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This work provides a globally regionalized approach for quantifying particulate matter (PM 2.5 ) health impacts. Atmospheric transport and pollutant chemistry of primary particulate matter, sulfur dioxide (SO 2 ), nitrogen oxide (NO  x  ), and ammonia (NH 3 ) from stack emissions were modeled and used to calculate monthly high-resolution maps of global characterization factors that can be used for life cycle impact assessment (LCIA) and risk assessment. These characterization factors are applied to a global data set of coal power emissions. The results show large regional and temporal differences in health impacts per kg of emission and per amount of coal power generation (5-1300 DALY TWh -1 ). While small emission reductions of PM 2.5 and SO 2 from coal power lead to similar health benefits across densely populated areas of Asia and Europe, we find that larger emission reductions result in up to three times higher health benefits in parts of Asia because of the nonlinear health responses to pollution exposure changes. Hence, many regions in Asia benefit disproportionately much from large coal power PM 2.5 and SO 2 emission reductions. NO  x  emission reductions can lead to equally high health benefits, where unfavorable atmospheric conditions coincide with elevated NH 3 background pollution and large population (e.g., in Central Europe, Indonesia, or Japan but also numerous other places).

Globally Regionalized Monthly Life Cycle Impact Assessment of Particulate Matter