% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Visser:275787,
      author       = {Visser, S. and Slowik, J. G. and Furger, Markus and Zotter,
                      P. and Bukowiecki, N. and Canonaco, F. and Flechsig, U. and
                      Appel, K. and Green, D. C. and Tremper, A. H. and Young, D.
                      E. and Williams, P. I. and Allan, J. D. and Coe, H. and
                      Williams, L. R. and Mohr, C. and Xu, L. and Ng, N. L. and
                      Nemitz, E. and Barlow, J. F. and Halios, C. H. and Fleming,
                      Z. L. and Baltensperger, U. and Prévôt, A. S. H.},
      title        = {{A}dvanced source apportionment of size-resolved trace
                      elements at multiple sites in {L}ondon during winter},
      journal      = {Atmospheric chemistry and physics},
      volume       = {15},
      number       = {19},
      issn         = {1680-7324},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {PUBDB-2015-04235},
      pages        = {11291 - 11309},
      year         = {2015},
      abstract     = {Trace element measurements in PM$_{10–2.5}$,
                      PM$_{2.5–1.0}$ and PM$_{1.0–0.3}$ aerosol were performed
                      with 2 h time resolution at kerbside, urban background and
                      rural sites during the ClearfLo winter 2012 campaign in
                      London. The environment-dependent variability of emissions
                      was characterized using the Multilinear Engine
                      implementation of the positive matrix factorization model,
                      conducted on data sets comprising all three sites but
                      segregated by size. Combining the sites enabled separation
                      of sources with high temporal covariance but significant
                      spatial variability. Separation of sizes improved source
                      resolution by preventing sources occurring in only a single
                      size fraction from having too small a contribution for the
                      model to resolve. Anchor profiles were retrieved internally
                      by analysing data subsets, and these profiles were used in
                      the analyses of the complete data sets of all sites for
                      enhanced source apportionment.A total of nine different
                      factors were resolved (notable elements in brackets): in
                      PM$_{10–2.5}$, brake wear (Cu, Zr, Sb, Ba), other
                      traffic-related (Fe), resuspended dust (Si, Ca), sea/road
                      salt (Cl), aged sea salt (Na, Mg) and industrial (Cr, Ni);
                      in PM$_{2.5–1.0}$, brake wear, other traffic-related,
                      resuspended dust, sea/road salt, aged sea salt and S-rich
                      (S); and in PM$_{1.0–0.3}$, traffic-related (Fe, Cu, Zr,
                      Sb, Ba), resuspended dust, sea/road salt, aged sea salt,
                      reacted Cl (Cl), S-rich and solid fuel (K, Pb). Human
                      activities enhance the kerb-to-rural concentration gradients
                      of coarse aged sea salt, typically considered to have a
                      natural source, by 1.7–2.2. These site-dependent
                      concentration differences reflect the effect of local
                      resuspension processes in London. The anthropogenically
                      influenced factors traffic (brake wear and other
                      traffic-related processes), dust and sea/road salt provide
                      further kerb-to-rural concentration enhancements by direct
                      source emissions by a factor of 3.5–12.7. The traffic and
                      dust factors are mainly emitted in PM$_{10–2.5}$ and show
                      strong diurnal variations with concentrations up to 4 times
                      higher during rush hour than during night-time. Regionally
                      influenced S-rich and solid fuel factors, occurring
                      primarily in PM$_{1.0–0.3}$, have negligible resuspension
                      influences, and concentrations are similar throughout the
                      day and across the regions.},
      cin          = {DOOR ; HAS-User},
      ddc          = {550},
      cid          = {I:(DE-H253)HAS-User-20120731},
      pnm          = {899 - ohne Topic (POF3-899) / FS-Proposal: II-20100006 EC
                      (II-20100006-EC)},
      pid          = {G:(DE-HGF)POF3-899 / G:(DE-H253)II-20100006-EC},
      experiment   = {EXP:(DE-H253)D-L-20150101},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000362971000023},
      doi          = {10.5194/acp-15-11291-2015},
      url          = {https://bib-pubdb1.desy.de/record/275787},
}