Document Type
Report
Publication Date
2019
Abstract
Solid waste management is a complex undertaking that addresses a basic human need. Wastes can affect human health and the environment. Managing them so as to reduce and minimize these impacts requires expending physical and human resources. Often there are trade-offs among the effects associated with technological and policy choices.
Generally, understanding the effects of the various choices requires expanding scope beyond the immediate issue. Recycling, for instance, reduces disposal needs. It also affects the inputs to manufacturing processes, and can reduce the demand to extract natural resources. A larger perspective on recycling can provide justifications for increasing diversion efforts. Diverting food wastes from landfills reduces landfill gas generation. This can reduce the release of gases that impact our climate. It might also reduce electricity generation at landfills. Reduced electricity from landfill gas may mean greater reliance on and use of fossil fuels, which also leads to the release of more gases impacting the climate system. In order to determine if food waste diversion is going to have a positive effect on climate change, it is necessary to be able to compare the different effects of diversion programs.
One decision-making tool that has wide acceptance is cost-benefit analysis. Financial concerns are an important driver of decisions, and many non-monetary aspects of issues can be translated into economic terms. Environmental measures, however, have usually been poorly conformed to monetary equivalents. Legal requirements and policy needs driven by awareness of the importance of environmental concerns have given the environment a growing role in decision-making, especially in solid waste arenas.
Life cycle analysis (LCA) is a decision-making tool that has been developed into its mature form over the past several decades, just as decision-makers sought means to adequately incorporate environmental issues. LCAs are systems-level processes, seeking to widely consider disparate and far-reaching aspects of problems and conditions. They are quantitative and comprehensive in nature, and focus on environmental impacts.
Their development has also co-incided with growing academic interests and emphases on models and modeling processes. In much of engineering and science there is a desire to capture phenomena through quantitative relationships so as to allow simulation of the processes; this modeling effort often illuminates important aspects of natural and human systems. Capturing theoretical aspects of the systems is sometimes of greater interest than necessarily matching the system’s actual behavior; deviations are sometimes assumed to be a failure of parameterization, and something that can be resolved if better inputs were made. Other models produce esoteric outputs that can be related only indirectly to real world conditions which, however, seem to powerfully describe some essence of process and system.
This report discusses some basic history of LCAs. It looks at a simple LCA (WARM) and a more complicated LCA (EASETECH) in some detail, including presenting some examples of how these models can be used to illustrate waste management policy decisions. The discussions include aspects of why these models are useful and why they may not be as informative as they appear to be.
Fact-driven (data-driven) public policy is well-established as a modern means of reaching decisions, including on solid waste issues. Quantitative comparisons are comforting for policy makers, especially in complex situations or when highly technical issues are at play. This is often the case in waste management. As mentioned above, many environmental impacts and effects are often a concern in waste decisions. LCAs are well-suited for providing data in these settings.
However, the report also underscores that LCAs lack the ability to be verified; the outputs they produce cannot be easily measured in the real world to determine their accuracy. The value of LCAs therefore depends upon trusting in the skill and ability of the modelers (which is great) and their accuracy in capturing all important aspects of the scenarios under consideration. For the more comprehensive models, it also means populating these models with hundreds (sometimes thousands) of parameters, not all of which may be appropriate to use.
Thus, there is inconsistency among the modeling platforms and across different studies. Some of this has been addressed through standardization efforts. But there are aspects of the very nature of LCAs that are likely to remain problematic. Chief are: the complex and different feasible choices regarding system boundaries; the use of output parameters that are not verifiable; and data aggregation to simplify decision choices, where different aggregation methodologies may lead to the identification of different better choices.
Recommended Citation
Tonjes, David J., "Life Cycle Analysis (LCA) Models and their Value for Solid Waste Planning" (2019). Technology & Society Faculty Publications. 35.
https://commons.library.stonybrook.edu/techsoc-articles/35