@article{fdi:010094293,
  title = {{C}omparison of modelled and experimental {PM}10 source contributions for mapping source-specific oxidative potential},
  author = {{P}ekel, {F}. and {U}zu, {G}a{\¨e}lle and {W}eber, {S}. and {K}ranenburg, {R}. and {T}okaya, {J}. and {S}chaap, {M}. and {D}ominutti, {P}. and {F}avez, {O}. and {J}affrezo, {J}. {L}. and {T}immermans, {R}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}o effectively reduce the health burden of particulate matter ({PM}) pollution requires indicators more directly linked to adverse health effects than total {PM} mass alone. {O}xidative potential ({OP})-the ability of {PM} to induce oxidative stress based on its chemical composition-is gaining recognition as a health-relevant metric. {I}ntegrating source-specific {OP} values from field measurements into {C}hemical {T}ransport {M}odels ({CTM}s) enables the mapping of source-specific {OP} with broad spatiotemporal coverage. {A} critical step is ensuring alignment between {CTM}-derived and observation-based source contributions. {T}his study evaluates and optimises the consistency between the {LOTOS}-{EUROS} {CTM} and {P}ositive {M}atrix {F}actorization ({PMF}) source profiles, using {PM}10 data from 15 {F}rench sites (2013-2016). {W}hile total {PM}10 shows reasonable correlation with observations (r2 = 0.35-0.66), source-specific comparisons vary across source-types and locations. {P}romising results are obtained for residential biomass burning (r2 = 0.34-0.75), secondary inorganic aerosols (r2 = 0.30-0.71), and sea salt (r2 = 0.18-0.71), whereas road traffic shows weaker alignment (r2 = 0.01-0.40). {U}sing the optimized source matching, {OP} maps are generated over {F}rance, showing stronger contributions from anthropogenic sources to {OP} than to {PM}10 mass. {T}he study highlights key challenges in matching {CTM} and {PMF} sources for {OP} modelling, due to secondary aerosol formation, source mixing within {PMF} profiles, and spatiotemporal representation differences. {R}efining emission data, incorporating secondary organic aerosol and aging processes in {CTM}s, and expanding source-specific {OP} measurements, particularly for uncharacterized sources like agriculture are identified as essential next steps. {D}espite current limitations, this approach offers a promising framework for advancing health-oriented air quality management.},
  keywords = {{P}articulate matter ; {S}ource attribution ; {P}ositive matrix factorization ; {C}hemical transport model ; {O}xidative potential ; {FRANCE}},
  booktitle = {},
  journal = {{A}tmospheric {E}nvironment-{X}},
  volume = {27},
  numero = {},
  pages = {100339 [18 p.]},
  year = {2025},
  DOI = {10.1016/j.aeaoa.2025.100339},
  URL = {https://www.documentation.ird.fr/hor/fdi:010094293},
}