1.1 Goal and Overview of Research
Climate change is a serious global concern. When it comes to reducing carbon
dioxide emissions, we almost always talk about power plants and vehicles. But a new
study by the EPA [1], shows that, if the whole life-cycle is considered, a huge chunk of
greenhouse gas emissions (42%) are caused by the way people in the US "procure,
produce, deliver and dispose of goods and services". It concludes that waste reduction
and recycling are very powerful tools to reduce these emissions. This is the underlying
concept behind the development of this work and to facilitate the organizations and
individuals with better understanding on how their actions can have a direct impact on the
environment. Apart from the emissions mitigation, recycling will directly decrease the
dependence on costly landfills and in most cases also generates revenue. The goal of this
thesis is to develop an ideal calculator for estimating the emissions from municipal solid
waste and the impact of recycling in reducing the green house gas emissions. Little effort
has gone into the estimation of emissions from waste compared to estimation of
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emissions from processes like electricity usage, fuel usage etc. It is universally accepted
that recycling helps the environment by reducing the need for landfills, reducing carbon
emissions and generating revenue. Some calculators totally ignore the impact of recycling
while others use odd ball approach to estimate the reduction of emissions from recycling.
This thesis will address the need for an accurate estimation.
This work is based upon the development of a model outlining the procedures and
analysis required to determine the impact of recycling on the emissions of a facility.
Because every facility faces extremely diverse and varying recycling challenges, this
analytical approach will be developed and presented in a generalized form. After
presenting this generalized procedural model, a detailed application will be demonstrated
using data collected from the facility in Lucas County (OH) which involves estimation of
total MSW, estimation of emissions and estimation of revenue under current and
suggested conditions.