences in extracted DNA concentration. 

Results
All datasets failed tests of normality and proceeded with non-parametric statistical tests. HF183 concentrations were significantly greater than Btheta concentrations in the full pairwise dataset (P<0.001, α=0.05, n=352, Wilcoxon matched-pairs signed rank test). HF183 concentrations were also significantly higher in HF183+/Btheta+ samples (n=36) compared to HF183+/Btheta− samples (n=109) (P<0.001, α=0.05, Mann-Whitney test). DNA concentrations did not differ significantly between HF183+/Btheta+ and HF183+/Btheta− samples (P=0.565, α=0.05, n=145, Mann-Whitney test). Similarly, B. theta concentrations did not differ significantly between Btheta+ /HF183+ and Btheta+ /HF183− samples (P=0.2079, α=0.05, n=51, Mann-Whitney test). However, DNA concentrations were significantly higher in HF183+/Btheta+ samples (n=36) compared to Btheta+ /HF183− samples (n=15) (P<0.0001, α=0.05, Mann-Whitney test), suggesting that co-occurrence of these markers may be associated with higher DNA concentrations. 

Conclusion
These findings highlight the differential detection of HF183 and Btheta markers in MST, with HF183 consistently exhibiting higher concentrations and broader detection of human fecal contamination. The significant differences in DNA concentrations between marker combinations suggest that co-occurrence patterns may affect overall marker detection. While HF183 remains a robust indicator of human fecal pollution, the limited detection and lower concentrations of Btheta indicate potential challenges in its application for broader fecal source identification. These results emphasize the importance of selecting appropriate MST markers based on study objectives and environmental conditions to enhance water quality assessments and public health protection.

High throughput sequencing and bioinformatic approaches for the Identification of bacterial pathogens from community untreated wastewater

Poster #11

Author: Pankaj Bhatt, Yabing Li, Irene Xagoraraki

Bio: Pankaj Bhatt, is a environmental microbiologist. He is working as Postdoctoral Research Associate under the supervision of Prof. Irene Xagoraraki in Civil and Environmental Engineering of Michigan State University. He is working on detection human disease causing bacterial pathogens from the community untreated wastewater.

Contact: bhattpan@msu.edu

Untreated community wastewater serves as a reservoir for human-associated bacterial pathogens. The present study aimed to identify pathogenic bacterial species associated with human diseases from untreated wastewater samples collected in Detroit city, using high throughput sequencing and bioinformatics approach. A polyphasic molecular approach was employed to detect human-associated bacterial pathogens. The techniques used included: (1) bacteriophage-pathogen interactions, (2) full-length 16S rRNA gene amplification, and (3) untargeted RNA sequencing. Using the bacteriophage-pathogen interaction approach, 399 bacterial pathogens associated with 2,477 known phages were identified. The proportion of phage contigs ranged from 15.53% to 18.91% in the wastewater samples. Full-length 16S rRNA sequencing was found to be a reliable method for accurate pathogen taxonomy. Using the DNA-Kraken2 method, 37.75% to 70.56% of contigs were identified as pathogenic bacterial species. Conversely, the DNA-QIIME2 method detected only a small fraction of contigs (0.08%–4.57%) as pathogenic bacterial species. Untargeted RNA sequencing was complementary in identifying active bacterial pathogens in the wastewater, detecting 20.61% to 44.82% of contigs as pathogenic bacterial species. The combination of DNA and RNA sequencing provided higher resolution and broader coverage of pathogenic bacterial genera causing human diseases, including Aeromonas, Arcobacter, Enterococcus, Flavobacterium, Klebsiella, Legionella, Listeria, Moraxella, Mycobacterium, Pseudomonas, Serratia, Staphylococcus, Streptococcus, Salmonella, and others. The findings of this study contribute to accurate taxonomic identification of human disease-causing bacterial pathogens in untreated community wastewater, which has implications for public health monitoring and pathogen detection strategies.

Antimicrobial Resistance Genes (ARGs) diversity in Wastewater

Poster #12

Author: Spencer Kuehn, Wenjing Ren, Nishita D’Souza, Joan B. Rose

Bio: Spencer Kuehn is a laboratory technician with over 2 years of experience in the water microbiology field. His work focuses on wastewater monitoring as a part of Michigan’s SEWER Project for viral pathogens under Dr. Joan Rose. His experience includes the amplification of DNA and RNA targets using molecular biology techniques such as qPCR and droplet digital PCR, as well as ddPCR data analysis.

Contact: kuehnspe@msu.edu

Introduction: Antimicrobial resistance is a growing public health concern. Wastewater monitoring can provide non-invasive insights into the presence of Antimicrobial Resistance Genes (ARGs) to suggest mitigation strategies for public health and protection of the water environment.  Rural communities are susceptible to exposure to human and animal ARGs and are less likely to be monitored.   

Purpose: To investigate the diversity and abundance of ARGs in wastewater comparing urban and rural systems. 

Methods: Wastewater samples were collected (September-October 2024) from a large urban sewershed (UW; n=2), urban wastewater treatment plant (WW1; n=3), rural hospital sewershed (HW; n=2), and  rural wastewater treatment plant (WW2; n=2). DNA was extracted and quantified using Microbial DNA qPCR Array (Qiagen), corresponding to 90 ARG targets. Select ARG targets were chosen from the screening, with a focus on ?-lactamases (bla), to quantify using droplet digital PCR (ddPCR).

Results: 71 of the 90 ARG targets were detected in at least one of the sites tested using the qPCR screening. Average ddPCR concentrations (gene copies/100 ml) were determined to be blaCMY-2 (1.87x106), blaCTX-M (2.94x106), blaNDM (4.92x102), blaOXA-48 (3.74x106), blaTEM (1.68x107), mcr-1 (2.51x102) and tetW (1.42x109).blaNDM and mcr-1, considered superbug genes resistant to last-resort antibiotics, were detected at UW. On average, WW1 was found to have 2 log higher ARG concentrations than WW2, notably for blaCMY-2 and blaOXA-48, which may be indicative of differences in population or antibiotic usage between areas. blaTEM (an ESBL target) and tetW were comparable between sewershed sites and treatment plants. Penicillin and Tetracycline are commonly used livestock antibiotics which may account for their similarities despite population differences. Positive results from the urban sewershed and the hospital site suggest that domestic wastewater is a major source of ARGs of concern. ARG concentrations were within the same log at both sites. The urban watershed was positive for 79% of ARGs tested, while the rural hospital was only positive for 63% of ARGs. This highlights the higher diversity spread of genes in urban environments.

Conclusions: A variety of ARG targets can be screened from wastewater using molecular methods. These results highlight the importance of ARG surveillance and the monitoring of wastewater sources as it is recycled for agricultural use and put back into waterways.

Tracking Norovirus in Tri-County Detroit, MI, Using Wastewater Testing, Syndromic Data, and Online Publicly Available Sources

Poster #13

Author: Heidy Peidro Guzman, Liang Zhao, Michael J Swain, Russell A Faust, Irene Xagoraraki

Bio: Heidy Peidro Guzman is a Postdoctoral Research Associate in the Environmental Virology lab under the supervision of Dr. Irene Xagoraraki at Michigan State University. Her work has been focusing on wastewater surveillance projects with the Michigan Department of Health and Human Services, the Great Lakes Water Authority, and local health departments. Heidy has used molecular microbiology laboratory techniques, statistical models and visualization methods to monitor infections of existing and emerging human communicable diseases in wastewater.

Contact: peidrogu@msu.edu

Human norovirus (HuNoV), the leading cause of acute gastroenteritis in the U.S., is voluntarily reported to the U.S. Center for Disease Control and Prevention (CDC) when infected individuals do not require hospitalization. Wastewater surveillance can be valuable in monitoring HuNoV trends and complementing under-reported clinical data. In this study, wastewater samples were collected between January and December 2023 from three interceptors in Tri-County Detroit, Michigan. HuNoV genogroup I (GI) and genogroup II (GII) were quantified, and the highest concentrations were observed during the winter season. HuNoV GI and GII and their sum were normalized by water quality parameters and fecal indicators. Pearson correlation and dynamic time warping (DTW) analysis were implemented to compare wastewater viral concentrations, in normalized and non-normalized scenarios, with clinical and online data sets. Using the DTW method, HuNoV concentrations in wastewater normalized by fecal indicators and norovirus-positive PCR detection rates in the Midwest U.S. (NPM), followed by Google Trends for “norovirus”, demonstrated the most similar patterns. This study highlights the importance of using multiple data sets, including wastewater surveillance, to identify disease trends, especially for under-reported diseases.

Assessments of fecal indicator organism concentrations and microbial source tracking markers in tributaries and groundwaters of the Mitchell Creek watershed

Poster #14

Author: Rebecca Riggi, Sarah U’Ren, Heather Smith, Christine Crissman, Joan Rose       

Bio: Rebecca Riggi received her Bachelor of Science and Master of Science degrees from Michigan State University. For twenty years, she has worked at Michigan State University on the detection of microbes in natural and built environments, with a focus on pathogenic organisms and fecal indicator organisms used for quantitative risk assessments. Rebecca frequently works with environmental consulting agencies on reduction assessments for current and planned treatment systems as well as with community members, academic agencies, government agencies, and non-governmental organizations to help protect and improve water quality.         

Contact: ivesrebe@msu.edu

Goals: Mitchell Creek in Grand Traverse County, Michigan (USA) is listed as impaired for bacterial contamination on the State’s Impaired Waters List.  The study objective was to use culture based microbial indicator data and molecular microbial source tracking (MST) to identify areas and strategies for water quality improvement.

Methods: Samples were collected between 7/12/2021 and 5/9/2023 from 10 surface water sites and five groundwater monitoring wells. Surface water was collected during four wet weather and four dry weather events and groundwater collected in two sampling events. Surface water samples (n=36 dry, n=38 wet) were analyzed for cultivable fecal indicators (E.coli, somatic coliphage, and Clostridium perfringens) and 57 samples (47 surface water, 10 groundwater) analyzed for MST markers (human, bovine, porcine, gull, and canine).

Key Findings: Levels of E.coli were elevated throughout the watershed during both wet and dry weather sampling events with alternative fecal indicator organism concentrations consistent with a mix of aged and fresh fecal material. 100% of surface water samples were positive for E.coli presence, with 64.6% of the samples exceeding the State of Michigan water quality standard. Somatic coliphage and Clostridium perfringens were detected in 95% and 100% of the surface samples, respectively. The canine, porcine, human HF183, bovine, and gull markers were detected in 94%, 53%, 26%,4%, and 3% of the surface water samples, respectively.  The porcine marker was predominantly detected in the western tributaries, while the human marker was detected more frequently in the central main branch.  The canine marker was widespread in all tributaries. The bovine and gull markers were rarely detected in the watershed. Rainfall was consistently associated with elevated levels of fecal indicator organisms.  However, across the duration of the study, consistent sources or locations of contamination were not identified across sampling events, indicating periodic inputs from a variety of sources rather than systemic contamination from particular human or agricultural activities.  Due to the rural characteristics of the sampling locations, the canine marker is likely coming from wild canids (fox, coyote) in these samples instead of domesticated dogs.

Conclusion.  Non-point sources of fecal contamination can be difficult to address in impaired watersheds. Multiple small individual events can accumulate to produce levels of fecal impairment that are associated with increased human health risks. Recommendations for watershed management were produced from this study for incorporation into the Grand Traverse Bay Coastal Watershed Plan. These include supporting the use of “Generally Accepted Agricultural Management Practices” (GAAMPs) and Best Management Practices (BMPs); providing septic system education on maintenance, right-sizing, replacing aged systems, and proper use; continuing maintenance on existing sanitary sewer systems and extension of sewerage service where possible; and preservation of forested and vegetated wetlands.

Unsafe and Unequal: Investigating Environmental (In)Justice in Metro Atlanta’s Community Drinking Water Systems

Poster #15

Author: Angelique B. Willis, Richard Milligan, Sarah Ledford, Chetan Tiwari 

Bio: Angelique Willis is strongly committed to leveraging her expertise in Geography, Public Health, Environmental Health, and Geographical Information Systems to enhance drinking water quality and safeguard human health. Her work focuses on the unique drinking water challenges faced by low-income communities and communities of color, where systemic inequities often exacerbate these issues. Her approach involves mapping drinking water quality disparities and conducting studies to assess associated health impacts. Ultimately, she strives to create sustainable solutions that resonate locally and nationally, advancing environmental justice and improving public health outcomes.

Contact: willis97@msu.edu

In the U.S., research highlights a persistent injustice in drinking water quality violations, revealing how disparities in clean water access are closely tied to socioeconomic and demographic characteristics. This interplay underscores a troubling pattern of environmental injustice, where minoritized communities often face significant challenges in accessing safe drinking water due to historical and structural inequities. However, there is a substantial gap in research regarding drinking water disparities in metro Atlanta, particularly in relation to socioeconomic and demographic factors. This study investigates two key questions: (1) What is the distribution of water quality violations across various water service areas served by community water systems in metro Atlanta counties? and (2) Is there an association between water quality violations and the socioeconomic and ethno-racial characteristics of each water service area? To address these questions, we analyzed water quality violations of community water systems regulated under the Safe Drinking Water Act (SDWA), using regression models that incorporate average Social Vulnerability Index (SVI) Themes from block groups contained in water service areas and SDWA violation data. Our findings indicate a significant positive association between community vulnerability and water quality violations (p = 0.04) after controlling for population size. Specifically, socioeconomic vulnerability and the population size of the water service area significantly influence water quality violations, demonstrating that drinking water quality disparities are systemic rather than incidental. These findings emphasize the need for policies confronting structural inequities in water management and environmental governance. Ensuring equitable access to safe drinking water requires a multi-pronged approach that strengthens regulatory oversight, prioritizes infrastructure investments in vulnerable communities, and amplifies community voices in decision-making processes. Thus, addressing persistent drinking water quality disparities demands cross-sector collaboration where science, policy, and community engagement work in tandem to drive meaningful change.

Expanding Wastewater Surveillance Capacity to Monitor for Respiratory Viruses of Concern in Michigan, USA

Poster #16

Author: Nishita D'Souza, Spencer Kuehn, Rebecca Riggi, Wenjing Ren, Joan B. Rose 

Bio: Nishita D’Souza is an Assistant Professor-Research in the Department of Fisheries and Wildlife at Michigan State University (MSU). Her research focuses on a One Health approach, applying culture, molecular based environmental and water quality monitoring tools to understand the burden of human pathogens; improve the safety of water, sustainability of resources and monitoring for public health impact. Dr. D’Souza works with the Michigan Network for Environmental Health and Technology (MiNET) and partners at the State of Michigan, MDHHS and EGLE to support funding acquisition, method optimization, quality assurance procedures, laboratory training and troubleshooting, data analysis and dissemination.

Contact: dsouzan1@msuedu

Goals

The COVID-19 wastewater surveillance (WS) program in Michigan facilitated capacity building to develop complementary public health approaches to monitor viral infections in  communities. Leveraging existing capacity for COVID-19 monitoring allows framework to expand surveillance to other viral infections of public health concern; particularly in rural, indigenous communities where there maybe limited capacity for clinical surveillance. This study details the adaptation of the SARS-COV-2 WS framework to expand testing to Respiratory Syncytial virus (RSV), Influenza A, Influenza B and Influenza H5 monitoring in Michigan.

Methods

Wastewater samples were collected from three lift station sewer sites and one WWTP site serving an indigenous community in Michigan. A total of 583 samples were collected (January 2023- September 2024). Virus concentration was carried out using PEG precipitation-centrifugation and RNA was extracted (Flood et al, 2021). SARS-CoV-2 (Flood et al, 2021), RSV, Influenza A, B and H5 markers were quantified with GT Molecular ddPCR Wastewater Test kits. Droplet digital PCR was performed using Bio-Rad’s 1-Step RT-ddPCR Advanced kit.

Key findings

SARS-COV-2 was detected in 59% (346/583) of the samples, at all sites. RSV positivity was 4% (8/191), Influenza A positivity was 8% (9/111) and Influenza B positivity was 1% (1/111). Monitoring for Influenza was during an Influenza H5 outbreak in Michigan in Spring 2024. A subset of samples were tested for Influenza H5 and 29% (4/14) were positive (3.23x102-1.85x104 copies/100mL). RSV was monitored in Respiratory season 2023 through Summer 2024 and Influenza in Spring-Summer 2024. Overall, SARS-COV-2 trends showed some sustained surges in Spring 2023 and Summer 2024 across the community. Lower detection rates of RSV and Influenza B were observed in this community. Influenza A positives detected in May-June 2024 warranted further characterization which provided focused surveillance of Influenza A and H5 in an area of concern. Additional investigation is necessary to detail the source of Influenza A and H5 signals in wastewater.

Conclusions

WS can be applied as a valuable tool for viral outbreak response management, for SARS-CoV-2 and other viral pathogens. The implementation of a WS strategy is suggested in areas where clinical data and resources are limited, where there is underrepresentation of asymptomatic individuals tested and amongst vulnerable populations. The study emphasized the importance of capitalizing on existing WS framework to broaden testing for pathogens of pandemic potential. Adapting current frameworks to mobilize testing for respiratory pathogens of concern such as Influenza A and H5 helped inform outbreak mitigation strategies. 

Food, Energy, and Water

Unstructured Grid Hydrodynamic Modeling for Flood Resilience and Sustainable Water Management in the Middle Mississippi River

Poster #17

Author: Muhammad Bilal Zafer, Dr. Phanikumar Mantha

Bio: Muhammad Bilal Zafar earned a master’s degree in civil engineering with a focus on Water Resources from Michigan State University (MSU) and is currently pursuing a Ph.D. in Water Resources at MSU under the supervision of Dr. Phanikumar Mantha. His research centers on hydrodynamic modeling and extends into water quality analysis to investigate the movement and effects of nutrients and other substances within aquatic systems. By integrating computational modeling with field-based observations, his work enhances understanding of complex environmental processes and contributes to crafting practical solutions for water resource management and policy formulation.

Contact: zafarmu2@msu.edu

Flooding poses a significant threat to ecosystems, communities, and infrastructure, requiring proactive management strategies and data-driven policy development. Traditional flood mitigation approaches have often been reactive, leading to unintended long-term consequences. This study aims to enhance flood resilience and sustainable water management through the application of a two-dimensional unstructured grid hydrodynamic model, providing a robust framework for predicting, assessing, and mitigating flood risks in large river systems. A key objective is to evaluate the model’s reliability in simulating historical flood events and its potential application for exploring levee construction, channel modifications, and climate-driven flood frequency changes.

The study applies the SRH-2D model to simulate major flood events on the Middle Mississippi River (MMR), focusing on extreme floods in 2011 and 2019, as well as a moderate flood event in 2022. The model domain covers a 314-km reach between St. Louis, Missouri, and Thebes, Illinois, incorporating high-resolution topo-bathymetric data. Model performance was evaluated using USGS gauge data from multiple stations and satellite-derived flood extents from Planet Labs Dove satellite imagery. Additionally, sensitivity analyses were conducted on Manning’s roughness values and topography-bathymetry resolution to assess their influence on simulated flood extents and water surface elevations.

Model simulations demonstrated strong agreement with observed discharge and water surface elevations (R² = 0.92–0.99) across nearly a decade of flood events, confirming the reliability of SRH-2D for long-term flood assessments. Comparisons with high-resolution satellite imagery further validated the model’s capability to accurately predict flood inundation extents. The sensitivity analysis revealed that variations in roughness coefficients and bathymetric resolution significantly impact hydrodynamic predictions, underscoring the need for accurate input data in flood modeling. The ability to integrate nested modeling approaches enhances its utility for both regional-scale flood planning and localized policy applications.

By integrating hydrodynamic modeling, remote sensing, and policy-driven analysis, this study provides actionable insights for flood resilience, sustainable water management, and infrastructure planning. The findings underscore the importance of science-based decision-making in managing flood risks while balancing human and environmental needs. This research aligns with the symposium’s mission by bridging modeling, observation, and policy to advance interdisciplinary solutions for pressing water challenges.

Innovative Framework for Assessing Agricultural Resilience Across Economic Classes in Diverse Climate Scenarios

Poster #18

Author: Kieron Moller, A. Pouyan Nejadhashemi, Mohammad Tirgaris, Nilson Vieira Junior, Ana Julia Paula Carcedo, Ignacio Ciampitti, P. V. Vara Prasad, Amadiane Diallo

Bio: Kieron Moller is a PhD student at Michigan State University in the Biosystems and Agricultural Engineering department. He specializes in agricultural development for low-income countries in the face of climate change. He specifically researches improving smallholder farmer resilience in Senegal by altering their planting dates, plant densities, and fertilizer rates. He evaluates the alternative agricultural practices using economic, nutrition, and risk data to holisticly understand the complex nature of agriculture in low-income countries.

Contact: mollerki@msu.edu

Climate change presents a substantial threat to agriculture in Senegal, a critical concern given agriculture’s pivotal role in the livelihoods of the country’s population. Furthermore, the effects of climate change—such as droughts, floods, heatwaves, and rising temperatures—extend well beyond agriculture, impacting human health, incomes, and livelihoods. These changes also exacerbate issues related to diseases, pests, food costs, and environmental degradation. The study focuses on farmers of varying economic classes who practice mixed farming of pearl millet (Pennisetum glaucum (L.) R. Br.), groundnut (Arachis hypogaea L.), and livestock in Senegal’s Groundnut Basin under dry, wet, and average climate conditions. This work aims to build on past research to further establish the resilience of farmers in connection with their economic class. Resilience is assessed using an innovative approach involving the development of a regression model to evaluate various variables and quantify their impacts on farmers. Therefore, surveys, organizational databases, scientific papers, and reports from government and nongovernmental organizations were utilized to collect data. This included demographic information, consumption behavior, economic metrics, and farm characteristics, which were incorporated into the models and the approach for determining resilience. A crop model APSIM (Agricultural Production Systems sIMulator) was utilized to see how combinations of three planting dates and three planting densities impact pearl millet yield, which was then used in the Farm Simulation Model (FARMSIM) to generate economic, nutrition, and risk data. The generated data was used in a resilience recovery analysis to determine how farmers of different economic classes perform compared to their baseline current practices under dry, wet, and average precipitation conditions. The economic classes’ resilience was also evaluated by comparing average conditions against dry and wet conditions. The regression analysis determined that higher education and income generally result in higher resilience and recovery. Additionally, the resilience results showed that climate variability impacts do not follow a simple script. In fact, there are scenarios where economically disadvantaged farmers display remarkable resilience, outpacing their wealthier counterparts. Conversely, there are instances where wealthier farmers fare better. This underscores the diverse nature of resilience among farmers, showing how economic status shapes their ability to adapt and recover. As a result, this study provides insights for tailoring policies to support farmers equitably across economic groups.

Evaluation of the Effects of Reservoir Tillage Practice on Water Conservation in irrigated Michigan potato fields

Poster #19

Author: Abraham Rai, Younsuk Dong, Kurt Steinke, Tim Harrigan

Bio: 

Contact: raiabrah@msu.edu

Effective irrigation management is crucial for potato production, as irrigation significantly influences both yield and quality of tubers. The crop’s shallow root zone, combined with daily evapotranspiration, makes precise irrigation challenging with severe water stress potentially reducing  yields by up to 52%.  The potato production in Michigan for the growing season 2023 accounted for about 5.2% of the U.S. total generating about 21.26 million cwt of potatoes, which is a 10% increase from 2022. The recent climate changes, erratic and intense precipitation, with temperature fluctuations, pose a risk to potato quality and yields, as well as irrigation management. Reservoir tillage is one of the techniques that can be employed to mitigate the effects of erratic and intense precipitations. In Michigan, reservoir tillage practices have not been well evaluated and implemented thus, the goal of this study is to examine the effects of the reservoir tillage practice on a cooperative farm in Michigan and evaluate the effect Reservoir Tillage has on Runoff, Sediment, Soil Moisture Content, and Yield. The research consists of two treatments: 1) Control, standard tillage, and 2) Reservoir Tillage, which utilizes Dammer-Diker; with each treatment being replicated four times. Teros 12 sensors were installed at 9-, 18-, and 24-inch depths to monitor soil moisture, temperature, and electrical conductivity on the ridges and depressions of each treatment. Runoff was measured using customized flumes and buckets, with a metal plate installed at an upgradient of 50 ft. from the collection point to maintain consistency in collection of runoff and sediments from each treatment area. The results revealed runoff volume (P-value = 0.017) and sediment (P-value = 0.001) from the control were significantly higher than reservoir tillage. The field monitoring data from 2024 revealed reservoir tillage reduced runoff volume by 56%, and sediment weights by 67%, as compared to the control treatment. Furthermore, reservoir tillage improves retaining water within the field, which was confirmed by soil moisture sensor data indicated by higher soil moisture levels observed throughout the growing season in the reservoir tillage areas as compared to the control areas. The yield comparisons between the treatments revealed reservoir tillage treatment maintain consistent yields as compared to control treatment; this consistency in yields for the reservoir tillage suggests greater reliability of potato production. Overall, the reservoir tillage practice reduced the runoff volume, and sediment transport as well as improved soil moisture retention, contributing to stable potato yields and water conservation.

Protecting the Environment: Developing Guidance to Support Sustainable Wastewater Treatment for Small Meat Processors

Poster #20

Author: Gregory Rouland, Younsuk Dong

Bio: Gregory Rouland is a 2nd year Ph.D student at Michigan State University. Born and raised in Michigan, he received his undergraduate degree in Biosystems Engineering from MSU before continuing with graduate school. His research is focused on the understanding and sustainable treatment of food processing wastewater, typically from small meat processors and slaughterhouses. His previous work was characterizing the wastewater of 6 different processors in Michigan, his current and future work is focused on the sustainable treatment and land application of this water. He also has a strong focus on community outreach in his research and works towards ensuring these businesses can implement his work. 

Contact: roulandg@msu.edu

From the 1980s to the present, the market share of the top four producers in the meat processing industry has increased from approximately 35% to 67 - 81% depending on the animal source. This has led to the difficulty of small meat processors, defined by the USDA as having 499 employees or less, staying competitive in the industry. Of all 7,093 USDA-Inspected facilities in the country, 5,757 of these are in the small category, not accounting for the many custom-exempt processors working towards inspection status. Each of these facilities is a crucial component of their local economies for both residents and farmers. Environmental regulation for these facilities can vary between states but must follow a baseline level of treatment established by the EPA. In Michigan, the department of Environment, Great Lakes, and Energy (EGLE) governs this permitting. Many processors in Michigan are facing issues affording the treatment necessary to meet the requirements of GP1530000, a general permit for small processors . Previous work that characterized the wastewater of a set of six facilities in Michigan and found that none of the 6 facilities were able to fully meet the permit requirements, specifically a limit on total inorganic nitrogen at 10mg/L-N for land applying. Other facilities have had to shut down due to an inability to afford treatment. Based on discussion with multiple facility managers, there is a major demand for guidance on what solutions may be available to pursue. Therefore, the goal of this project is to create guidance for facility managers on what technologies are available and work best with their unique situation. Potential solutions include improving existing systems, such as septic tank filters and biological treatment lagoons. If that is not feasible or possible then other pre-treatment technologies including coagulation and flocculation, constructed wetlands, and greenhouse ecosystem units are all considered as possible additions to the system. This guidance begins with a series of questions that facility owners and managers can ask themselves when considering their treatment options. After answering these questions, the pros and cons of each alternative are presented so that informed decisions can be made that are both environmentally and economically sustainable.

Spatio-temporal heterogeneities in hydrologic dynamics across the Asian Water Tower

Poster #21

Author: Saugat Aryal and Yadu Pokhrel

Bio: Saugat Aryal is a Civil Engineering PhD student at Michigan State University, specializing in large-scale hydrological modeling. After earning his bachelor's degree from Tribhuwan University in Nepal with distinction, he focused his research on understanding hydrological dynamics in the Asian Water Tower. As a Graduate Research Assistant under Dr. Yadu Pokhrel, he works with advanced models like CaMa-Flood and CLM5. Aryal has published multiple peer-reviewed papers on hydropower and hydro-climatic extremes and holds a prestigious National Science Foundation fellowship through MSU's WaterCube program. His expertise spans hydrological modeling, GIS, and programming, with professional engineering licenses in Nepal and the United States.

Contact: aryalsau@msu.edu

The Asian Water Tower (AWT), encompassing ten major river basins, is crucial in supporting biodiversity and sustaining over 2 billion people. However, climate change and human activities are significantly altering its hydrological dynamics, posing water security and ecosystem stability challenges. Despite extensive research, a comprehensive understanding of the AWT’s long-term hydrological changes remains limited, particularly regarding the spatiotemporal variations across its diverse basins. This study aims to address this gap by conducting a multi-decadal analysis of hydrologic changes across the entire AWT region, focusing on river discharge, water storage, inundation patterns, and Terrestrial Water Storage (TWS). Using high-resolution integrated hydrological-hydrodynamic modeling, combining HiGW-MAT and CaMa-Flood models, we simulated hydrological processes from 1979 to 2018 at approximately 5 km resolution. Our analysis reveals important spatiotemporal heterogeneity in hydrological trends across the AWT basins, including diverse changes in river discharge, water storage, flood regimes, and TWS dynamics. We observed unexpected patterns such as increased water storage in arid regions and shifts towards more intense flooding events in several basins, while identifying varying drivers of TWS across the region. These findings highlight the complex interplay of surface and subsurface processes in the AWT, underscoring the need for basin-specific approaches in water resource management and climate change adaptation strategies.

Do EV Charging Stations Care about Electricity Rates?

Poster #22

Author: Jae-Yu Jung

Bio: Jae Yu Jung is currently a Ph.D. student at Michigan State University. His main research focus is environmental economics including the effect of new electricity rates on EV charging stations.

Contact: jungja10@msu.edu

This paper investigates the relationship between electricity rate plans and the installation of EV charging stations. Public charging stations are likely to draw a lot of electricity in a short period. As a result, they will face high demand charges even though they have few customers. Some utility companies have introduced electricity tariffs dedicated to EV charging stations to relieve this burden.

I constructed a zip code by quarter level panel using two primary datasets: (1) the number of EV charging stations in the contiguous state from 2015 to 2022, imported from the Monthly Energy Review, and (2) commercial electricity tariffs of investor-owned utility companies in the United States collected from the US Rate Database, webpages of utility companies and public utility commissions. 

This study employs the local projection difference in differences method and the synthetic control difference in differences method to estimate the impact of newly introduced EV-related electricity tariffs on EV charging station entries. These methods are particularly effective in the presence of staggered interventions and when dynamic effects are of interest. The results show that introducing EV-dedicated tariffs led to the installation of approximately two additional charging port.

This paper makes two contributions. First, it emphasizes the importance of electricity costs in EV charging station installation decisions. Previous literature primarily focused on fixed installation costs. Second, it adds another implication to the existing literature that has studied how demands for electronic devices, such as heat pumps, react to electricity rates.