@article{fdi:010089629,
  title = {{A}erosol source apportionment uncertainty linked to the choice of input chemical components},
  author = {{A}mato, {F}. and van {D}rooge, {B}. {L}. and {J}affrezo, {J}. {L}. and {F}avez, {O}. and {C}olombi, {C}. and {C}uccia, {E}. and {R}eche, {C}. and {I}ppolito, {F}. and {R}idolfo, {S}. and {L}ara, {R}. and {U}zu, {G}a{\¨e}lle and {N}goc, {T}. {V}. {D}. and {D}ominutti, {P}. and {D}arfeuil, {S}ophie and {A}lbinet, {A}. and {S}rivastava, {D}. and {K}aranasiou, {A}. and {L}anzani, {G}. and {A}lastuey, {A}. and {Q}uerol, {X}.},
  editor = {},
  language = {{ENG}},
  abstract = {{F}or a {P}ositive {M}atrix {F}actorization ({PMF}) aerosol source apportionment ({SA}) studies there is no standard procedure to select the most appropriate chemical components to be included in the input dataset for a given site typology, nor specific recommendations in this direction. {H}owever, these choices are crucial for the final {SA} outputs not only in terms of number of sources identified but also, and consequently, in the source contributions estimates. {I}n fact, {PMF} tends to reproduce most of {PM} mass measured independently and introduced as a total variable in the input data, regardless of the percentage of {PM} mass which has been chemically characterized, so that the lack of some specific source tracers (e.g. levoglucosan) can potentially affect the results of the whole source apportionment study. {T}he present study elaborates further on the same concept, evaluating quantitatively the impact of lacking specific sources' tracers on the whole source apportionment, both in terms of identified sources and source contributions. {T}his work aims to provide first recommendations on the most suitable and critical components to be included in {PMF} analyses in order to reduce {PMF} output uncertainty as much as possible, and better represent the most commons {PM} sources observed in many sites in {W}estern countries. {T}o this aim, we performed three sensitivity analyses on three different datasets across {EU}, including extended sets of organic tracers, in order to cover different types of urban conditions ({M}editerranean, {C}ontinental, and {A}lpine), source types, and {PM} fractions. {O}ur findings reveal that the vehicle exhaust source resulted to be less sensitive to the choice of analytes, although source contributions estimates can deviate significantly up to 44 %. {O}n the other hand, for the detection of the non-exhaust one is clearly necessary to analyze specific inorganic elements. {T}he choice of not analysing non-polar organics likely causes the loss of separation of exhaust and non-exhaust factors, thus obtaining a unique road traffic source, which provokes a significant bias of total contribution. {L}evoglucosan was, in most cases, crucial to identify biomass burning contributions in {M}ilan and in {B}arcelona, in spite of the presence of {PAH}s in {B}arcelona, while for the case of {G}renoble, even discarding levoglucosan, the presence of {PAH}s allowed identifying the {BB} factor. {M}odifying the rest of analytes provoke a systematic underestimation of biomass burning source contributions. {SIA} factors resulted to be generally overestimated with respect to the base case analysis, also in the case that ions were not included in the {PMF} analysis. {T}race elements were crucial to identify shipping emissions ({V} and {N}i) and industrial sources ({P}b, {N}i, {B}r, {Z}n, {M}n, {C}d and {A}s). {W}hen changing the rest of input variables, the uncertainty was narrow for shipping but large for industrial processes. {M}ajor and trace elements were also crucial to identify the mineral/soil factor at all cities. {B}iogenic {SOA} and {A}nthropogenic {SOA} factors were sensitive to the presence of their molecular tracers, since the availability of {OC} alone is unable to separate a {SOA} factor. {A}rabitol and sorbitol were crucial to detecting fungal spores while odd number of higher alkanes ({C}27 to {C}31) for plant debris.},
  keywords = {{S}ensitivity analysis ; {PMF} ; {I}ons ; {E}lements ; {C}arbon ; {M}olecular markers ; {ESPAGNE} ; {FRANCE} ; {ITALIE} ; {BARCELONE} ; {GRENOBLE} ; {MILAN}},
  booktitle = {},
  journal = {{E}nvironment {I}nternational},
  volume = {184},
  numero = {},
  pages = {108441 [ 12p.]},
  ISSN = {0160-4120},
  year = {2024},
  DOI = {10.1016/j.envint.2024.108441},
  URL = {https://www.documentation.ird.fr/hor/fdi:010089629},
}