Page 257 - Materials Chemistry, Second Edition

10 Life Cycle Impact Assessment 243

CF ¼ FF XF EF SF ð10:10Þ

Emissions are expressed as mass of PM or precursor substance released into air.
From there, the impact pathway follows different distribution processes within and
between air compartments and/or regions (indoor, outdoor, urban, rural, etc.)
yielding a time-integrated mass of PM in the different air compartments and/or
regions. Relating the time-integrated PM mass in air to the mass of PM or precursor
substance emitted yields the fate factor (FF) with unit kg in air integrated over one
day per kg emitted. A certain fraction of PM mass in air is subsequently inhaled by
an exposed human population. This fraction is expressed by the exposure factor
(XF) describing the rate at which PM is inhaled with unit kg PM inhaled per kg PM
in air integrated over one day. Multiplying FF and XF yields the cumulative PM
mass inhaled by an exposed population per kg PM or precursor emitted expressed
as human intake fraction (iF). Inhaling PM mass may then lead to a cumulative
population risk referred to as expected disease incidences in the exposed human
population and typically assessed based on PM air concentration. Relating PM
concentration in air to cumulative population risk yields the exposure-response or
effect factor (EF) with unit disease cases (e.g. death for mortality effects) per kg PM
inhaled. Finally, disease incidences are translated into human health damages by
accounting for the disease severity expressed as disability-adjusted life years
(DALY) that include mortality and morbidity effects. Linking health damages to
disease incidences yields the severity (or damage) factor (SF) with unit DALY per
disease case.
For characterising health impacts from emissions of PM or precursor substances,
several aspects influence emission, fate, intake and health effects. Regardless of the
modelling setup (spatial vs. archetypal; including or disregarding indoor sources
and/or secondary PM formation, etc.), main influential aspects are spatiotemporally
variable population density and activity patterns, background PM concentration in
air, background disease rate and background severity, emission location (e.g. indoor
vs. outdoor or urban vs. rural) and emission height, as well as potential nonlinearity
in the disease-specific exposure-response relationship. The effect of using a
non-linear exposure-response curve in the calculation of CFs following the mar-
ginal and average approach is illustrated in Fig. 10.22 for two distinct background
concentration scenarios, where the difference between marginal and average
approach is increasing with increasing background concentration for an
exposure-response curve of supralinear shape.

10.13.3 Emissions and Main Sources

Substances considered in the different LCIA methods to contribute to health
impacts from PM are typically one or more PM fractions (PM 10 ,PM 10–2.5 ,PM 2.5 )