dc.contributor.author
Pommier, Matthieu
dc.contributor.author
Fagerli, Hilde
dc.contributor.author
Schulz, Michael
dc.contributor.author
Valdebenito, Alvaro
dc.contributor.author
Kranenburg, Richard
dc.contributor.author
Schaap, Martijn
dc.date.accessioned
2020-05-04T15:06:42Z
dc.date.available
2020-05-04T15:06:42Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/27183
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-26939
dc.description.abstract
A large fraction of the urban population in Europe is exposed to particulate matter levels above the WHO guideline value. To make more effective mitigation strategies, it is important to understand the influence on particulate matter (PM) from pollutants emitted in different European nations. In this study, we evaluate a country source contribution forecasting system aimed at assessing the domestic and transboundary contributions to PM in major European cities for an episode in December 2016. The system is composed of two models (EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0), which allows the consideration of differences in the source attribution.
We also compared the PM10 concentrations, and both models present satisfactory agreement in the 4 d forecasts of the surface concentrations, since the hourly concentrations can be highly correlated with in situ observations. The correlation coefficients reach values of up to 0.58 for LOTOS-EUROS and 0.50 for EMEP for the urban stations; the values are 0.58 for LOTOS-EUROS and 0.72 for EMEP for the rural stations. However, the models underpredict the highest hourly concentrations measured by the urban stations (mean underestimation of 36 %), which is to be expected given the relatively coarse model resolution used (0.25∘ longitude × 0.125∘ latitude).
For the source attribution calculations, LOTOS-EUROS uses a labelling technique, while the EMEP/MSC-W model uses a scenario having reduced anthropogenic emissions, and then it is compared to a reference run where no changes are applied. Different percentages (5 %, 15 %, and 50 %) for the reduced emissions in the EMEP/MSC-W model were used to test the robustness of the methodology. The impact of the different ways to define the urban area for the studied cities was also investigated (i.e. one model grid cell, nine grid cells, and grid cells covering the definition given by the Global Administrative Areas – GADM). We found that the combination of a 15 % emission reduction and a larger domain (nine grid cells or GADM) helps to preserve the linearity between emission and concentrations changes. The nonlinearity, related to the emission reduction scenario used, is suggested by the nature of the mismatch between the total concentration and the sum of the concentrations from different calculated sources. Even limited, this nonlinearity is observed in the NO-3, NH+4, and H2O concentrations, which is related to gas–aerosol partitioning of the species. The use of a 15 % emission reduction and of a larger city domain also causes better agreement on the determination of the main country contributors between both country source calculations.
Over the 34 European cities investigated, PM10 was dominated by domestic emissions for the studied episode (1–9 December 2016). The two models generally agree on the dominant external country contributor (68 % on an hourly basis) to PM10 concentrations. Overall, 75 % of the hourly predicted PM10 concentrations of both models have the same top five main country contributors. Better agreement on the dominant country contributor for primary (emitted) species (70 % is found for primary organic matter (POM) and 80 % for elemental carbon – EC) than for the inorganic secondary component of the aerosol (50 %), which is predictable due to the conceptual differences in the source attribution used by both models. The country contribution calculated by the scenario approach depends on the chemical regime, which largely impacts the secondary components, unlike the calculation using the labelling approach.
en
dc.format.extent
21 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
LOTOS-EUROS v2.0
en
dc.subject
PM10 concentrations
en
dc.subject.ddc
500 Naturwissenschaften und Mathematik::550 Geowissenschaften, Geologie::551 Geologie, Hydrologie, Meteorologie
dc.title
Prediction of source contributions to urban background PM10 concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0 – Part 1: The country contributions
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.doi
10.5194/gmd-13-1787-2020
dcterms.bibliographicCitation.journaltitle
Geoscientific model development
dcterms.bibliographicCitation.number
4
dcterms.bibliographicCitation.pagestart
1787
dcterms.bibliographicCitation.pageend
1807
dcterms.bibliographicCitation.volume
13
dcterms.bibliographicCitation.url
https://doi.org/10.5194/gmd-13-1787-2020
refubium.affiliation
Geowissenschaften
refubium.affiliation.other
Institut für Meteorologie
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.issn
1991-959X
dcterms.isPartOf.eissn
1991-9603
refubium.resourceType.provider
WoS-Alert