Renewable Energy Production and Urban Remediation: Modeling the biogeochemical cycle at contaminated urban brownfields and the potential for renewable energy production and mitigation of greenhouse gases

Abstract:

Brownfields or urban sites that have been contaminated as a result of historic practices are present throughout the world. In the United States alone, the National Research Council has estimated that there are approximately 300,000 to 400,000 sites which have been contaminated by improper use and disposal of chemicals (NRC 1993). The land available at these sites is estimated at several million acres; however, the presence of high levels of contamination in the soil and groundwater makes it difficult to utilize these sites for traditional purposes such as agriculture. Further, the time required to remediate these contaminants to regulated levels is in the order of decades, which often results in long-term economic consequences for the areas near these sites. There has been significant interest in developing these sites as potential sources of renewable energy production in order to increase the economic viability of these sites and to provide alternative land resources for renewable energy production (EPA 2012). Solar energy, wind energy, and bioenergy from lignocellulosic biomass production have been identified as the main sources of renewable energy that can be produced at these locations. However, the environmental impacts of such a policy and the implications for greenhouse gas emissions, particularly resulting from changes in land-use impacting the biogeochemical cycle at these sites, have not been studied extensively to date.

This study uses the biogeochemical process-based model DNDC to simulate carbon sequestration, nitrous oxide emissions and methane emissions from typical urban brownfield systems in the United States, when renewable energy systems are deployed. Photovoltaic solar energy and lignocellulosic biomass energy systems are evaluated here. Plants modeled include those most widely used for both bioenergy and remediation such as woody trees. Model sensitivity to soil conditions, contaminant levels and local weather data and the resulting impacts on greenhouse gas emissions are explored. Tradeoffs between renewable energy production,contaminant removal, and mitigation of greenhouse gases are also evaluated. Results indicate that a decrease in greenhouse gas emissions of 29-43% is possible, together with an estimated increase in renewable energy production of 7-22%.