City emissions: Similarities and Differences

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• City emissions Similarities and Differences
• Ispra 14-15 October
• G.Maffeis, M.G. Longoni, E. Bossi
• g.maffeis_at_terraria.com
• Terraria srl. Milan Italy
• P.Thunis, K. Cuvelier
• IES-JRC Ispra Italy

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Five cities

• Five City Delta cities MILAN, PARIS, BERLIN,
  PRAGUE and LONDON both local (city) and national
  (EMEP) emission inventories have been compared
  and analyzed.
• A special acknowledg-ment is due to all city and
  EMEP emission inventory manager.

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LOCAL INVENTORY DOMAIN NOx traffic emissions
Total domains
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Five cities inventorygeneral information
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Five cities inventorytemporalchemical
disaggreation
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Five cities inventorytemporal profiles
MILAN source sector 2
LONDON source sector 2
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Five cities inventoryLondon vs Milan VOC
profiles
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City Delta Emission DensitiesCity vs EMEP
inventory (I)
BERLIN
PARIS
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City Delta Emission DensitiesCity vs EMEP
inventory (II)
MILAN
PRAGUE
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City Delta Emission DensitiesCity vs EMEP
inventory (III)
LONDON
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Local vs regional inventory percent difference
on total domain
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Five cities emission densities differences
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City centre emission densities / total domain
emission densities
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Pro capita emissionsthe Milan case
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Emission ratios function of city centre distance
(I)
NOxgtVOC
VOCgtNOx
City centre
transept
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Emission ratios function of city centre distance
(II)
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Emission ratios function of city centre distance
(III)
NOx traffic 60-80
PM traffic 60-80 to 50
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2010 emission scenarios

• Emission data (both local and EMEP) have been
  projected in 2010 for two scenarios the CLE
  (Current LEgislation) and the MFR (Most Feasible
  Reduction) emission reduction scenarios.

Percent reductions
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City 2010 emission scenarios NOx
20
City 2010 emission scenarios PM
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Conclusions

• A first set of rough QA/QC emissions indicators
  (e.g. emission density, pro capita emission,
  emission ratios ..) could help in a first check
  of emission inventories. This evidence some
  difference to be checked for the local
  inventories.
• While NOx, CO, SOx emission estimates seems to be
  quite robust with an uncertainty roughly thought
  to be around 20-30, PM one seems to be still
  higher than 50, probably due to sector lack.
  This higher uncertainty could confound scenarios
  efficacy.
• The check of the red points evidenced in local
  inventory could assure an acceptable QA/QC on
  emission input. Major focus should be given to
  temporal and VOC disaggregation that could
  strongly influence peak emissions and
  consequently air quality excendances.