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Life cycle impact assessment modeling for particulate matter: A new approach based on physico-chemical particle properties
Institution:1. Korea Institute of Atmospheric Prediction Systems, Seoul, South Korea;2. School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea;3. Pacific Northwest National Laboratory, Richland, WA, United States;4. Department of Atmospheric Science, Yonsei University, Seoul, South Korea;1. Department of Epidemiology, Health Economics and Public Health, UMR1027 INSERM–Toulouse University, Toulouse University Hospital (CHU), Toulouse, France;2. Department of Epidemiology and Public Health, INSERM UMR744, Pasteur Institute of Lille, Lille Nord de France University–UDSL, Lille, France;3. Department of Epidemiology and Public Health, EA 3430, FMTS, Strasbourg University, Strasbourg, France;4. Department of Public Health, Strasbourg University Hospital, Strasbourg, France;5. Department of Cardiology B, Toulouse University Hospital, Toulouse, France
Abstract:Particulate matter (PM) causes severe damage to human health globally. Airborne PM is a mixture of solid and liquid droplets suspended in air. It consists of organic and inorganic components, and the particles of concern range in size from a few nanometers to approximately 10 μm. The complexity of PM is considered to be the reason for the poor understanding of PM and may also be the reason why PM in environmental impact assessment is poorly defined. Currently, life cycle impact assessment is unable to differentiate highly toxic soot particles from relatively harmless sea salt. The aim of this article is to present a new impact assessment for PM where the impact of PM is modeled based on particle physico-chemical properties. With the new method, 2781 characterization factors that account for particle mass, particle number concentration, particle size, chemical composition and solubility were calculated. Because particle sizes vary over four orders of magnitudes, a sound assessment of PM requires that the exposure model includes deposition of particles in the lungs and that the fate model includes coagulation as a removal mechanism for ultrafine particles. The effects model combines effects from particle size, solubility and chemical composition. The first results from case studies suggest that PM that stems from emissions generally assumed to be highly toxic (e.g. biomass combustion and fossil fuel combustion) might lead to results that are similar compared with an assessment of PM using established methods. However, if harmless PM emissions are emitted, established methods enormously overestimate the damage. The new impact assessment allows a high resolution of the damage allocatable to different size fractions or chemical components. This feature supports a more efficient optimization of processes and products when combating air pollution.
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