Rowan granted $260K for AI analysis of hazardous landfills impacted by climate change


Rowan University was recently awarded a $260K grant from the U.S. Department of Agriculture. The grant permits the building of a virtual reality that uses artificial intelligence (AI) to simulate the behaviors of landfills under various environmental conditions exacerbated by climate change.

Landfill liners have become susceptible to breaking given the changes in the climate. Warmer temperatures in winter months and heavier storms throughout the year equal waste leaking out of landfills and into watersheds. 

According to the United States Environmental Protection Agency (EPA), a great majority of polluted streams, rivers, and lakes in the country stem from pollution in their watersheds, which is the land area that surrounds and drains into the waters.   

Gloucester County alone has 13 hazardous waste sites according to the State of New Jersey Department of Health, with nine of those locations being considered a superfund site. Locations being dubbed a superfund site mean that affected areas contain hazardous waste and must be cleaned because they pose risks to human health and the environment.

Given the ability to simulate landfills in various environmental conditions affected by climate change, town officials can take steps to mitigate potential problems and improve their community’s water quality. 

Researchers will use satellite imagery of landfills, temperature and gas at various depths from wells drilled in the landfills, groundwater from nearby wells, and surface water measurements in the vicinity of the study area to collect the data needed to create watershed models and program the AI that will go alongside it.

The research team will also develop an analysis tool to assess water resources if extreme flooding were to release waste from landfills into the water resources that can be trained to landfill staff in helping maintain active landfills.  

In the wake of this project, researchers will study landfills in economically disadvantaged communities.

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