CAREER: Leveraging Data Science & Policy to Promote Sustainable Development Via Resource Recovery

The waste management sector is transitioning from an “out of site, out of mind” approach to a resource recovery approach in which valuable energy and fertilizer can be recovered. This resource recovery approach is driven by national and global challenges related to population growth, climate change, and resource scarcity. Rural agricultural regions are prime locations for resource recovery because they are typically abundant in organic waste streams such as animal manure and agricultural crop residues while also requiring fertilizer for crop production.

Rural agricultural regions may generate so much organic waste that excess waste is shipped to other watersheds. Therefore, these regions could receive increased economic benefits and reduced environmental impacts if the excess waste was not shipped out and instead used as a feedstock for the recovery of energy and nutrients. However, such rural regions face challenges in implementing resource recovery technologies due to limited technical and economic resources, unavailable or inaccessible data, and lack of contextual policy support.

Accordingly, the overarching goal of this CAREER project is to promote sustainable, context-sensitive resource recovery in rural regions. Successful completion of research and educational objectives on the topics of data science, life cycle modeling, policy, and stakeholder engagement will provide a data-driven, cost-effective framework to bridge the gap between research and implementation of resource recovery technologies in rural agricultural regions.

Stakeholder engagement and policy dissemination will facilitate increased adoption of best practices for organic waste management.

Current organic waste management practices such as landfilling and incineration negatively impact the environment by emitting greenhouse gases, harmful contaminants, and pathogens. However, recovery of resources such as energy and nutrients from organic waste can reduce such negative impacts. The goal of this CAREER project is to develop, apply, and assess a data-driven framework that integrates data science, life cycle modeling, and policy analysis to promote sustainable, context-sensitive resource recovery in rural agricultural regions.

The recent emergence of powerful data science tools can effectively predict outcomes such as recovery efficiency, economic impacts, and environmental impacts. While larger wastewater utilities are beginning to use data science methods to improve treatment efficiency and reduce chemical and energy use, the use of data science in rural organic waste management is unexplored.

Therefore, an opportunity exists to utilize data science tools with accessible datasets and generalized methods integrated with stakeholder engagement and contextual policy support. This strategy can provide a data-driven, cost-effective framework to bridge the gap between research and implementation of resource recovery technologies in rural farming regions.

Implementation of this framework could allow rural farming regions nationally and internationally to strategically utilize their organic waste to best reflect their environmental, economic, social, political, and geographical context. The long-term educational goal is to increase the “impact competencies” in civil engineering students by providing training and practice on sustainable development, data science, and policy.

In pursuit of this, the educational objectives of this proposal include integrating undergraduate and graduate learning modules and creating a pathway within the civil engineering MS curriculum that includes one year of stateside community-engaged service integrated with a research thesis. Broader impacts of the educational plan result from stakeholder engagement with community partners in undergraduate and graduate courses and providing needed yet underrepresented skills in data science and policy to undergraduate students that they can use to transition to the marketplace or graduate school.

This project is jointly funded by the CBET/ENG Environmental Sustainability program and the Established Program to Stimulate Competitive Research (EPSCoR).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.