Masters Theses

Keywords and Phrases

computer visualization; imaging station; landfill leachate; phenotype; phytoremediation


"Most solid waste collected in the US is disposed of in sanitary landfills, which have a lingering legacy of unintended negative impacts on the environment. Landfill design and operation are expensive, prone to multiple failure modes, and often do not address human and ecological risks presented by contaminants of emerging concern. A notable and common failure mechanism is leachate production. Moisture in the waste mixes with infiltrating water to form wastewater that must be collected and treated prior to discharge. Recycling leachate at landfills by recirculating it onto vegetated landfill covers relies on the evapotranspiration potential of plants to reduce the quantity of leachate produced and promote degradation of waste. Plant and soil cover selection for specific landfills is critical to designing and operating effective, long-term vegetative covers. Plants are selected based on their ability to withstand site-specific stresses. This short term, laboratory study assessed plant stress response to municipal solid waste landfill leachate. On one side, results provide insight in the ability of remote sensing techniques to identify appropriate species and genomes for vegetative covers based on leachate composition. On the other side, they provide guidance in setting up similar studies. Improving methods to rapidly assess species and genome’s ability to withstand toxic conditions works towards addressing the grand challenge of fostering informed decisions and actions for waste management that is efficient and sustainable"--Abstract, p. iv


Burken, Joel G. (Joel Gerard)
Smith, Ryan G.

Committee Member(s)

Wang, Jianmin


Civil, Architectural and Environmental Engineering

Degree Name

M.S. in Environmental Engineering


Missouri University of Science and Technology

Publication Date

Fall 2022


xiii, 339 pages

Note about bibliography

Includes_bibliographical_references_(pages 331-338)


© 2022 Rahel Sofia Nino Pommerenke, All Rights Reserved

Document Type

Thesis - Open Access

File Type




Thesis Number

T 12203