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Orner Research Group
Environmental Engineering & Sustainable Development

Research

Developing, Demonstrating, and Assessing Innovative Technologies for Safe, Contextually-Appropriate Resource Recovery

Treatment system for animal manure that also recovers nutrients, energy, and water. Shows pigs and cows, struvite reactor, digestor, and lagoons.

Our research group develops innovative, safe, context-specific, and culturally-appropriate resource recovery technologies that improve water quality. These technologies can recover resources such as nutrients, energy, and water from multiple organic waste streams to promote food security and energy production. Additionally, we develop decision-making frameworks that engineers and development practitioners can use to integrate all the pillars of sustainability. These resource recovery technologies and decision-making frameworks can increase sanitation coverage and reduce contaminants entering the environment while simultaneously providing additional nutrients, energy, and water for communities.

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Integrating Social Context, Health Risk, and Policy into Wastewater Treatment and Resource Recovery at the Building, Community, and City Scales

Our research group develops technologies and frameworks that integrate social context, health risk, and policy alongside more traditional considerations of cost and discharge requirements of treating wastewater and recovering resourcesat multiple scales. Predicting and optimizing resource recovery while reducing health risk and unwanted nutrients and pathogens can increase opportunities to safely and efficiently recover nutrients, energy, and water.

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Holistically managing pathogens and nutrients in urbanizing tropical towns: Can sanitation technologies create safer conditions for beach recreation? Shows balancing priorities between nutrient management and microbial water quality.

Utilizing Data Science to Leverage Resource Recovery and Carbon Capture

Our research group utilizes data science to improve monitoring, evaluation, and performance of wastewater treatment, resource recovery, organic waste management, and carbon capture. Opportunities exist to integrate data from apps, sensors, and participatory community analysis. Likewise, analyzing data using machine learning can translate to improved performance at different scales (building, community, city) with different waste inputs (wastewater, animal manure, food waste) in different contexts (rural and urban, developed and developing) and inform real-time decisions to maintain desired levels of treatment.

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Controller for real-time adjustment of wastewater treatment