Elemental Carbon (EC) has a significant impact on human health and climate change. In order to evaluate the size segregation of EC emission in the EUCAARI inventory and investigate its influence on the simulation of EC long-range transportation in Europe, we used the fully coupled online Weather Research and Forecasting/Chemistry model (WRF-Chem) at a resolution of 2 km focusing on a region in Germany, in conjunction with a high-resolution EC emission inventory. The ground meteorology conditions, vertical structure and wind pattern were well reproduced by the model. The simulations of particle number and/or mass size distributions were evaluated with observations at the central European background site Melpitz. The fine mode particle concentration was reasonably well simulated, but the coarse mode was substantially overestimated by the model mainly due to the plume with high EC concentration in coarse mode emitted by a nearby point source. The comparisons between simulated EC and Multi-angle Absorption Photometers (MAAP) measurements at Melpitz, Leipzig-TROPOS and Bösel indicated that the coarse mode EC (ECc) emitted from the nearby point sources might be overestimated by a factor of 2–10. The fraction of ECc was overestimated in the emission inventory by about 10–30 % for Russia and 5–10 % for Eastern Europe (e.g., Poland and Belarus). This incorrect size-dependent EC emission results in a shorter atmospheric life time of EC particles and inhibits the long-range transport of EC. A case study showed that this effect caused an underestimation of 20–40 % in the EC mass concentration in Germany under eastern wind pattern.
Elemental carbon (EC) and black carbon (BC) are characterized by their
strong radiation absorbing effect (Hansen et al., 2000; Jacobson et al.,
2000; Cheng et al., 2008, 2009; Bond et al., 2013) and adverse health effects
(Pope et al., 2009; Bond et al., 2013). For climate change, EC is the second
strongest contributor to current global warming with a total radiative
forcing of about
The emission inventory is one of the key factors for the evaluation of the EC
climate effect with model (Vignati et al., 2010). The IPCC (IPCC, 2013)
reported BC radiative forcing of 0.4 (0.05–0.8), 0.2 and 0.04
(0.02–0.09) W m
Numerous works have evaluated the performance of EC emission and transport models for Europe. Koch et al. (2009) evaluated 17 global models and found out that 13 of 17 models over-estimate EC in Europe. Stern et al. (2008) compared five models result with northern Germany observations, and none of the models could reproduce the high EC concentration at the central Europe background station Melpitz. Genberg et al. (2013) pointed out that the EMEP MSC-W model underestimates the EC concentration at Melpitz may because the low model resolution can not represent local effects (like point source). Nordmann et al. (2014) pointed out that the EUCAARI inventory may underestimate the Eastern European EC emission by a factor of about 2, but not considering the size segregation uncertainty of EC emission and its influence on transportation.
In this work, a high-resolution WRF-Chem simulation was set up in conjunction
with the EUCAARI EC inventory, focusing on the central Europe region. The
modelling result was evaluated by the aerosol and EC/BC in situ measurements
from GUAN and HOPE-Melpitz Campaign. The EC emission fraction for coarse
(PM
The fully coupled “online” Weather Research and Forecasting/Chemistry model (WRF-Chem V3.5.1) is a state-of-the-art regional air quality model (Grell et al., 2005). It is suitable for a broad spectrum of atmospheric research with horizontal extents ranging from hundreds of meters to thousands of kilometers. Trace gases, aerosols, and interactive processes with meteorology are simulated with several treatments in the model (Grell et al., 2005). The following is a brief summary of the primary WRF-Chem modules relevant to the current study.
Sectional approach for aerosols: particle dry-diameter ranges used in this study.
In this study, the Carbon-Bond Mechanism version Z (CBMZ, Zaveri and Peters, 1999; Fast et al., 2006) was used for gas-phase atmospheric chemistry. 67 prognostic species and 164 reactions are included in CBMZ mechanism with a lumped structure approach, which classifies organic compounds according to their internal bond types. Fast-J scheme (Wild et al., 2000; Barnard et al., 2004) was used for calculating the rates for photolytic reactions within CBMZ.
The sectional approach MOdel for Simulating Aerosol Interactions and Chemistry (MOSAIC; Zaveri et al., 2008) was applied to better represent the size segregated aerosol properties. In MOSAIC, dry aerosol particles with eight discrete size bins were selected with upper and lower bin diameters defined as shown in Table 1; and particles are assumed to be inter-mixed in each bin (Zaveri et al., 2008). MOSAIC treats the following chemical species: sulfate, methane sulfonate, nitrate, chloride, carbonate, ammonium, sodium, calcium, elemental carbon (EC), organic carbon (OC) and other inorganic mass. Both particle mass and particle number are simulated for each bin. Water uptake or loss will not transfer particles between bins, since bins are based on dry particle diameters (Zaveri et al., 2008). However, particle growth or reduction due to chemical processes (e.g., uptake or release of trace gases, etc.) and physical processes (e.g., coagulation, etc.) will transfer particles between bins (Chapman et al., 2009). In addition, particle coagulation and nucleation processes of sulfuric acid and water vapor are included (Fast et al., 2006; Zaveri et al., 2008). But the formation mechanism of Secondary Organic Aerosol (SOA) is not included in this version (Zaveri et al., 2008).
In WRF-Chem, dry (Binkowski and Shankar, 1995) and wet (Easter et al., 2004) deposition processes of aerosol particles are considered. The dry deposition of aerosol in the lowest model layer is derived from the deposition velocities, which is dependant on the sublayer resistance, aerodynamic resistance and surface resistance (Grell et al., 2005). The scavenging of cloud-phase and below-cloud aerosol by interception and impaction processes is calculated by look-up tables. It is worth mentioning that the particles are treated internally mixed in each bin; therefore the hygroscopicity of EC contained particles tends to be slightly overestimated in the model. Furthermore, the model tends to overestimate the removal rate of EC, especially for the wet deposition processes (Nordmann et al., 2014). In addition, Saide et al. (2012) pointed out that the irreversible removal of aerosol by rain in WRF-Chem might overestimate the wet deposition. However, it was mostly dominated by dry conditions before 16 September 2013 in this simulation.
As shown in Fig. 1, the simulation consists of four nested domains with 39
vertical layers. The spatial resolutions of domains (D01–D04) are 54, 18, 6,
and 2 km respectively. The outer domain (D01) covers Europe and the inner
domain (D04) focuses on Saxony in Germany, centered at Melpitz
(12.93
EUCARRI (resolution 7 km) EC emission (kg m
The anthropogenic emissions were taken from the Pan-European Carbonaceous
aerosol inventory (Visschedijk and Denier van der Gon, 2008) for EC and OC,
which was developed in the framework of the European Integrated project on
Aerosol Cloud Climate and Air Quality interactions (EUCAARI, Kulmala et al.,
2011) for the year 2005. It is available on a spatial resolution of
1/8
The EMEP inventory for 2013 (
In this study, biogenic emissions are taken from the Model of Emissions of Gases and Aerosols from Nature (MEGAN, Guenther et al., 2006). The Fire INventory from NCAR (FINN, Wiedinmyer et al., 2011), with 1 km spatial and 1 hour temporal resolution, was used in this study. The previous studies reported that the dust emission scheme (Saide et al., 2012) and the sea-salt emission scheme (Saide et al., 2012; Zhang et al., 2013) in WRF-Chem have large uncertainties. However, based on the filter measurements with high volume sampler DIGITEL DHA-80 (Walter Riemer Messtechnik, Germany) at Melpitz, dust and sea-salt contributed less than 3 % of aerosol mass in the simulation period. Therefore, the online sea-salt and dust emissions were switched off.
The experimental data used in this paper were drawn from two major sources:
first, the HOPE-Melpitz Campaign of the HD(CP)
Configurations of WRF-Chem.
The regional background site Melpitz (12.93
At Melpitz, Bösel (7.94
Comparison of meteorological variables between Melpitz ground-based
measurements and WRF-Chem D04 result.
The WRF performance on simulating the meteorological fields was evaluated
with the Melpitz ground measurements data and radio-sounding measurements
over the whole of Europe. The wind pattern in the simulated time period was
dominated by westerly winds in Melpitz (Fig. 2d). It was mostly dominated by
dry conditions between 13 and 15 September in Melpitz. The air mass of
northern Germany changed from continental to maritime after 15 September. The
maritime air mass from the North Sea was relatively clean, with less
anthropogenic pollutants. In 15–16 September, the concentration of primary
gaseous pollutant NO was significantly lower at Melpitz than 13–14 September
(Fig. S1 in the Supplement), and also the PM
As shown in Fig. 2, the variances of temperature, relative humidity, wind
speed and wind direction were validated with the ground measurements, with a
correlation coefficient (
The vertical gradient of the potential temperature is an important indicator
for the stability of atmosphere. Figure S2 shows a
Comparison result for meteorological variables between Melpitz radio-sounding measurements and WRF-Chem model.
Comparison of Particle Number Size Distribution (PNSD, left) and Particle Mass Size Distribution (PMSD, right) between WRF-Chem model and Melpitz measurements. Model results indicated by the red lines and measurements by the black lines. The size distributions are averaged in the period 10–20 September 2013, the error bar indicates the upper and lower limits.
The modeled particle number size distribution (PNSD) and particle mass size
distribution (PMSD) for Melpitz were compared with the measurements, shown in
Fig. 3. For the fine mode (PM
We found out that EC had a very high contribution of modeled coarse mode aerosol mass when the EC plumes hit Melpitz (Figs. 4a and 5a). In order to investigate the reasons of the EC plumes and its influence on coarse mode overestimation, a more detailed case study for the plume episode in the morning of 13 September will be given in Sect. 3.3.
The comparison of EC/BC concentration between model and MAAP measurements.
Red line: EC concentration in PM
In order to evaluate the EC emission in central Europe and investigate local effect of point source, MAAP measurements of three background sites (Melpitz, Leipzig-TROPOS and Bösel) were compared with modeled results (Fig. 4). In Leipzig-TROPOS, the relatively high EC concentration in the morning and night but low concentration at the noontime could have resulted from the development of planet boundary layer and traffic rush hours. According to modeled transportations, Melpitz and Bösel were influenced by the point source plume, but Leipzig-TROPOS was not (see Figs. 5b and S4). Here we use MAAP instead of DIGITEL measurement to compare with the model output, because only MAAP data are available for all those three sites and the higher temporal resolution of the MAAP is better for investigating the point source plume influence.
The model result:
The model substantially overestimated the EC concentration in Melpitz
especially for high episode peaks (Fig. 4a), during which the modeled EC
concentration in PM
This EC plume effect was not only found in Melpitz. As shown in Fig. S4,
Bösel was also influenced by a nearby EC point source in the morning of
13 and 14 September 2013 (also Fig. 4c). The EC concentration was
overestimated and had a high coarse mode fraction, similar to Melpitz.
However, the overestimation of EC was not as significant as for Melpitz, with
These results imply that the EC point sources in Germany can be overestimated
by a factor of 2–10 in the EUCAARI emission inventory, especially for the
coarse mode EC emission in the large point sources. To further evaluate the
coarse mode EC emission (ECc, EC in PM
EUCAARI EC emission coarse mode fraction (ECc).
Note that the dry and wet deposition processes also contribute to the uncertainty of the modeling results. The dominant removal process for EC is wet deposition (Genberg et al., 2013); Croft et al. (2005) estimated that about 75 % of the EC is removed by wet deposition and 25 % by dry deposition, based on global model runs. And the wet deposition of EC may be overestimated in the WRF-Chem model due to the irreversible removal process (Yang et al., 2011; Saide et al., 2012) and the internal mixture of EC (Nordmann et al., 2014). It indicates that the overestimation of EC should result from the emission source instead of the deposition process, although the uncertainty of deposition would influence the emission evaluation results. More measurements and modeling studies are still needed for the quantified evaluation of the deposition processes uncertainty.
EC is in general mostly emitted in the fine mode, especially for the area
emissions (Echalar et al., 1998; Hitzenberger and Tohno, 2001; Kuenen et al., 2014),
although the SNAP-5 point sources may be an exception. The major SNAP-5 point
sources giving coarse EC are coal mines and originate from storage and
handling – dust being released due to loading and unloading, driving on the
premises etc. Based on the EUCAARI inventory, the average ECc emission
fraction for Western Europe is around 5 %, also about 5 % in Germany
of year 2009 TNO-MACC_II inventory (Kuenen et al., 2014). This is
consistent with previous knowledge. But on the contrast to the generally low
ECc emission fraction, this fraction is relatively high in Eastern Europe
(e.g. Poland, Slovakia and Belarus), about 15–20 %, and about 35 %
in Poland of TNO-MACC_II inventory (Kuenen et. al., 2014). For Russia
(including Kaliningrad in the north of Poland) and Moldova the fraction can
reach up to 20–40 %, and about 17 % in Russia of TNO-MACC_II
inventory (Kuenen et al., 2014). As shown in the long-term (2003–2011)
filter measurement study at Melpitz (Spindler et al., 2013), in the eastern
wind dominated period when the air mass came from Eastern Europe and Russia,
the EC coarse mode mass fraction was only in the range of 4–15 %
(
Comparison between the adjusted EC coarse emission simulation and original one.
The life-time for fine mode particles is about 5–7 days, but only 1–2 days
for the coarse mode aerosol (Jaenicke, 1980; Petzold and Kärcher, 2012;
Croft et al., 2014). Therefore, the fine mode EC particles have more time to
accumulate in the atmosphere. To evaluate the influence of this high coarse
mode EC emission fraction in Eastern Europe on EC's long-range
transportation, we constructed the following concept model. In a steady
state, where sources are continuous and there is a quasi-equilibrium between
sources and sinks such that the EC concentration is constant in time. For the
same emission rate of EC, the equilibrium mass concentration of fine mode
will be 2–3 times higher than coarse mode as described in Eq. (1) (Croft et
al., 2014).
On the other hand, longer lifetime makes fine mode EC particles have more
opportunity to be transported from Eastern Europe to Melpitz. In the
following scenario, the particles were emitted instantly into the air mass,
which was assumed to be transported by an eastern wind pattern with
5 m s
The overestimation of ECc emission fraction in EUCAARI inventory resulted in less EC transported from the Eastern Europe and Russia to Melpitz. This may be one reason for the underestimation of the EC mass concentration in the other studies under eastern wind pattern. For instance, Genberg et al. (2013) and Nordmann et al. (2014) reported an underestimation of EC in Europe with the simulation of EUCAARI inventory.
Aerosol mass residential rate with relationship of transport time and lifetime. The color indicates the percentage of aerosol mass that can be transported to Melpitz.
Nordmann et al. (2014) reported an underestimation about 50 % of EC mass
concentration in Germany during March–April 2009, especially for the period
when air mass approached the observation sites from eastern directions. And
they suspected that the EC emission in Eastern Europe may be underestimated
by a factor of 2 to 5. In order to investigate the possible influence of the
overestimated ECc emission fraction in Eastern Europe in this case, we
re-simulated the same time period as in Nordmann et al. (2014) with the
adjusted EC emission inventory. The ECc emission fraction was adjusted to
5 % (the average value for Western Europe,
longitude
A WRF-Chem simulation was performed for the period between 10 and 20 September 2013, with an inner most domain of 2 km resolution for the Melpitz region in eastern Germany. The high-resolution EUCAARI inventory of EC emission was applied in the model. The measurements of HOPE-Melpitz Campaign and GUAN network project were used for modelling results validation.
The comparison of particle number/mass size distributions showed that the coarse mode particle concentration was substantially overestimated by the model. However, the meteorology and transport process were well simulated, because of the good agreement with the ground-based and radio-sounding meteorological measurements. These results indicated that the overestimation of the coarse mode particle should mostly come from the uncertainty of emission inventories. The comparisons of EC mass concentrations at the Melpitz, Leipzig-TROPOS and Bösel sites indicated that the EC point sources may be overestimated by a factor of 2–10, which made a remarkable unrealistic plume in Melpitz.
The coarse mode EC emission fraction was substantially overestimated in Eastern Europe (e.g.: Poland, Belarus etc.) and Russia by EUCAARI inventory, with about 10–30 % for Russia and 5–10 % for the Eastern European countries. A concept model and a case study were designed to interpret the influence of this overestimation on EC long-range transportation. Due to the overestimation of ECc emission fraction, EC mass transported from Moskva to Melpitz would decrease by about 25–35 % of ECc mass concentration, and decrease by about 25–55 % from Warsaw to Melpitz. This is because the coarse mode particle has a shorter life-time and therefore less opportunity for being long-range transported and accumulated in the atmosphere. The March–April 2009 case (Nordmann et al., 2014) was re-simulated with adjusted ECc emission fraction in Eastern Europe in order to validate the influence on transportation. The result showed that the overestimation of ECc emission fraction in Eastern Europe was one reason of the underestimation of EC in Germany, when the air masses came from eastern direction. It contributed to an underestimation of about 20–40 %.
Will the health and climatic effects of atmospheric EC particles be local, regional or global? This is to some extent determined by the transportation of EC, which is largely influenced by its size distribution. The size segregation information of EC particles should be carefully considered in the model validation and climate change evaluation studies. Unfortunately, the size segregation information is not included in most of the current global EC emission inventories, and the size segregation in EUCAARI inventory only covers Europe and is still with high uncertainty. More EC particle size distribution measurements (e.g.: online analysis of SP2, offline analysis of Berner/MOUDI samples, etc.) and long-term model simulation studies are needed to further improve the EC emission inventories.
Continuous aerosol measurements at Melpitz were supported by the German
Federal Environment Ministry (BMU) grants F&E 370343200 (German title:
“Erfassung der Zahl feiner und ultrafeiner Partikel in der Außenluft”)
and F&E 371143232 (German title: “Trendanalysen
gesundheitsgefährdender Fein- und Ultrafeinstaubfraktionen unter Nutzung
der im German Ultrafine Aerosol Network (GUAN) ermittelten Immissionsdaten
durch Fortführung und Interpretation der Messreihen”. The black carbon
data used for this paper can be accessed through the German Ultrafine Aerosol
Network's data dissemination page: