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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp018w32r581g
Title: A Feasibility Analysis of a Waste-to-Energy Conversion Facility at Princeton University
Authors: Calof, Andrew
Advisors: Mauzerall, Denise L.
Department: Chemical and Biological Engineering
Class Year: 2014
Abstract: Greenhouse gas emissions and global warming are pressing issues. The Intergovernmental Panel on Climate Change’s assessment reports among other sources suggest that increases in greenhouse gas (GHG) concentration have been one of the main causes of global warming. As a result, governments, companies, and other institutions are implementing policies and investing in technologies to reduce GHG emissions. Princeton University has made it clear that reducing their GHG emissions is extremely important. They have self-imposed a CO\(_{2}\) tax to incentivize investing in greener technologies and have instituted a host of GHG emission programs. The purpose of this thesis is to examine if waste-to-energy technology can assist Princeton reduce their GHG emissions economically. Princeton currently disposes their 2386 tons of municipal solid waste in a landfill and in an incinerator, both of which generate large GHG emissions. Currently Princeton’s MSW emits 2536 tons of CO\(_{2}\)eq from decomposing at a landfill, assuming all the MSW is transported to the landfill, or 2187 tons of CO\(_{2}\), assuming all the MSW is incinerated. Through an extensive literature review and in talking to numerous industrial professional’s including Princeton University staff, three waste to energy technologies were chosen for analysis: Alter NRG (plasma-assisted gasification), AdaptiveARC (plasma gasification), and GIPO (wet thermal conversion). All three companies have technologies that can handle Princeton’s MSW, will reduce GHG’s and generate electricity for University use. Alter NRG is the only one of the three companies with commercialized plants. Alter NRG’s process can produce 756 kWh/ton MSW. AdaptiveARC has a UV pulsing technique that allows for less electricity and heat loss as it can break down the MSW more efficiently. AdaptiveARC’s process can produce 498 kWh/ton MSW. GIPOs wet thermal conversion process can handle wet feedstock without needing to pre-dry which is something the plasma gasification processes cannot do. However, based on the 35% moisture content of Princeton MSW, none of the companies being compared must do this as they can all handle this moisture content. GIPOs process produces 1224 kWh/ton MSW. Based on the assumptions and calculations made in this thesis and only using Princeton’s MSW, the analysis showed that the GIPO process has the greatest percentage GHG reduction of the three system; 38% over the landfill process and 31% of incineration. The discounted payback times were most attractive with the GIPO process, 18.1 years over landfill and 19.1 year over incineration, in comparison to the AdaptiveARC and Alter NRG whose processes payback times were infeasible. GIPO was also the only company with a positive net present value using only Princeton’s MSW. Running the units at capacity by bringing in other MSW shows a different result. GIPO still had the shortest discounted payback time, 7.19 years over the landfill process and 8.50 years over the incineration process. However, Alter NRG had the greatest net present value, $6,399,135 over the landfill process (1.4 times greater than GIPO) while GIPO had the greatest net present value over the incineration process, $4,345,985 (1.02 time greater than Alter NRG). The recommendation for running the systems at capacity is still the GIPO process because it only requires accepting 2414 tons of MSW to be imported (compared to 31,114 for the Alter NRG process) which is more realistic for Princeton, also it has the greatest emissions reduction percentage and the difference in economics is marginal.
Extent: 72 pages
URI: http://arks.princeton.edu/ark:/88435/dsp018w32r581g
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Chemical and Biological Engineering, 1931-2016

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