Interdisciplinary, Scalable Solutions for a Sustainable Future Project
Background and Purpose
The Interdisciplinary, Scalable Solutions for a Sustainable Future (ISSSF) project is funded by the Office of the Provost, Provost Investment Fund.
The primary aims for this project are to:
- Promote the University of Iowa as an important destination for research and teaching in the environmental and sustainability sciences.
- Enhance the competitiveness of UI researchers as they seek large interdisciplinary grants.
- Engage faculty, graduate students and undergraduate students from across campus in research focused on sustainability.
The projects below were funded through the Interdisciplinary, Scalable Solutions for a Sustainable Future Project. ISSSF grants provide seed funding for the development of major external grant proposals in the environmental and sustainability sciences. The project is supported by the Office of the Provost, Provost Investment Fund and administered by the Office of Sustainability and the Environment.
Total funding distributed 2019-2023: $296,500
Hyperspectral satellite remote sensing: The new tool for detecting harmful algal blooms (HAB) events in Iowa’s lakes ($39,113)
Principal Investigators: Susan Meerdink (Geographical and Sustainability Sciences, University of Iowa); Mary Skopec (Iowa Lakeside Laboratory)
Harmful algal bloom (HAB) events are becoming increasingly common and threaten Iowa’s valuable lake resources in the closure of beaches, degradation of drinking water quality, and increasing health risks (IDNR, 2022). In the context of sustainability, the development and persistence of HABs fall into two of the World Health Organization (WHO) Sustainable Development Goals to ensure healthy lives and promote well-being for all ages and ensure availability and sustainable management of water and sanitation for all. Thus, the early detection of a HAB event can reduce the public health risk to recreational users and protect drinking water sources. Current monitoring of Iowa HABs occurs only at 39 state-owned beaches and is completed once a week with a water sample (IDNR, 2022). This approach does not capture the spatial and temporal variability of lake HABs, limiting the ability to determine the appropriate public health risk for recreation and drinking water. Here, we propose to explore hyperspectral satellite remote sensing’s ability to capture the dynamic nature of HAB development and compare it to existing HAB products. We will evaluate the use of the newly launched hyperspectral satellite, EnMap, for detecting the spatial and temporal heterogeneity of HABs in Iowa’s Big Spirit Lake. We will develop monthly sub-pixel HAB extent maps using hyperspectral satellite imagery and contrast them with commonly used multispectral satellite-derived HAB products. We will address these specific aims by conducting a HAB sampling campaign on Big Spirit Lake four times during the summer of 2023 to capture the HAB development throughout the season. We will coordinate these sampling campaigns to match EnMap overpasses so that the imagery will align with the water sampling results. During at least one field campaign, we will also collect airborne hyperspectral imagery to help facilitate the validation of EnMap imagery. Together, these analyses will provide insights into how satellite imagery can be used specifically for Iowa’s lakes, which represent very different geology, wave dynamics, and geographic patterns than other large lakes.
Watershed-Level Multi-Criteria Quantification of Agricultural Sustainability for Iowa ($39,943)
Principal Investigators: Ibrahim Demir, PhD (Civil & Environmental Engineering, IIHR Hydroscience & Engineering, University of Iowa); Ozlem Baydaroglu, PhD (IIHR Hydroscience & Engineering, University of Iowa); Serhan Yesilkoy, PhD (IIHR Hydroscience & Engineering, University of Iowa)
Climate projections have indicated that climate change will have a long-term influence on temperature, precipitation, and wind patterns, as well as other atmospheric parameters. The most severe problems that people will encounter as a result of this change will be water and food scarcity. Sustainable agriculture will become increasingly crucial as water scarcity causes drinking water shortages and makes agricultural irrigation more challenging. Agricultural sustainability is a phenomenon that consists of environmental, social and economic factors. From an environmental standpoint alone, it can be easily seen that modeling sustainable agriculture is a very complex and difficult task, as water distribution, land features, crop diversity, and geographic conditions on watersheds are not uniform both in time and space. In this regard, in this project, we aim to (1) identify the most effective factors that affect sustainable agriculture, namely climate-resilient agriculture, in Iowa farmland; (2) determine representative subregions of Iowa; and (3) develop a multi-criteria, multi-index, adaptive agricultural sustainability quantification methodology based on identified factors and indicators for these subregions (4) generate an agricultural sustainability index for the MiddleCedar Watershed as a pilot study. With this project, we will provide a multidimensional perspective for agricultural sustainability, develop an adaptive quantification methodology, and create a state-based agricultural sustainability map that will be a model for the other regions in US.
Using Contaminants of Emerging Concern to Trace Groundwater-Surface Water Exchange in a Wastewater Effluent Dominated Stream ($40,000)
Principal Investigators: Jessica Meyer (Assistant Professor of Earth & Environmental Sciences, University of Iowa); Gregory LeFevre (Associate Professor of Environmental Engineering, University of Iowa)
Climate change and urbanization are increasing the influence of municipal wastewater effluent on receiving waters, making wastewater effluent-dominated streams common worldwide, including in temperate regions. This phenomenon increases loading of contaminants of emerging concern (CECs) including pharmaceuticals, personal care products, pesticides, and industrial chemicals from wastewater treatment plants (WWTPs) to drinking water supplies (i.e., de facto reuse) and ecological systems. Treated effluent from WWTPs releases CEC mixtures that vary spatiotemporally, generating complex exposure conditions for biota and potential for deleterious interactive effects (e.g., drug-drug interactions). When individual CECs present in mixtures are removed from the aqueous phase at different rates (i.e., differential attenuation), exposure conditions for biota change. Currently, we do not fully understand the role of groundwater-surface water exchange on complex mixture evolution. There is a critical need to evaluate the role of groundwater-surface water exchange as a driver of complex mixture evolution using next-generation high-resolution non-target analytical approaches to quantify CEC spatiotemporal dynamics. The proposed work will occur at Muddy Creek, an established effluent-dominated stream research site in Iowa. We will establish a foundation for greater understanding of the role of groundwater-surface water interactions, including relevant geologic and hydrologic conditions, in complex CEC mixture formation, quantified using state-of-the-art analytical techniques. The overall goal of the work will be to quantify differential attenuation of complex CEC mixtures as a result of interactions between the surface water and groundwater in a temperate-region effluent dominated stream. The specific objectives of this research are to (1) use the more conservative chemicals within the wastewater effluent (i.e., per-and polyfluoroalkyl substances or PFAS) as tracers to elucidate water exchange between the stream and the groundwater in combination with hydraulic data and (2) characterize how CECs evolve when interacting with shallow groundwater in a streambed using targeted analysis of CECs (i.e., pharmaceuticals/pesticides) and high-resolution mass spectrometry (HRMS) non-targeted feature analysis.
UI-ISU Climate Change and Sustainability Innovation Labs ($7,500)
This program is designed to build and support UI interdisciplinary teams focused on the climate-environment-health nexus leading to competitive external funding applications. Through February 4, 2022, University of Iowa (UI) and Iowa State University (ISU) are partnering to host a survey leading to a series of Innovation Labs. The Innovation Labs will connect UI and ISU researchers and networks to generate novel interdisciplinary research ideas, help refine research questions, build interdisciplinary teams, and begin the important task of writing team-based, impactful, winning research proposals. With your involvement, expertise, and enthusiasm, new and exciting paths can be charted for Iowa researchers leading to the capture of climate change and sustainability science research funding.
Sustainable Food Systems and COVID-19: A Mixed-Methods Assessment of Innovations and Strategies ($33,676)
Principle Investigators: Dr. Carly Nichols (Assistant Professor, Department of Geographical and Sustainability Science and Global Health Studies, College of Liberal Arts and Science); Dr. Brandi Janssen (Clinical Assistant Professor, Department of Occupational and Environmental Health Director, Iowa’s Center for Agricultural Safety and Health or I-CASH)
In the wake of the COVID-19 pandemic and resultant social distancing restrictions, the food system has seen unprecedented shifts in consumer demand alongside supply chain bottlenecks that resulted in empty store shelves and consumer fear around the resiliency of the conventional food system (Stephens et al. 2020). The meat and vegetable/fruit supply chains have proven particularly vulnerable due to COVID-19 outbreaks in processing facilities and a lack of farmworker labor due to increased visa restrictions. At the same time, record unemployment claims and school closures have led to sudden economic stress and food insecurity for millions (Bauer 2020). The implications of these bottlenecks within the conventional food system and shifts in consumer demand will slowly become clear throughout the next year and beyond (Ker and Cardwell 2020). Amidst this unprecedented uncertainty, there is reinvigorated interest in local and regional foods as a reliable and sustainable alternative to the conventional food system (Blay-Palmer et al. 2020, Kolodinsky et al. 2020). Local and regional food systems confer multiple sustainability benefits in terms of shorter supply chains, increased local economic benefits, and an increased community accountability that reduces exploitative labor or environmental practices. However, the unique changing structure of demand (e.g. decreased institutional purchases, household buying surges, and increased economic vulnerability) alongside social distancing restrictions has presented novel challenges to local food systems’ normal modus operandi. This offers a unique opportunity to better understand regional food system actors’ responses to COVID-related challenges in order to gain knowledge about food system resilience that will inform both conventional and regional food systems and enhance social, ecological, and economic sustainability as well as crisis preparedness.
A hard rain’s gonna fall: Responses of Iowa’s bur oak to increased precipitation variability ($35,497) *This project received an additional ISSSF funding of $5,771 in the 2022-23 cycle
Principle Investigators: Matthew Dannenberg (Geographical and Sustainability Sciences, GSS); Susan Meerdink (GSS); Mary Skopec (Iowa Lakeside Laboratory); Adam Skibbe (GSS)
Anthropogenic CO2 emissions have warmed the Earth by about 1°C, with further warming a virtual certainty over the next century. Warming accelerates the hydrologic cycle due to higher water vapor holding capacity of a warmer atmosphere, likely leading to increases in precipitation variability across the globe, as vividly seen in the extreme precipitation and flooding of the Midwest in spring 2019. How Earth’s forests, including those in the Midwest, will respond to increasingly volatile precipitation remains largely unknown. Given that forests provide numerous ecosystem services to humanity, understanding how and why forests will respond to changes in the amount and timing of precipitation is a necessary step for sustainable forest management in the face of global change. Here, we propose to examine bur oak responses to a combination of drought and high precipitation variability using precipitation manipulation experiments at Iowa’s Lakeside Laboratory. We will test the hypothesis that increased precipitation variability decreases photosynthetic capacity and growth, including quantification of the physical and physiological drivers of these responses.
Algal Blooms Detection and Forecasting through Smart and AI-Powered UAV System ($40,000)
Principle Investigators: Xun Zhou (UI Business Analytics); Corey Markfort (UI Civil & Environmental Engineering); Ali Jannesari (ISU, Computer Science); Charles Stanier (UI Chemical & Biochemical Engineering)
Harmful algal blooms (HABs), those caused by toxin-producing blue-green algae (cyanobacteria), significantly reduce water quality as well as recreational and ecological value of lakes. HABs degrade fisheries, are a direct health concern for humans through drinking water and contact recreation, and can be lethal for pets, livestock, and waterfowl. HABs may form in large and smaller lakes, wetlands, and farm ponds. HAB events have increased in occurrence in recent years. Yet, little information is available on what factors trigger an outbreak or why a HAB may occur at one lake and not at another. To address these challenges, we propose to develop a novel solution that integrates the latest artificial intelligence (AI) techniques, UAV systems, and dynamical simulation models to jointly and smartly plan, sample, and predict HABs for more accurate and timely decision making.
NSF Dynamics of Integrated Socio-Environmental Systems (DISES) Development Proposal ($7,500)
Principle Investigators: Marc Linderman (Department of Geographical and Sustainability Sciences); Jerry Anthony (Urban and Regional Planning); Matthew Dannenberg (Department of Geographical and Sustainability Sciences); Carly Nichols (Department of Geographical and Sustainability Sciences
More than 1.2 billion people live in arid and semi-arid regions around the world. Precipitation dynamics and uncertainty can have significant impacts on agricultural decision-making and yields. As a result, these households are often income and food insecure. This uncertainty and limited resources often ties households more directly to the environment relying on biomass for cooking, subsistence agriculture, and agricultural day-labor. This, in turn, leads to strongly coupled systems in which households affect the environment and are strongly impacted by environmental feedback processes. We propose to bring together an interdisciplinary group across the University of Iowa to improve our funding competitiveness centered on household-level decision-making and the sustainability of human-environment systems in marginal lands. At the intersection of the interactions of people and the environment are household-level decisions. Household decisions related to food, agriculture, and energy choices drive not only individual impacts, but also environmental feedbacks on households. This is particularly true in marginal lands where the amount and timing of precipitation and availability of water can be driven by landscape level vegetation characteristics and land use. Funding will be used to support student research and strengthening collaborative partnerships with universities and researchers in India. Student-led research will provide initial findings to strengthen potential proposals. Collaborative research will increase available initial data and research.
Preparing for the Unknown: Assessing factors that impact community response, recovery, and sustainability in the face of disasters ($7,500)
Principle Investigators: Dr. Elise Pizzi (Department of Political Science); Drs. Kylah Hedding (School of Journalism and Mass Communication); Kajsa E. Dalrymple (School of Journalism and Mass Communication)
Local communities are on the front lines in responding to natural disasters, climate events, and other social disasters such as pandemics. Although state and federal governments can support recovery, the preparation and immediate response to natural disasters rely on local governments. Some communities are better prepared to face natural disasters than others. We intend to explore this variation and respond to questions including what types of policies allow communities to respond quickly and effectively to natural and social disasters? When in the midst of these crises, how do individuals process risk information to inform their safety decisions? How are marginalized communities represented and their needs incorporated in disaster preparedness plans? Broadly, the goal of this project is to understand the variation in disaster preparedness at the local level. To answer these questions and achieve this goal, we propose a mixed-method approach to collect pilot data on disaster response and communication plans from seven Iowa counties recently affected by natural disasters. Collecting these data will improve the competitiveness of a proposal submitted to the National Science Foundation’s (NSF) Accountability Institutions and Behaviors (AIB) and Decision, Risk and Management Sciences (DRMS) programs which will be used to fund data collection on all 99 counties in Iowa. We intend to expand this project regionally to states along the Mississippi River Basin, eventually expanding nationally across the United States. The University of Iowa will be the lead for this regional/national project, collaborating with colleagues at flagship universities across the nation and drawing attention to our strength in interdisciplinary approaches to studying sustainability. In addition to its academic merit, lessons from this project will help local governments improve their communication strategies and capacity to respond to natural disasters and other crises.
Sustainable air quality: tracking aeroallergens across urban and rural environments ($40,000)
Principle Investigators: Elizabeth Stone (Associate Professor, Department of Chemistry and Department of Chemical and Biochemical Engineering, University of Iowa); Thomas Peters (Department of Occupational and Environmental Health, College of Public Health, University of Iowa)
Air quality is essential to public health and is increasingly challenged by population rise, urbanization, and climate change. Our long-term goal is to understand how natural and built environments impact air pollution, aeroallergen concentrations, and human respiratory health under changing climatic conditions and extreme weather events. The objective of this seed grant is to develop low-cost, scalable methods to quantify airborne pollen and mold spore concentrations with high spatial resolution. Our first aim centers on developing a novel method to quantify these aeroallergens. We will use passive sampling to collect aeroallergens by gravitational settling and inertial impaction, light microscopy to identify allergen type and size, and deposition velocity modeling to quantify airborne concentrations. We will assess the accuracy of the method against traditional pollen and spore counting and establish the method precision with co-located samplers. Our second aim will demonstrate the capabilities of this new method to characterize the spatial distribution of pollen and mold spore concentrations across an urban-rural landscape. We will test our working hypothesis that aeroallergens are spatially heterogeneous on both neighborhood and city scales, leading to differing exposures across urban populations. Through this aim, we will gain novel scientific insights to the spatial distribution of mold spores on urban spatial scales and will establish the effect of allergen size on spatial heterogeneity. The development, validation, and demonstration of a low-cost and scalable method to quantify aeroallergens is significant, in that it will enable future measurements of aeroallergens over local, regional, and national spatial scales and potentially over long temporal scales by us and other researchers. Scalable methods, such as these, are essential in understanding complex interactions between humans and natural and urban landscapes and to support sustainable air quality for current and future generations.