Emissions of most land-based air pollutants in western Europe
have decreased in the last decades. Over the same period emissions from
shipping have also decreased, but with large differences depending
on species and sea area. At sea, sulfur emissions in the SECAs
(Sulphur Emission Control Areas) have decreased following the implementation
of a 0.1 % limit on sulfur in marine fuels from 2015. In Europe the North
Sea and the Baltic Sea are designated as SECAs by the International
Maritime Organisation (IMO).
Model calculations assuming present (2016) and future (2030) emissions have
been made with the regional-scale EMEP model covering Europe and the
sea areas surrounding Europe, including the North Atlantic east of 30∘ W. The main focus in this paper is on the effects of ship
emissions from the Baltic Sea.
To reduce the influence of meteorological variability, all model
calculations are presented as averages for 3 meteorological years
(2014, 2015, 2016). For the Baltic Sea, model calculations have also been made
with higher sulfur emissions representative of year 2014 emissions.
From Baltic Sea shipping the largest effects are calculated for NO2
in air, accounting for more than 50 % of the NO2 concentrations in central parts of the
Baltic Sea. In coastal zones contributions to NO2 and also nitrogen
depositions can be of the order of 20 % in some regions.
Smaller effects, up to 5 %–10 %, are also seen for PM2.5 in
coastal zones close to the main shipping lanes.
Country-averaged contributions from ships are small for large
countries that extend far inland like Germany and Poland, and larger for
smaller countries like Denmark and the Baltic states Estonia, Latvia, and
Lithuania, where ship emissions are among the largest contributors to
concentrations and depositions of anthropogenic origin.
Following the implementations of stricter SECA regulations, sulfur emissions
from Baltic Sea shipping now have virtually no effects on
PM2.5 concentrations and sulfur depositions in the Baltic Sea region.
Adding to the expected reductions in air pollutants and depositions
following the projected reductions in European emissions, we expect that
the contributions from Baltic Sea shipping to NO2 and
PM2.5 concentrations, and to depositions of nitrogen, will be
reduced by 40 %–50 % from 2016 to 2030 mainly as a result of the Baltic
Sea being defined as a Nitrogen Emission Control Area from 2021. In most
parts of the Baltic Sea region ozone levels are expected to decrease from
2016 to 2030. For the Baltic Sea shipping, titration, mainly in winter, and
production, mainly in summer, partially compensate. As a result the
effects of Baltic Sea shipping on ozone are similar in 2016 and 2030.
Introduction
Even though emissions of most air pollutants have decreased
in the countries surrounding the Baltic Sea (BAS) in past decades
, air pollution and atmospheric depositions
affecting ecosystems remain a problem in the region. Significant
contributions to the emissions also come from shipping, both
inside and outside the region. Obtaining reliable data on emissions
from international shipping has always been
challenging, but in recent years ship emissions
estimated based on AIS (automatic
identification system) positioning data have become available,
continuously tracking the position of the vessels, resulting in
substantial improvements in the reliability of ship emissions data.
A number of IMO (International Maritime Organisation) and EU regulations
have been implemented in the recent past or will be implemented in the
near future, affecting ship emissions in European waters. Most
noteworthy are the SECA (Sulphur Emission Control Area) regulations,
reducing the maximum sulfur content allowed in marine fuels from 1.0 % to 0.1 %
from 1 January 2015 . Fuels with higher sulfur
content may be used in combination with emission reduction technology,
reducing sulfur emission to levels equivalent to the use of compliant
low-sulfur fuels. In European waters the North Sea (NOS) and
BAS are designated as SECAs by the IMO. These two sea areas are
also accepted as NECAs (NOx Emission Control Areas) from
2021 . Reductions in NOx emissions are expected
to occur only gradually in the NECAs as these regulations only apply to
new ships or when major modifications are made on existing ships.
Furthermore, from 2020 a global cap on sulfur content in marine fuels of
0.5 % will be implemented.
The global effects of international shipping on air
pollution and depositions have been discussed in several papers
.
In a global model calculation found that a large
portion of the anthropogenic contributions to air pollution and
nitrogen depositions in adjacent countries could be attributed to NOS and
BAS ship emissions of NOx and particles also after the
introduction of stricter SECA regulations in 2015.
In addition, several regional studies focusing on the effects of
NOS and BAS ship emissions have been performed.
studied the effects of reducing the sulfur content in marine fuels
from 1.5 % to 1 % in 2011 on air pollution, including also
calculations of health effects as well as effects
of future (2030) ship emissions. They found that the introduction
of a NECA from 2016 (later postponed to 2021) would reduce the burden
on health due to shipping in the BAS region. Reductions in future
PM2.5 (particulate matter with diameter less than 2.5 µm)
levels as a result of the 2021 NECA are also predicted by
. calculated the effects of
ship emission on Europe for the years 2000 and 2020. They found that
the implementation of the stricter SECA regulations in the BAS
and the NOS would result in substantial health improvements in Europe.
compared the effects of BAS shipping
calculated by three different chemistry transport models
using year 2012 emissions and meteorology. They found that in the entire BAS
region the average contribution from ships to PM2.5 is
in the range of 4.3 %–6.5 % for the three CTMs, and deposition of
oxidised nitrogen to the Baltic Sea is in the 20–24 ktN per year range.
calculated
the dispersion of air pollutants and depositions from NOS and
BAS shipping for the period 2011 to 2050, with the main focus on
seawater acidity in BAS. They found that, also in the future, ship
emissions could remain a major source of acidity, in particular
when assuming high penetration of open-loop scrubbers in combination
with the use of high-sulfur-content fuels.
SOx removal by scrubbing the exhaust can significantly reduce both
the gaseous sulfur compounds as well as particulate matter. Scrubbers may
use seawater as a cleaning agent if the alkalinity of seawater is high
enough and contains enough carbonates, bicarbonates, and borates. However,
in areas of low alkalinity, like the Bothnian Bay in the Baltic Sea, the
required wash water volume becomes very large, and chemicals like caustic
soda are added to neutralise the acidic releases.
The wash water may also contain other pollutants such as heavy metals.
Ship owners can also comply with stringent sulfur rules by using LNG
(liquefied natural gas).
However, during 2016 only about 0.8 % of the energy need of the Baltic Sea
fleet was produced with LNG. Use of renewable liquid fuels is rather
limited because of high price and low availability. Liquid biofuels are not
used by any ship in our modelling approach.
In this paper we have calculated the effects of ship emissions in
the BAS on air pollution and depositions of oxidised sulfur and
nitrogen in adjacent countries.
Calculations have been made applying BAS emissions prior to (2014)
and after (2016) the implementation of the stricter SECA regulations,
which went into force on 1 January 2015. Furthermore, model
calculations have been made with future (2030) land-based and
ship emissions.
Experimental setupEmissions
Land-based emissions have been provided by the International Institute
for Applied Systems Analysis (IIASA) within European FP7 project
ECLIPSE. In this study we use version 5a (hereafter “ECLIPSEv5a”),
a global emission data set at 0.5×0.5∘ resolution, which has
been widely used in recent years by the scientific community (http://www.iiasa.ac.at/web/home/research/researchPrograms/air/ECLIPSEv5.html,
last access: 27 February 2019).
ECLIPSEv5a is available in 5-year intervals from 2005 onwards,
and in this study we have chosen data for 2015 and 2030.
The ECLIPSE v5a emissions were re-gridded using the TNO-MACC-III
0.125×0.0625 long–lat emission
distribution for the year 2011. During the re-gridding process
only the spatial distribution of the ECLIPSE v5a emissions was modified,
while the national and sector totals remained unchanged. Where TNO-MACC-III
emissions are not available (such as northern Africa), the gridded ECLIPSE v5a
emissions were interpolated to the TNO-MACC grid resolution. Any missing
sectors for countries which were included in the TNO-MACC-III emission data
were also completed from the interpolated ECLIPSE v5a emissions.
In reality land-based emissions will change between years. Annual emissions
from years 2000 to 2016 for the European countries are listed in
. In the Baltic region reported changes in country emission
are small, with the exception of SOx emissions in Poland dropping
by almost 20 % from 2014 to 2016.
In regard to ship emissions in the BAS, we use emission data as
provided by the FMI (Finish Meteorological Institute) for the year 2014
(i.e. with 1 % maximum sulfur
content in fuels in the SECA) and 2016 (maximum sulfur content
reduced to 0.1 % in the SECA). For the remaining sea
areas, ship emissions for the year 2015 are used from a previous
global data set .
The emissions from shipping have been calculated with the Ship Traffic
Emission Assessment Model (STEAM) based on ship movements from
the AIS which provides real-time
information on ship positions. The model requires as input
detailed technical specifications of all onboard fuel-consuming systems
and other relevant technical details for all ships considered. The
data from constituted the most significant source
of this information. The STEAM model is described in
and
.
Hourly emission grids for Baltic Sea ship emissions were produced based
on vessel-specific modelling, considering the changes in fuel sulfur
content that occurred between 2014 and 2016.
In STEAM scrubbers can operate in closed- or open-loop mode, depending on
the equipment installed. If a hybrid scrubber system is known to be
installed, it is assumed to operate in open-loop mode when the vessel
operates in an area where open-loop systems are feasible. Closed-loop mode
of a hybrid scrubber is assumed in the Bothnian Bay and restricted zones,
like German waters. If a vessel has an open-loop scrubber installed and it
enters a restriction zone, the model assumes a fuel switch to low-sulfur
fuels. Emission modelling uses scrubber equipment type (closed/open/hybrid),
vessel identity, and installation date as input to emission modelling. All
future scrubber scenarios introduce hybrid scrubbers to the fleet.
Globally, during 2014
there were 77 vessels using a scrubber, of which 30 % were of open-loop,
48 % of closed-loop, and 22 % of hybrid type. By 2016 scrubber installations
were doubled globally to 155 units. In the Baltic Sea area during 2016,
there were 85 vessels operating a scrubber releasing 73 million tonnes
of wash water into the sea. Almost all of this (99.8 %) discharge came
from open-loop operation of scrubbers.
Ship-emitted pollutants were modelled using AIS data for the years 2014 and 2016.
Any changes in vessel activity, fleet size, and development will have an
impact on energy use and all pollutant emissions. However, the sulfur rule
was the only significant change which had a large impact on emitted
pollutants. Both PM and SOx were reduced by this change, but only
the sulfate fraction of PM was reduced accordingly, whereas other components
of PM were less affected.
From 2021 onward, NOx emissions for new ships have to comply with
IMO Tier 3 regulations. These contributions were taken into account
in the emission modelling.
Future emission projections for the year 2030 also include changes in
energy efficiency improvements, modelled following the method of
, which goes beyond the Energy Efficiency Defined Index
(EEDI) requirements of the IMO;
fleet size increase;
vessel size growth, assuming a linear annual
growth dependent on ship types.
Annual growth rates in fleet size are implemented as percentage increase
per type of ship: for example, if the annual percentage growth is n % for
container ships, we duplicate n % of the container ships in the current
fleet in the following year.
The following growth rates are assumed for vessel DWT:
vehicle carriers and RoRo: 1.25 % per annum;
dry cargo: 0.4 % per annum;
container carriers: 1.2 % per annum;
liquid cargo: 2.0 % per annum;
passenger vessels, ferries, and high-speed craft: 0.3 % per annum;
cruise ships: 0.3 % per annum;
fishing vessels: 0.3 % per annum.
Vessel size growth for other types was set to zero. For those vessels,
the vessel size remains at the 2014 level.
As the ship emission data are used for multiple meteorological years (see
the next section), we did not retain the high (hourly) temporal resolution
in the data, but rather aggregated them to monthly resolution before
use in the chemistry transport model.
Model calculations of air pollutants and depositions
Concentrations of air pollutants and depositions of sulfur and
nitrogen have been calculated with the EMEP MSC-W model (hereafter
“EMEP model”), version rv4.14, at 0.1×0.1∘ resolution for the
domain between 30∘ W and 45∘ E and between 30 and 75∘ N.
A detailed description of the EMEP model can be found in ,
with later model updates being described in , and
references therein. The EMEP model is available as open source
(see https://github.com/metno/emep-ctm, last access: 27 February 2019) and is regularly evaluated
against measurements as part of the EMEP status reports. See
for evaluations of the
meteorological years 2014, 2015, and 2016, respectively. In addition, the EMEP
model has successfully participated in model intercomparisons and model
evaluations presented in
a number of peer-reviewed publications: ,
, , , , and .
evaluated depositions of sulfur and nitrogen species in Europe
calculated by 14 regional models, showing good results for the EMEP model.
In the present study the model is driven by meteorological data from the
European Centre for Medium-Range Weather Forecasts (ECMWF) based on the
CY40R1 version of their IFS (Integrated Forecast System) model. All
simulations for this paper have been run for the 3 meteorological
years 2014, 2015, and 2016 and then averaged, in order to cancel out
meteorological variability. The simulations are the following.
Present_Base: base case with ship emissions of 2016. Land-based
emissions for 2015 (from ECLIPSEv5).
Present_NoShip: as Present_Base, but without ship emissions in the BAS.
Present_HiSulphur: as Present_Base, but with ship emissions of
2014 (i.e. high sulfur content) in the BAS.
Future_Base: ship emissions of 2030 (assuming NECA and business-as-usual development) and land-based emissions of 2030 (from ECLIPSEv5).
Future_NoShip: as Future_Base, but without ship emissions in the BAS.
The emissions are also summarised in Table .
In the future scenarios it is assumed that ships that are in compliance with
the NECA regulations will operate the equipment (i.e. be compliant) also
when sailing outside the NECA.
All model scenarios have been calculated for the 3
meteorological years 2014, 2015, and 2016. In the comparisons to
measurements in Table only year 2016 model
calculations are shown. The land-based ECLIPSE
emissions for 2016 have been interpolated between 2015 and 2020.
SECA regulations for the North Sea are included in the remaining
sea ship emissions. The 2020 sulfur cap is included in the
2030 ship emissions outside the SECAS.
In this section model results for parts of Europe centred
around the BAS are shown. Concentrations and depositions are
shown as averages for 3 meteorological years for Present_Base
and Future_Base and for differences between the two Base runs
and the perturbation
scenarios as described in Sect. . The impact
on PM2.5 levels and on the depositions of oxidised
nitrogen and sulfur species derived from the perturbation
model runs presented here forms the basis of upcoming papers
discussing the effects on human health
and assessing the environmental impacts,
including the exceedances of critical loads from
ship emissions in the BAS .
In the EMEP model results for 2016 compared to
measurements are discussed in detail. Although the model setup is not
completely identical, the results are qualitatively very similar.
The model underestimates NO2.
Measured PM2.5 is also underestimated, and results for the
individual PM2.5 components are mixed, with SO4
underestimated, whereas other components are overestimated compared to
measurements.
Annual average measured (Obs) and model-calculated
concentrations (Calc) of NO2 and SO2
for the present (2016) Base, NoShip, and HiSulphur scenarios.
The figure continues on the next page with SO4 and PM2.5.
Also listed are normalised mean bias (NMB), the daily correlations
(Corr.), and rms errors (rms) between model and measurements. For Hallahus
there are PM2.5 measurements only for parts of the year,
and bias, correlations, and rms errors are not listed. The time-series
plots for the same sites are shown in Appendix .
Km Balt. is a classification of the distance in kilometres
between the stations and the Baltic Sea coast. The distance is
equal to or smaller than the distance listed. The positions of the
measurement sites and the time-series plots are shown in
Appendix .
(a, b) Concentrations of NO2 and PM2.5 in the
Present_Base case. (c, d) Present percentage contribution from
BAS ship emissions to NO2
and PM2.5 after the new sulfur regulations. (e) Percentage contribution to PM2.5 concentrations before the
new sulfur regulations.
Air pollution due to Baltic Sea shipping
Concentrations of NO2
for Present_Base are shown in
Fig. a. The lifetime of NO2 is relatively short,
and as a result the concentrations largely reflect the locations of the main
source areas. Concentrations of NO2 are high in central Europe and
in and around the English Channel, with markedly lower
concentrations north and east of the BAS. In the NOS and the BAS
the major ship tracks are clearly visible. Figure c
shows the difference between the Present_Base and Present_NoShip
scenarios. The calculations show that ship emissions account for more
than 50 % of NO2 in central parts of the BAS and for a substantial
percentage also in coastal zones, in particular in Denmark, southern parts
of Sweden and Finland, and the Baltic states (Estonia, Latvia, and Lithuania).
This is also illustrated in Table ,
where measured NO2
at sites located in the BAS coastal regions are compared to the
Present_Base, Present_NoShip, and Present_HiSulphur model calculations
calculated with 2016 meteorology. The position of the measurement sites and
the corresponding time-series plots for NO2 are shown in Appendix . In the Present_NoShip case NO2 levels are clearly
underestimated and correlations and rms errors deteriorated compared to
the Present_Base calculation, in particular for those sites located very close
to major shipping routes. The comparisons with measurements
convincingly show that these measurements can only be reproduced when BAS
ship emissions are included. The contributions to individual
countries will be further discussed in a later section.
As shown in Table , measured SO2 levels for 2016 are
relatively well reproduced by the model for the Present_Base calculation.
The position of the measurement sites and the corresponding time-series
plots for SO2 are shown in Appendix .
The effects of excluding the BAS ship emissions in the Present_NoShip
scenario have only minor effects on the SO2 levels. Replacing
2016 BAS emissions with 2014 ones (Present_HiSulphur) has much larger
effects, resulting in an overestimation of SO2 levels at most of
the sites listed in Table , and in particular for Anholt and
Råö, located very close to the shipping routes. This clearly illustrates
the effects of the stricter SECA regulations. With the high ship emissions
of 2014, the measurements for 2016 can not be reproduced. This is also a
strong indication
that the ships are largely in compliance with the SECA regulations.
As for NO2, the contributions to individual countries are discussed
further in a later section.
PM2.5 in the atmosphere is a mixture of many chemical species
of both natural and anthropogenic origins. It is emitted as a
primary pollutant and formed as a secondary pollutant in the atmosphere.
As a result PM2.5 concentrations
are more spread out compared to NO2.
Concentrations decrease from south to north from a maximum
in central Europe. As shown in Fig. d the percentage
contributions from BAS shipping, calculated as
Present_Base–Present_NoShip, are much smaller for PM2.5
than for NO2, but with noticeable contributions in coastal
zones, in particular in parts of Denmark, Sweden, and Finland.
Figure e shows higher contributions when assuming
BAS shipping at 2014 levels (Present_HiSulphur), prior to the
implementation of the stricter SECA regulations. These results are
also illustrated in the comparisons of model scenario calculations
at the measurement sites located in BAS coastal regions as listed in
Table . The positions of the measurement sites and the
corresponding time-series plots for PM2.5 are shown in
Appendix .
For PM2.5 differences between the Present_Base
and Present_NoShip cases are much smaller than for
NO2. Likewise, differences are smaller than for SO2
between Present_Base and Present_HiSulphur. In Table
we also show measured and model-calculated concentrations of SO4.
Continuing a downward trend from the late 1980s, land-based sulfur emissions
have decreased by more than 50 %, i.e. more than for any other of the major air
pollutants , and thus the importance of sulfur in particle
formation has decreased relative to other anthropogenic emitted species
and natural sources. In the SECAs the sulfur content in marine
fuels has decreased from the global average of about 2.5 % to 1 % in 2011
and finally to 0.1 % in 2015. As a result of these large emission reductions
the fraction of SO4 in PM2.5 in the BAS region has
decreased even further here.
At the sites in Table both the measured and model-calculated
fractions of SO4 in PM2.5 are about 0.15. As SO4
makes up a moderate portion of the PM2.5 composition,
this fraction increases only by a small amount with the Present_HiSulphur
scenario.
The model results underestimate the measurements at most of the sites listed.
Based only on the comparisons between measurements and the different model
scenarios for PM2.5, one can not conclude that the Present_Base
scenario is more realistic than the other two.
As for NO2 and SO2, the contributions
to individual countries are discussed further in a later section.
(a, b) Calculated depositions of oxidised nitrogen and sulfur.
(c, d) Present percentage contributions from BAS ship emissions to
depositions of oxidised nitrogen and oxidised sulfur with
reference to Base 2016. (e) Percentage contribution to
depositions of oxidised sulfur with reference to 2014 BAS emissions.
Depositions of sulfur and nitrogen from Baltic Sea shipping
Total depositions (wet and dry) of oxidised sulfur and nitrogen
for Present_Base are shown in
Fig. a, b. The highest depositions of both sulfur
and nitrogen are seen over central Europe. For nitrogen, high levels of
depositions also extend into northern Germany and Denmark.
Based on the difference between Present_Base and Present_NoShip, a
significant amount of the nitrogen depositions can be attributed to BAS
shipping (Fig. c), contributing
more than 15 % of the total nitrogen depositions in major parts of
the BAS and also in parts of Sweden, Finland, and the Baltic states
(Estonia, Latvia, and Lithuania). Dry deposition is parameterised as a function
of subgrid-scale ecosystems and is typically higher than the grid average
for forest ecosystems (both coniferous and deciduous). This will affect
the calculations of critical loads for acidification and eutrophication as
the subgrid-scale ecosystem depositions are used in the critical load
calculations. Critical loads will be
discussed in a companion paper .
Figure d shows that the calculated contributions
from BAS shipping in 2016 to depositions of sulfur are very low
(Present_Base–Present_NoShip) and much lower than what has been
calculated assuming 2014 emissions (Present_HiSulphur–Present_Base)
as shown in Fig. e, with percentage
contributions exceeding 10 % in many coastal zones.
Annual average measured (Obs) and model-calculated
concentrations (Calc.) in precipitation of oxidised nitrogen in
mgNL-1 and oxidised sulfur in mg(inS)L-1 in 2016
for the present Base, NoShip, and HiSulphur scenarios. Also listed
are the normalised mean bias (NMB), the daily correlations
(Corr.), and rms errors (rms) between
model and measurements. Km Balt. is a classification of the
distance in kilometres between the stations and the Baltic
Sea coast. The distance is equal to or smaller than the distance
listed. The position of the measurement sites and the time-series
plots are shown in Appendix .
Wet dep. oxN Base HiSulphur NoShip StationKm Balt.ObsCalc.NMBCorr.rmsCalc.NMBCorr.rmsCalc.NMBCorr.rmsBredkälen2000.150.14-0.070.630.380.14-0.070.620.280.12-0.200.610.27Råö100.550.800.450.571.210.800.450.571.210.720.310.571.15Preila100.650.760.170.381.620.760.170.381.620.650.000.361.65Lahemaa200.480.39-0.190.160.950.39-0.190.160.940.32-0.330.160.94Leba100.730.780.070.591.050.780.070.591.040.67-0.080.531.10Wet dep. oxS Base HiSulphur NoShip StationKm Balt.ObsCalc.NMBCorr.rmsCalc.NMBCorr.rmsCalc.NMBCorr.rmsBredkälen2000.110.110.000.390.310.120.090.400.310.110.000.390.31Råö100.230.400.740.540.660.450.960.550.700.400.740.530.65Preila100.380.560.470.371.200.600.580.391.200.550.450.371.21Leba100.420.510.210.480.850.560.330.530.830.510.210.470.85
These findings for the depositions of oxidised nitrogen and sulfur are
also illustrated in Table ,
where measured concentrations in
precipitation at sites located in the BAS coastal regions are compared to the
Present_Base, Present_NoShip, and Present_HiSulphur model calculations.
Compared to
Present_Base, averaged concentrations in precipitation are
about 14 % lower for oxidised nitrogen when BAS ship emissions are excluded
(Present_Base–Present_NoShip). The effects of the
stricter SECA regulations are demonstrated by an increase of about 9 %
in the calculated concentrations of oxidised sulfur in precipitation
in the Present_HiSulphur scenario compared to the Present_Base calculation.
For each country, the upper bar shows the future (2030) case
and the lower bar the present case country average
concentration. (a)SO2, (b)NO2,
(c) PM2.5, and depositions of oxidised
sulfur (d) and oxidised nitrogen (e). The black and
green bars represent the Present_NoShip and Future_NoShip
calculations, respectively. The additional contributions
from BAS (Add Baltic) are shown in blue and the additional
effect assuming high sulfur fuel emissions (Add Baltic 2014)
in red. (These are also given as numbers.
Numerical values for NO2 Add Baltic 2014 and for SO2
Add Baltic are not given as they are very small.)
Contributions to individual countries from BAS shipping.
Figure shows the concentrations of NO2,
SO2, and PM2.5 and the depositions of oxidised sulfur
and oxidised nitrogen averaged over the individual countries
bordering the BAS. The black (Present) and green (Future)
bars represent contributions from all other sources
(both anthropogenic and natural) than BAS shipping. The blue part
of the bars represents the (present and future) contributions from BAS shipping
calculated as Base–NoShip, where Base can be either Present_Base or
Future_Base and NoShip can be either Present_NoShip or Future_NoShip.
The sum of the black or blue and green parts of the bars then adds up to
the total concentrations and depositions averaged over the individual
countries bordering the BAS for the Present_Base and Future_Base
scenarios. The red part is the additional BAS contributions assuming
BAS ship emissions at 2014 levels calculated as
Present_HiSulphur–Present_Base. The calculations
are made assuming linearity. Previous calculations, adding up
contributions from different sources, have shown that this assumption
is reasonable . Irrespective
of species and depositions, the largest contributions are seen for smaller
countries with long coastlines exposed to the BAS such as Denmark and the Baltic
states, and the least for large countries such as Germany and Poland with major
parts of their areas located far from the shipping routes.
Following the expected reductions between 2016 and 2030 in both land-based
and ship emissions, calculated concentrations and depositions
are reduced over the 2016 to 2030 time span. For SO2 and
depositions
of sulfur, BAS shipping is already an insignificant source in 2016 and the
differences between 2030 and 2016 are almost entirely caused by changes in
land-based emissions. For NO2 concentrations and depositions of oxidised
nitrogen, reductions in land-based and BAS ship emissions both contribute
to the improvements in pollution levels. In the BAS region the fractional
reductions in future concentrations attributed to (mainly) land-based
and BAS ship emissions are roughly in the same range.
The largest contributions from BAS shipping are seen for NO2
(Fig. b), depositions of oxidised nitrogen
(Fig. c), and partially also for SO2
(Fig. a) when assuming 2014 emissions (Present_HISulphur).
However, for
SO2 calculated contributions are insignificant following the
implementation of the stricter SECA in 2015. The same conclusion also holds
for sulfur depositions (Fig. d). PM2.5
contributions from BAS shipping are markedly smaller than for NO2.
Contributions are higher when assuming Present_HiSulphur emissions.
After the implementation of stricter SECA regulations in 2015,
PM2.5 from shipping mainly
originates from NO2 and, in part, primary PM emissions.
As shown in Fig. d, e, elevated PM2.5
concentrations from BAS shipping are mainly seen in coastal zones
close to shipping lanes. Much of these coastal zones is densely
populated. When assessing the health effects of PM in a forthcoming
companion paper ,
population-weighted PM2.5 concentrations are used.
(a) SOMO35 in ppb days where black bars represent Present_Base levels.
(b) Changes in annual ozone in ppb (annual average ozone is in the
30–35 ppb range in all countries). For both SOMO35 and annual ozone green
bars represent changes in levels from 2016 to 2030
(Future_Base–Present_Base),
red bars contributions from BAS (Present_Base–Present_NoShip),
and blue bars contributions from BAS in 2030 (Future_Base–Future_NoShip).
Figure (left) shows calculated SOMO35
SOMO35 is
the indicator for health impacts recommended by the WHO calculated as the daily
maximum of 8 h running ozone maximum over 35 ppb.
as an average for
countries around the Baltic Sea and the effect of BAS shipping. The effects
on annually averaged ozone are shown in the same figure (right). For all
countries annually averaged ozone is in the 33–37 ppb range. For most
countries both SOMO35 and annually averaged ozone increase only slightly as a
result of BAS shipping, and relatively more so for SOMO35 than for annually
averaged ozone. However, in Denmark emissions from BAS shipping result in
a decrease in annually averaged ozone with present emissions.
Changes in ozone are caused by a combination of ozone production,
mainly in the summer months, and ozone titration by
NO, mainly in winter. In winter reductions in NOx emissions
(including reductions in emissions from ships) result in a decrease in
ozone titration and subsequently higher ozone levels. This is illustrated
in Fig. a with ozone winter levels in 2030 higher than in
2016 throughout northern and central Europe. Ozone production dominates in
the summer months (Fig. b) and, with the exception of a
region around the English Channel, the expected reductions
in the emissions of ozone precursors result in lower ozone levels.
For SOMO35 (Fig. c, d) the relative increase in winter is
much smaller as ozone is largely below the 35 ppb threshold. In summer
the increase in ozone from present to future caused by less titration
around the English Channel is confined to a much smaller area. As a result
annually averaged ozone production and titration in the BAS region partially
cancel out, and for some regions and countries titration dominates the annual
values. As shown in Fig. (green bars), the expected
emission reductions (land-based and from ships) from the years 2016 to 2030
result in overall reductions in ozone levels (both annually averaged ozone
and SOMO35) for all countries except Germany and Denmark, where
calculated average ozone levels are higher in 2030 (but SOMO35 is reduced).
In 2030 the additional emissions from BAS shipping result in increased
SOMO35 and annually averaged ozone in all countries.
(blue bars in Fig. ).
These results are in good agreement with detailed model calculations with
projected emission changes, demonstrating a future transition from
NMVOC
NMVOC – non-methane volatile organic compounds
-limited
to NOx-limited regimes in large parts of Europe
north of the Alps .
It has to be noted that in our model calculations the ship emissions are
instantly diluted throughout the model grid cell where the emissions occur.
Previous studies have shown that
this could lead to an overestimation of ozone formation. However,
found that the overestimation caused by instant dilution
was small in polluted regions, such as the central parts of the BAS.
Conclusions
Our calculations clearly show that, following the stricter SECA regulations
from 1 January 2015, sulfur emissions from BAS shipping
now contribute little to depositions of oxidised sulfur and PM2.5
concentrations in air. This is in contrast to
pre-2015 conditions when less stringent sulfur regulations were in place,
and even more compared to pre-2011 conditions when up to 1.5 % in sulfur was
allowed in marine fuels in the SECAs.
Still, emissions of NOx and particles from BAS shipping continue
to be high, causing health problems and other detrimental impacts
on the environment in the BAS region. At present emission levels, particles
originating from BAS shipping are mainly formed from NOx emissions
and partially by primary particles other than SO4.
Currently very few openly available emission factor data exist for marine
diesels using ultra-low sulfur heavy fuel oil and covering the whole
engine load range from zero to 100 %. Hypothetically, with these cases
STEAM calculates the SOx emission factor based on available sulfur
in the fuel. If this was close to zero, then the SOx emission factor
is very small. The conversion of fuel sulfur to sulfate has a similar
mechanism, and only a small fraction of available sulfur is converted to
SO4. Again, the emission factor for SO4 would be very small
if the fuel sulfur content is close to zero. For other species of PM,
like EC, OC, and ash, emission factors will be similar to with HFO,
and thus emissions of non-sulfur particles from BAS shipping are assumed
to be virtually unaffected by the SECA regulations.
EMEP source–receptor calculations for the individual countries
(see EMEP country reports for the year 2016; )
show that, for many countries in the region, BAS shipping is among the
five to six largest regions/countries contributing to SIA (secondary inorganic
aerosol). SIA is a major constituent of PM2.5, typically ranging
from about 30 % to 60 % of PM2.5 mass in (scarce) measurements and
in EMEP model calculations . Other constituents in
PM2.5 include sea salt and organics (both natural and anthropogenic)
with no or minor contributions from shipping, as well as primary particles.
As a result, the percentage contributions from BAS shipping to SIA are
of the order of a factor of 2 higher than for PM2.5.
As the natural part of PM2.5 (and likewise PM10) is
not included in the EMEP source–receptor calculations , they
bear some resemblance to SIA. Thus the relative contributions from BAS
shipping presented here are lower than the above source–receptor
calculations as compared to PM2.5 (and likewise PM10)
of both anthropogenic and natural origin.
In a global model calculation with ship emission from the BAS and
NOS also provided by FMI, source–receptor relationships are in the
same range as the reported EMEP results for 2014 and 2016 .
It should however be noted that the EMEP source–receptor relationships are
calculated by perturbing the emissions by 15 %, whereas in this study we
have excluded the emissions altogether in the NoShip scenarios.
The largest contributions from shipping
are calculated for the coastal zones. Many of the larger cities in the BAS
region are located in the coastal zones where contributions can be of the
order of 20 % for NO2 but smaller (up to 5 %–10 %) for
PM2.5. In the companion paper health effects
from BAS shipping have been adjusted to the population density, resulting
in a proportionally higher contribution from shipping than presented
here as area-averaged concentrations.
BAS ship emissions also affect the formation of ground-level ozone. In much
of the BAS region NO2 levels are already influenced by large land-based
sources, and additional contributions from BAS shipping to ozone and
ozone metrics, exemplified by SOMO35, are moderate and for several regions
even negative. In this paper we have shown that for most countries future ozone
and ozone metrics are expected to decrease from their present levels.
In addition to influencing particle formation and ozone levels, NOx
emissions also contribute to the depositions of oxidised nitrogen, causing
exceedances of critical loads for acidification and in particular
eutrophication. Depositions do however depend on the type of land cover.
In the EMEP model the calculations of dry depositions are
made separately for each sub-grid land-cover classification. These sub-grid
estimates are aggregated to provide output deposition estimates for
broader ecosystem categories as deciduous and coniferous forests. The
ecosystem-specific depositions are not shown here, but will be used in a
companion paper when calculating exceedances of critical
loads for acidification and eutrophication.
A significant portion of the depositions of oxidised
nitrogen is due to BAS shipping. This is also corroborated by the
source–receptor
calculations for the individual countries in Europe for 2016: see
, where they calculate that BAS shipping is the
largest contributor to oxidised nitrogen deposition in Estonia (with 14 %)
and among the three to five largest contributors in several other countries
in the region. As discussed above, these depositions are projected to be
gradually reduced following the implementation of the NECA regulations,
with relative reductions largely comparable to the decrease from other
anthropogenic sources.
Presently there are no further emission mitigation regulations
targeted for the Baltic Sea and the North Sea apart from the NECA
regulation entering into force in 2021. This regulation is expected to
result in gradual reductions in PM2.5 concentrations and in
depositions of nitrogen from BAS shipping, as shown in our calculations for
future versus present conditions. The relative reductions are largely
comparable to the decrease from other anthropogenic sources in the region.
However, according to the target set by the IMO is
“to reduce CO2 emissions per
transport work, as an average across international shipping, by
at least 40 % by 2030, pursuing efforts towards 70 % by 2050, compared to
2008; and GHG emissions from international shipping to peak and decline
as soon as possible and to reduce the total annual GHG emissions by at
least 50 % by 2050
compared to 2008 whilst pursuing efforts towards phasing them out
as called for in the vision as a point on a pathway of CO2
emissions reduction consistent with the Paris Agreement temperature goals.”
It is unlikely that this goal can be reached without substantial
penetration of zero emission ships. If a portion of these
zero emission ships run on electricity or hydrogen in 2030 they will be
zero emission also for sulfur, nitrogen, and PM2.5 (in addition to
CO2), potentially resulting in reductions in these air pollutants
beyond what is assumed in the Future_Base scenario in this paper.
Code availability
The EMEP model is available as open source
(see https://github.com/metno/emep-ctm, code version rv4.14, last access: 29 October 2019) 10.5281/zenodo.3355041.
Data availability
Model output data are available upon request to the first author.
This Appendix contains time-series plots for NO2, SO2,
and PM2.5 for the meteorological year 2016. Measured and model-calculated annual average concentrations, correlations, and rms errors
are listed in Table in the main text. For many sites
the time series for the different model scenarios are virtually identical,
and the HiSulphur and NoShip scenarios are masked by the
Base scenario.
Location of the measurement sites shown in Figs. to
and listed in Tables and .
Measured and model-calculated present (2016) concentrations of NO2.
Present model-calculated results are shown for the Base, HiSulphur,
and NoShip scenarios. The HiSulphur calculations are
not visible as they are almost identical to Present_Base.
Measured and model-calculated present (2016) concentrations of SO2.
Present model-calculated results are shown for the Base, HiSulphur,
and NoShip scenarios.
Measured and model-calculated present (2016) concentrations of PM2.5.
Present model-calculated results are shown for the Base, HiSulphur,
and NoShip scenarios.
Difference between Future_Base and Present_Base for average surface ozone
in winter (a) and summer (b) and for SOMO35 in winter (c) and summer (d).
Author contributions
JEJ made the model calculations and wrote most of the paper. MG assisted in designing the model scenarios and in writing the paper. JPJ and LJ provided the ship emission data for both the present and future scenarios. JPJ also assisted in the writing of the paper.
Competing interests
The authors declare that they have no conflict of interest.
Special issue statement
This article is part of the special issue “Shipping and the Environment – From Regional to Global Perspectives (ACP/OS inter-journal SI)”. It is not associated with a conference.
Acknowledgements
Computer time for EMEP model runs was supported by the Research Council
of Norway through NOTUR project EMEP (NN2890K) for CPU
and NorStore project European Monitoring and Evaluation Programme
(NS9005K) for storage of data and partially by UNECE through the EMEP programme under CLRTAP. Surface measurements have been
made available
through the EBAS web site at http://ebas.nilu.no/Default.aspx, last access: 27 February 2019.
Financial support
This research has been supported by European Union (European Regional Development Fund) project EnviSum (grant no. ERDF Ro27).
Review statement
This paper was edited by Huan Liu and reviewed by three anonymous referees.
ReferencesAngelbratt, J., Mellqvist, J., Simpson, D., Jonson, J. E., Blumenstock, T., Borsdorff, T., Duchatelet, P., Forster, F., Hase, F., Mahieu, E., De Mazière, M., Notholt, J., Petersen, A. K., Raffalski, U., Servais, C., Sussmann, R., Warneke, T., and Vigouroux, C.: Carbon monoxide (CO) and ethane (C2H6) trends from ground-based solar FTIR measurements at six European stations, comparison and sensitivity analysis with the EMEP model, Atmos. Chem. Phys., 11, 9253–9269, 10.5194/acp-11-9253-2011, 2011.Barregård, L., Molnàr, P., Jonson, J. E., and Stockfeld, L.: Impact on
population health of emissions of pollutants from Baltic shipping,
Int. J. Env. Res. Pub. He., 59, 11,
10.3390/ijerph16111954, 2019.Beekmann, M. and Vautard, R.: A modelling study of photochemical regimes over Europe: robustness and variability, Atmos. Chem. Phys., 10, 10067–10084, 10.5194/acp-10-10067-2010, 2010.Brandt, J., Silver, J. D., Christensen, J. H., Andersen, M. S., Bønløkke, J. H., Sigsgaard, T., Geels, C., Gross, A., Hansen, A. B., Hansen, K. M., Hedegaard, G. B., Kaas, E., and Frohn, L. M.: Assessment of past, present and future health-cost externalities of air pollution in Europe and the contribution from international ship traffic using the EVA model system, Atmos. Chem. Phys., 13, 7747–7764, 10.5194/acp-13-7747-2013, 2013.Claremar, B., Haglund, K., and Rutgersson, A.: Ship emissions and the use of current air cleaning technology: contributions to air pollution and acidification in the Baltic Sea, Earth Syst. Dynam., 8, 901–919, 10.5194/esd-8-901-2017, 2017.Colette, A., Granier, C., Hodnebrog, Ø., Jakobs, H., Maurizi, A., Nyiri, A., Bessagnet, B., D'Angiola, A., D'Isidoro, M., Gauss, M., Meleux, F., Memmesheimer, M., Mieville, A., Rouïl, L., Russo, F., Solberg, S., Stordal, F., and Tampieri, F.: Air quality trends in Europe over the past decade: a first multi-model assessment, Atmos. Chem. Phys., 11, 11657–11678, 10.5194/acp-11-11657-2011, 2011.Colette, A., Granier, C., Hodnebrog, Ø., Jakobs, H., Maurizi, A., Nyiri, A., Rao, S., Amann, M., Bessagnet, B., D'Angiola, A., Gauss, M., Heyes, C., Klimont, Z., Meleux, F., Memmesheimer, M., Mieville, A., Rouïl, L., Russo, F., Schucht, S., Simpson, D., Stordal, F., Tampieri, F., and Vrac, M.: Future air quality in Europe: a multi-model assessment of projected exposure to ozone, Atmos. Chem. Phys., 12, 10613–10630, 10.5194/acp-12-10613-2012, 2012.
Corbett, J., Winebrake, J., Green, E., Kasibhatla, P., and Laurer, E. A.
V.: Mortality from ship emissions: A global assessment, Environ. Sci.
Tech., 4, 8512–8518, 2007.Dore, A. J., Carslaw, D. C., Braban, C., Cain, M., Chemel, C., Conolly, C.,
Derwent, R. G., Griffiths, S. J., Hall, J., Hayman, G., Lawrence, S.,
Metcalfe, S. E., Redington, A., Simpson, D., Sutton, M. A., Sutton, P., Tang,
Y. S., Vieno, M., Werner, M., and Whyatt, J. D.: Evaluation of the
performance of different atmospheric chemical transport models and
inter-comparison of nitrogen and sulphur deposition estimates for the UK,
Atmos. Environ., 119, 131–143, 10.1016/j.atmosenv.2015.08.008,
2015.EMEP MSC-W: metno/emep-ctm: OpenSource rv4.15 (201709) (Version rv4_15), Zenodo, 10.5281/zenodo.3355041, 30 July 2019.
EMEP Status Report 1/2018: Transboundary particulate matter, photo-oxidants,
acidifying and eutrophying components, EMEP MSC-W & CCC & CEIP,
Norwegian Meteorological Institute (EMEP/MSC-W), Oslo, Norway, 2018.Endresen, Ø., Sørgård, E., Sundet, J., Dalsøren, S., Isaksen, I.,
Berglen, T., and Gravir, G.: Emission from international sea transport and
environmental impact, J. Geophys. Res., 108, D17, 10.1029/2002JD002898, 2003.
Eyring, V., Isaksen, I., Berntsen, T., Collins, W., Corbett, J., Endresen,
Ø., Grainger, R., Moldanova, J., Schlager, H., and Stevenson, D.:
Transport impacts on atmosphere and climate: Shipping, Atmos. Environ., 44,
4735–4771, 2007.Gauss, M., Tsyro, S., Benedictow, A., Fagerli, H., Hjellbrekke, A.-G., Aas, W.,
and Solberg, S.: EMEP/MSC-W model performance for acidifying and eutrophying
components, photo-oxidants and particulate matter in 2014, Supplementary
material to EMEP Status Report 1/2016, available at:
https://www.emep.int/ (last access: 27 February 2019), The Norwegian
Meteorological Institute, Oslo, Norway, 2016.Gauss, M., Tsyro, S., Fagerli, H., Hjellbrekke, A.-G., Aas, W., and Solberg,
S.: EMEP MSC-W model performance for acidifying and eutrophying components,
photo-oxidants and particulate matter in 2015, Supplementary material to
EMEP Status Report 1/2017, available online at https://www.emep.int/ (last
access: 27 February 2019), The Norwegian Meteorological Institute, Oslo,
Norway, 2017.Gauss, M., Tsyro, S., Fagerli, H., Hjellbrekke, A.-G., Aas, W., and Solberg,
S.: EMEP MSC-W model performance for acidifying and eutrophying components,
photo-oxidants and particulate matter in 2016, Supplementary material to
EMEP Status Report 1/2018, available online at https://www.emep.int/ (last
access: 27 February 2019), The Norwegian Meteorological Institute, Oslo,
Norway, 2018.Huszar, P., Cariolle, D., Paoli, R., Halenka, T., Belda, M., Schlager, H., Miksovsky, J., and Pisoft, P.: Modeling the regional impact of ship emissions on NOx and ozone levels over the Eastern Atlantic and Western Europe using ship plume parameterization, Atmos. Chem. Phys., 10, 6645–6660, 10.5194/acp-10-6645-2010, 2010.IHS Global: SeaWeb database of the global ship fleet, Commercial content,
IHS Global, Chemin de la Mairie, Perly, Geneva),
available at: https://maritime.ihs.com/ (last access: 27 February 2019),
2017.IMO: Amendments to the annex of the protocol of 1997 to amend the
international convention for the prevention of pollution from ships 1973, as
modified by the protocol of 1978 relating thereto, Annex vi, IMO
(International Maritime Organization),
available at: http://www.imo.org/en/OurWork/Environment/PollutionPrevention/AirPollution/Documents/176%
2858%
29.pdf
(last access: 27 February 2019), 2008.IMO: RESOLUTION MEPC.286(71). Adopted on 7 July 2017. Amendments to the annex
of the protocol of 1997 to amend the international convention for the
prevention of pollution from ships, 1973, as modified by the protocol of 1978
relating there to Amendments to MARPOL Annex VI, available at:
http://www.imo.org/en/OurWork/Environment/PollutionPrevention/AirPollution/Documents/Res_MEPC_286%
2871%
29_Tier%
20III%
20ECA%
20and%
20BDN.pdf (last access: 27 February 2019),
IMO (International Maritime Organization),
2017.IMO: Adoption of the initial IMO strategy on reduction of GHG emissions from
ships and existing IMO activity related to reducing GHG emissions in the
shipping sector., Available at
https://unfccc.int/sites/default/files/resource/250_IMO%
20submission_Talanoa%
20Dialogue_April%
202018.pdf (last access: 5 April 2019),
IMO (International Maritime Organization), 2018.Jalkanen, J.-P., Brink, A., Kalli, J., Pettersson, H., Kukkonen, J., and Stipa, T.: A modelling system for the exhaust emissions of marine traffic and its application in the Baltic Sea area, Atmos. Chem. Phys., 9, 9209–9223, 10.5194/acp-9-9209-2009, 2009.Jalkanen, J.-P., Johansson, L., Kukkonen, J., Brink, A., Kalli, J., and Stipa, T.: Extension of an assessment model of ship traffic exhaust emissions for particulate matter and carbon monoxide, Atmos. Chem. Phys., 12, 2641–2659, 10.5194/acp-12-2641-2012, 2012.Jalkanen, J.-P., Johansson, L., and Kukkonen, J.: A comprehensive inventory of ship traffic exhaust emissions in the European sea areas in 2011, Atmos. Chem. Phys., 16, 71–84, 10.5194/acp-16-71-2016, 2016.Johansson, L., Jalkanen, J.-P., Kalli, J., and Kukkonen, J.: The evolution of shipping emissions and the costs of regulation changes in the northern EU area, Atmos. Chem. Phys., 13, 11375–11389, 10.5194/acp-13-11375-2013, 2013.Johansson, L., Jalkanen, J.-P., and Kukkonen, J.: Global assessment of shipping
emissions in 2015 on a high spatial and temporal resolution, Atmos.
Environ., 167, 403–415,
10.1016/j.atmosenv.2017.08.042,
2017.Jonson, J., Borken-Kleefeld, J., Nyíri, A., Posch, M., and Heyes, C.:
Impact of excess NOx emissions from diesel cars on air quality,
public health and eutrophication in Europe, Environ. Res. Lett., 12, 9,
10.1088/1748-9326/aa8850, 2017.Jonson, J., Gauss, M., Schulz, M., and Nyíri, A.: Emissions from
international shipping, in: Transboundary particulate matter, photo-oxidants,
acidifying and eutrophying components. EMEP Status Report 1/2018, pp. 83–98,
The Norwegian Meteorological Institute, Oslo, Norway,
available at: http://emep.int/publ/reports/2018/EMEP_Status_Report_1_2018.pdf
(last access: 27 February 2019), 2018.Jonson, J. E., Jalkanen, J. P., Johansson, L., Gauss, M., and Denier van der Gon, H. A. C.: Model calculations of the effects of present and future emissions of air pollutants from shipping in the Baltic Sea and the North Sea, Atmos. Chem. Phys., 15, 783–798, 10.5194/acp-15-783-2015, 2015.Kalli, J., Jalkanen, J.-P., Johansson, L., and Repka, S.: Atmospheric emissions
of European SECA shipping: long-term projections, WMU Journal of Maritime
Affairs, 12, 129–145, 10.1007/s13437-013-0050-9, 2013.Karl, M., Bieser, J., Geyer, B., Matthias, V., Jalkanen, J.-P., Johansson, L., and Fridell, E.: Impact of a nitrogen emission control area (NECA) on the future air quality and nitrogen deposition to seawater in the Baltic Sea region, Atmos. Chem. Phys., 19, 1721–1752, 10.5194/acp-19-1721-2019, 2019a.Karl, M., Jonson, J. E., Uppstu, A., Aulinger, A., Prank, M., Sofiev, M., Jalkanen, J.-P., Johansson, L., Quante, M., and Matthias, V.: Effects of ship emissions on air quality in the Baltic Sea region simulated with three different chemistry transport models, Atmos. Chem. Phys., 19, 7019–7053, 10.5194/acp-19-7019-2019, 2019b.Klein, H., Gauss, M., Nyíri, A., and Benedictow, A.: Transboundary air
pollution by main pollutants (S, N, O3) and PM, MSC-W Data Note 1/2018
Individual Country Reports, available at: https://www.emep.int (last access: 27 February
2019), The
Norwegian Meteorological Institute, Oslo, Norway, 2018.Kuenen, J. J. P., Visschedijk, A. J. H., Jozwicka, M., and Denier van der Gon, H. A. C.: TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling, Atmos. Chem. Phys., 14, 10963–10976, 10.5194/acp-14-10963-2014, 2014.Repka, S., Erkkilä-Välimäki, A., Törrönen, J., Jalkanen, J.-P., Jonson,
J. E., and Posch, M.: IMO regulation on ship-originated SOx and NOx in the Baltic
Sea – assessing the relevance of environmental impacts, in
preparation, 2019.Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á., and Wind, P.: The EMEP MSC-W chemical transport model – technical description, Atmos. Chem. Phys., 12, 7825–7865, 10.5194/acp-12-7825-2012, 2012.Simpson, D., Wind, P., Bergström, R., Gauss, M., Tsyro, S., and Valdebenito,
A.: Updates to the EMEP MSC-W model, 2017–2018, EMEP Status Report
1/2018, available at: http://emep.int/publ/reports/2018/EMEP_Status_Report_1_2018.pdf
(last access: 27 February 2019), The Norwegian Meteorological
Institute, Oslo, Norway,
2018.Sofiev, M., Winebrake, J. J., Johansson, L., Carr, E. W., Prank, M., Soares,
J., Vira, J., Kouznetsov, R., Jalkanen, J.-P., and Corbett, J. J.: Cleaner
fuels for ships provide public health benefits with climate tradeoffs,
Nature, 9, 406, 10.1038/s41467-017-02774-9, 2018.
Stjern, C. W., Samset, B. H., Myhre, G., Bian, H., Chin, M., Davila, Y., Dentener, F., Emmons, L., Flemming, J., Haslerud, A. S., Henze, D., Jonson, J. E., Kucsera, T., Lund, M. T., Schulz, M., Sudo, K., Takemura, T., and Tilmes, S.: Global and regional radiative forcing from 20 Tista, M., Wankmüller, R., Matthews, B., Mareckova, K., Fagerli, H., and
Nyíri, A.: Emissions in 2016, in: Transboundary particulate matter,
photo-oxidants, acidifying and eutrophying components. EMEP Status Report
1/2018, pp. 41–64, The Norwegian Meteorological Institute, Oslo, Norway,
available at: http://emep.int/publ/reports/2018/EMEP_Status_Report_1_2018.pdf
(last access: 27 February 2019), 2018.
Tsyro, S., Aas, W., Solberg, S., Benedictow, A., Fagerli, H., and Posch, M.:
Status of transboundary air pollution in 2016, in: Transboundary particulate
matter, photo-oxidants, acidifying and eutrophying components, EMEP Status
Report 1/2018, pp. 15–40, The Norwegian Meteorological Institute, Oslo,
Norway,
available at: http://emep.int/publ/reports/2018/EMEP_Status_Report_1_2018.pdf
(last access: 27 February 2019), 2018.Vinken, G. C. M., Boersma, K. F., Jacob, D. J., and Meijer, E. W.: Accounting for non-linear chemistry of ship plumes in the GEOS-Chem global chemistry transport model, Atmos. Chem. Phys., 11, 11707–11722, 10.5194/acp-11-11707-2011, 2011.Vivanco, M. G., Theobald, M. R., García-Gómez, H., Garrido, J. L., Prank, M., Aas, W., Adani, M., Alyuz, U., Andersson, C., Bellasio, R., Bessagnet, B., Bianconi, R., Bieser, J., Brandt, J., Briganti, G., Cappelletti, A., Curci, G., Christensen, J. H., Colette, A., Couvidat, F., Cuvelier, C., D'Isidoro, M., Flemming, J., Fraser, A., Geels, C., Hansen, K. M., Hogrefe, C., Im, U., Jorba, O., Kitwiroon, N., Manders, A., Mircea, M., Otero, N., Pay, M.-T., Pozzoli, L., Solazzo, E., Tsyro, S., Unal, A., Wind, P., and Galmarini, S.: Modeled deposition of nitrogen and sulfur in Europe estimated by 14 air quality model systems: evaluation, effects of changes in emissions and implications for habitat protection, Atmos. Chem. Phys., 18, 10199–10218, 10.5194/acp-18-10199-2018, 2018.