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
Authors: Pommier Matthieu , Fagerli Hilde , Schulz Michael , Valdebenito Alvaro , Kranenburg Richard , Schaap Martijn 
Published: April 2020

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 NO3-, NH4+, 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.