Life cycle impact assessment and interpretation of municipal solid waste management scenarios based on the midpoint and endpoint approaches

Few studies have examined differing interpretations of life cycle impact assessment (LCIA) results between midpoints and endpoints for the same systems. This paper focuses on the LCIA of municipal solid waste (MSW) systems by taking both the midpoint and endpoint approaches and uses LIME (Life Cycle Impact Assessment Method based on Endpoint Modeling, version 2006). With respect to global and site-dependent factors, environmental impact categories were divided into global, regional, and local scales. Results are shown as net emissions consisting of system emissions and avoided emissions.

This study is divided into five segments. The first segment develops the LCIA framework and four MSW scenarios based on the current MSW composition and systems of Seoul, considering adaptable results from the hierarchy MSW systems. In addition, two systems are considered: main MSW systems and optional systems. Several “what if” scenarios are discussed, including various compositions and classifications of MSW. In the second segment, life cycle inventory (LCI) analysis is applied to define various inputs and outputs to and from MSW systems, including air (23 categories), water (28 categories) and land (waste) emissions, resource consumption, land use, recovered material, compost, landfill gas, biogas, and heat energy. The third segment, taking the midpoint approach, investigates the nine environmental impacts of the system and avoided emissions. In the fourth segment, this study, taking the endpoint approach, evaluates the damages, dividing the four safeguard subjects affected by 11 environmental impact categories of the system and avoided emissions. In these third and fourth segments, LCIA is applied to analyze various end-of-life scenarios for same MSW materials. The final segment defines the differences from the results in accordance with the two previous life cycle assessment methodologies (the LCIA and interpretations with respect to midpoints and endpoints).

With the respect to midpoints, Scenario 1 (S1) using 100% landfills (L) is the worst performer in terms of global (global warming and resource consumption), regional (acidification, human toxicity, and ecotoxicity), and local (waste: landfill volume) impacts. In terms of all impacts except global warming and waste, Scenario 2 (S2) using 64.2% L and 35.8% material recycling (MR) was found to be the most effective system. With respect to global-scale endpoints, S1 was the worst performer in terms of human health and social assets, whereas the other scenarios with MR were poor and bad performers in terms of biodiversity and primary production. With respect to regional- and local-scale endpoints, S1 was the worst performer in terms of human health, biodiversity, and primary production, whereas Scenario 4 (S4) using 4.2% L (only incombustibles), 35.8% MR, 28.5% biological treatment (BT), and 31.5% incineration (I) was the worst performer in terms of social assets. S4 was the best performer in terms of global-scale endpoints, whereas S2 and Scenario 3 (S3, using 35.7% L, 35.8% MR, and 28.5% BT) were the best on regional- and local-scale endpoints, respectively. With respect to the monetization analysis, which considered net emissions and integrated all endpoints, S3 was found to be “the most effective system,” indicating US $31.6 savings per ton-waste.

The results of this study illustrate the differences in the LCIA outcomes and interpretations with respect to the midpoint and endpoint approaches. In addition, it would be possible to interpret the effect of each indicator on safeguard subjects by integrating separate midpoints. The LCIA results of each endpoint for the scenarios were generally consistent with those of each midpoint. However, the results changed dramatically when the main contributor was a new category not included in midpoint categories. The key advantage with respect to grouping impact categories in the midpoint and endpoint approaches can be described as “the simplification of midpoints and the segmentation of endpoints.”

This research raises many questions that warrant further research. This method does not provide an uncertainty evaluation of input data at the inventory level; it addresses only the main contributor for each impact category to four endpoints. In addition, it would be beneficial to investigate the suitability of midpoints and endpoints for different stakeholders with a low or high level of environmental expertise by comparing previous studies.