The sensitivities of emissions reductions for the mitigation of UK PM2.5

Abstract

The reduction of ambient concentrations of fine particulate matter
(PM2.5) is a key objective for air pollution control policies in the UK
and elsewhere. Long-term exposure to PM2.5 has been identified as a
major contributor to adverse human health effects in epidemiological studies
and underpins ambient PM2.5 legislation. As a range of emission sources
and atmospheric chemistry transport processes contribute to PM2.5
concentrations, atmospheric chemistry transport models are an essential tool
to assess emissions control effectiveness. The EMEP4UK atmospheric chemistry
transport model was used to investigate the impact of reductions in UK
anthropogenic emissions of primary PM2.5, NH3, NOx, SOx
or non-methane VOC on surface concentrations of PM2.5 in the UK for a
recent year (2010) and for a future current legislation emission (CLE)
scenario (2030). In general, the sensitivity to UK mitigation is rather
small. A 30 % reduction in UK emissions of any one of the above components
yields (for the 2010 simulation) a maximum reduction in PM2.5 in any
given location of ∼ 0.6 µg m−3 (equivalent to
∼ 6 % of the modelled PM2.5). On average across the UK,
the sensitivity of PM2.5 concentrations to a 30 % reduction in UK
emissions of individual contributing components, for both the 2010 and 2030
CLE baselines, increases in the order NMVOC, NOx, SOx, NH3
and primary PM2.5; however there are strong spatial differences in the
PM2.5 sensitivities across the UK. Consequently, the sensitivity of
PM2.5 to individual component emissions reductions varies between area
and population weighting. Reductions in NH3 have the greatest effect on
area-weighted PM2.5. A full UK population weighting places greater
emphasis on reductions of primary PM2.5 emissions, which is simulated
to be the most effective single-component control on PM2.5 for the 2030
scenario. An important conclusion is that weighting corresponding to the
average exposure indicator metric (using data from the 45 model grids
containing a monitor whose measurements are used to calculate the UK AEI)
further increases the emphasis on the effectiveness of primary PM2.5
emissions reductions (and of NOx emissions reductions) relative to the
effectiveness of NH3 emissions reductions. Reductions in primary
PM2.5 have the largest impact on the AEI in both 2010 and the 2030 CLE
scenario. The summation of the modelled reductions to the UK PM2.5 AEI
from 30 % reductions in UK emissions of primary PM2.5, NH3,
SOx, NOx and VOC totals 1.17 and 0.82 µg m−3 for the 2010 and 2030 CLE simulations, respectively (not accounting
for non-linearity).

Full text

Atmos. Chem. Phys., 16, 265–276, 2016
www.atmos-chem-phys.net/16/265/2016/
doi:10.5194/acp-16-265-2016
© Author(s) 2016. CC Attribution 3.0 License.
The sensitivities of emissions reductions for the mitigation
of UK PM2.5
M. Vieno1, M. R. Heal2, M. L. Williams3, E. J. Carnell1, E. Nemitz1, J. R. Stedman4, and S. Reis1,5
1Natural Environment Research Council, Centre for Ecology & Hydrology, Penicuik, UK
2School of Chemistry, The University of Edinburgh, Edinburgh, UK
3Environmental Research Group, Kings College London, London, UK
4Ricardo-AEA, Harwell, UK
5University of Exeter Medical School, Knowledge Spa, Truro, UK
Correspondence to: M. Vieno (vieno.massimo@gmail.com)
Received: 12 June 2015 – Published in Atmos. Chem. Phys. Discuss.: 5 August 2015
Revised: 20 November 2015 – Accepted: 7 December 2015 – Published: 18 January 2016
Abstract. The reduction of ambient concentrations of fine
particulate matter (PM2.5)is a key objective for air pollution
control policies in the UK and elsewhere. Long-term expo-
sure to PM2.5has been identified as a major contributor to
adverse human health effects in epidemiological studies and
underpins ambient PM2.5legislation. As a range of emission
sources and atmospheric chemistry transport processes con-
tribute to PM2.5concentrations, atmospheric chemistry trans-
port models are an essential tool to assess emissions control
effectiveness. The EMEP4UK atmospheric chemistry trans-
port model was used to investigate the impact of reductions
in UK anthropogenic emissions of primary PM2.5, NH3,
NOx, SOxor non-methane VOC on surface concentrations
of PM2.5in the UK for a recent year (2010) and for a future
current legislation emission (CLE) scenario (2030). In gen-
eral, the sensitivity to UK mitigation is rather small. A 30%
reduction in UK emissions of any one of the above compo-
nents yields (for the 2010 simulation) a maximum reduction
in PM2.5in any given location of ∼0.6µgm−3(equivalent
to ∼6 % of the modelled PM2.5). On average across the UK,
the sensitivity of PM2.5concentrations to a 30% reduction
in UK emissions of individual contributing components, for
both the 2010 and 2030 CLE baselines, increases in the or-
der NMVOC, NOx, SOx, NH3and primary PM2.5; however
there are strong spatial differences in the PM2.5sensitivi-
ties across the UK. Consequently, the sensitivity of PM2.5to
individual component emissions reductions varies between
area and population weighting. Reductions in NH3have the
greatest effect on area-weighted PM2.5. A full UK population
weighting places greater emphasis on reductions of primary
PM2.5emissions, which is simulated to be the most effective
single-component control on PM2.5for the 2030 scenario. An
important conclusion is that weighting corresponding to the
average exposure indicator metric (using data from the 45
model grids containing a monitor whose measurements are
used to calculate the UK AEI) further increases the empha-
sis on the effectiveness of primary PM2.5emissions reduc-
tions (and of NOxemissions reductions) relative to the effec-
tiveness of NH3emissions reductions. Reductions in primary
PM2.5have the largest impact on the AEI in both 2010 and
the 2030 CLE scenario. The summation of the modelled re-
ductions to the UK PM2.5AEI from 30% reductions in UK
emissions of primary PM2.5, NH3, SOx, NOxand VOC to-
tals 1.17 and 0.82µg m−3for the 2010 and 2030 CLE simu-
lations, respectively (not accounting for non-linearity).
1 Introduction
Atmospheric particulate matter (PM) has a range of ad-
verse impacts including on climate change through radiative
forcing (IPCC, 2013) and on human health (WHO, 2006,
2013). The global health burden from exposure to ground-
level ambient fine particulate matter (as characterized by the
PM2.5metric) is substantial. The Global Burden of Disease
project attributed 3.2 million premature deaths and 76 mil-
lion disability-adjusted life years to exposure to ambient
PM2.5concentrations prevailing in 2005 (Lim et al., 2012).
Published by Copernicus Publications on behalf of the European Geosciences Union.

266 M. Vieno et al.: The sensitivities of emissions reductions for the mitigation of UK PM2.5
Exposure to ambient PM2.5remains a major health issue in
Europe. The European Environment Agency report that for
the period 2010–2012, 10–14% of the urban population in
the EU28 countries were exposed to ambient concentrations
of PM2.5exceeding the EU annual-average PM2.5reference
value of 25µg m−3, but 91–93 % were exposed to concentra-
tions exceeding the WHO annual-average PM2.5air quality
guideline of 10µg m−3(EEA, 2014).
European Commission (EC) legislation for PM2.5includes
an obligation on individual member states to reduce expo-
sure to PM2.5in areas of population by a prescribed percent-
age between 2010 and 2020. The exposure to PM2.5is quan-
tified through the average exposure indicator (AEI) which
is the average of the annual PM2.5measured across desig-
nated urban background and suburban sites spread over cities
and large towns (averaged over the 3-year periods spanning
2010 and 2020). The AEI is therefore a quasi-indicator of
population-weighted PM2.5. For the UK, the calculation of
the AEI uses data from 45 sites (Brookes et al., 2012) and
the required reduction by 2020 is 15% from its 2010 value
of 13µg m−3(Defra, 2012).
While standards focus on PM2.5mass concentrations,
meeting these standards is complicated by the considerable
chemical heterogeneity, which arises because ambient PM2.5
comprises both primary PM emissions and secondary in-
organic and organic components formed within the atmo-
sphere from gaseous precursor emissions, specifically NH3,
NOx(NO and NO2), SO2, and a wide range of non-methane
volatile organic compounds (VOC) (USEPA, 2009; AQEG,
2015). Meteorological conditions also control PM2.5con-
centrations through their influences on dispersion, chemistry,
and deposition.
European legislation sets current and future caps on an-
thropogenic emissions of primary and secondary-precursor
components of PM2.5at national level and from individual
sources (Heal et al., 2012). Although it is well-known that
much of the ambient PM2.5in the UK derives from trans-
boundary emissions and transport into the UK (Vieno et al.,
2014; AQEG, 2015), a pertinent policy question to address is
what additional surface PM2.5reductions could the UK uni-
laterally achieve, at least in principle? In other words, what
are the sensitivities of UK PM2.5to UK reductions in emis-
sions of relevant components?
This is the motivation for the work presented here, which
investigates the impact of reductions from UK anthropogenic
sources of emissions of primary PM2.5and of precursors of
secondary PM2.5on surface PM2.5concentrations across the
whole UK. To adequately simulate the UK national domain
requires the use of a regional atmospheric chemistry trans-
port model (ACTM), in this study the EMEP4UK Eulerian
ACTM (Vieno et al., 2009, 2010, 2014). Recognizing that
reductions in UK and rest-of-Europe emissions are already
projected under current legislation, this work compares the
present-day sensitivity of UK emissions reductions on UK
PM2.5with a future time point (2030) to examine the effec-
tiveness of potential options in the future. It is recognized
that climate change may also have some influence on future
PM2.5concentrations in the UK; however the focus is here
on UK precursor emission sensitivity and many studies have
concluded that on the 2030 timescale air pollutant concen-
trations will be much more strongly influenced by changes in
precursor emissions than by changes in climate (e.g. Langner
et al., 2012; Coleman et al., 2013; Colette et al., 2013).
Throughout, the focus is on annual average PM2.5, since
this is the metric within the AEI, which in turn is driven by
the evidence from epidemiological studies that demonstrate
associations between adverse health outcomes and long-term
(annual average) concentrations of PM2.5(COMEAP, 2010;
WHO, 2013). It is also recognized that, whilst the focus here
is on reduction in concentrations of PM2.5from the perspec-
tive of its impact on human health, the reduction of anthro-
pogenic emissions in general will also have other benefits
including on human health, on N and S deposition, and on
ozone formation.
2 Methods
2.1 Model description and set-up
The EMEP4UK model used here is a regional ACTM based
on version rv4.4 (www.emep.int) of the EMEP MSC-W
model which is described in Simpson et al. (2012). A de-
tailed description of the EMEP4UK model is given in Vieno
et al. (2010, 2014).
The EMEP4UK model meteorological driver is the
Weather Research and Forecast (WRF) model version 3.1.1
(www.wrf-model.org). The EMEP4UK and WRF model hor-
izontal resolution is 50km ×50 km for the extended Euro-
pean domain and 5km ×5 km for the inner domain as il-
lustrated in Fig. 1. The EMEP4UK model uses a nested
approach, the European domain concentrations are used as
boundary condition for the UK domain. The boundary condi-
tions at the edge of the European domain are prescribed con-
centrations in terms of latitude and adjusted for each year.
For ozone, 3-D fields for the whole domain are specified
from climatological ozone-sonde data sets, modified monthly
against clean-air surface observations as described in Simp-
son et al. (2012).
The default EMEP MSC-W chemical scheme was used for
the present study, as it has been extensively validated at the
European scale (Simpson et al., 2012, www.emep.int). The
scheme has 72 species and 137 reactions, and full details are
given in Simpson et al. (2012). The gas/aerosol partitioning
is the model for aerosols reacting system (MARS) formula-
tion (Simpson et al., 2012). In the model version used here,
PM2.5is the sum of the fine (PM2.5)fraction of ammonium
(NH+
4), sulphate (SO2−
4), nitrate (NO−
3), elemental carbon
(EC), organic matter (OM), sea salt (SS), mineral dust, and
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M. Vieno et al.: The sensitivities of emissions reductions for the mitigation of UK PM2.5267
Figure 1. 2010 EMEP4UK annual-average surface concentrations
of PM2.5(µgm−3)at 50km ×50 km horizontal resolution for the
European model domain, and at 5km×5 km horizontal resolution
for the nested Great Britain and Ireland domain (black box).
27 % of the coarse nitrate. PM10 is the sum of PM2.5plus the
coarse (PM2.5−10)fraction of EC, OM, NO−
3, SS, and dust.
Whilst fine nitrate production is modelled using a ther-
modynamic model (MARS), the formation of coarse nitrate
from nitric acid (HNO3)uses a parameterized approach that
seeks to capture the HNO3reaction with sea salt and crustal
material. The conversion rate of HNO3to coarse nitrate
depends on relative humidity, as described by Simpson et
al. (2012), but is not explicitly linked to the surface area of
the existing coarse aerosol. Both nitrate generation mecha-
nisms compete for the same HNO3, and whilst this constrains
the total amount of nitrate produced, it is acknowledged that
the resulting split into fine and coarse nitrate is somewhat
uncertain as discussed in Aas et al. (2012). A more explicit
aerosol scheme is under development for the model.
Anthropogenic emissions of NOx, NH3, SO2, primary
PM2.5, primary PMcoarse, CO, and non-methane VOC for the
UK are derived from the National Atmospheric Emission In-
ventory (NAEI, http://naei.defra.gov.uk) at 1km×1 km res-
olution and aggregated to 5km×5 km resolution. For the
European domain, the model uses the EMEP 50 km ×50km
resolution emission estimates provided by the Centre for
Emission Inventories and Projections (CEIP, http://www.
ceip.at/). Shipping emissions estimates, for the inner domain,
are derived from the ENTEC (now Amec Foster Wheeler)
emissions estimate (ENTEC, 2010). Natural emissions of
isoprene and DMS are as described in Simpson et al. (2012).
The EMEP MSC-W model from which the EMEP4UK
model is derived is used widely in support of European
air quality science and policy development and the perfor-
mances of both have been extensively evaluated (Carslaw,
2011b; Schulz et al., 2013; Simpson et al., 2014; Schaap et
al., 2015).
2.2 Model experiments
A base run and a set of 5 sensitivity experiments were car-
ried out for emissions and meteorology for 2010. The exper-
iments applied 30% reductions to UK anthropogenic emis-
sions from all sectors for each of the following pollutants
individually: primary PM2.5, NH3, NOx, SOxand NMVOC.
This 30% perturbation was applied to land-based emissions
only; shipping emissions (both domestic and international)
were left unchanged.
Model runs were repeated for a 2030 future emissions sce-
nario to investigate sensitivities of UK PM2.5to UK emis-
sions reductions further along the pathway of current legis-
lation (CLE) emissions. The 2030 CLE emissions used in
the model runs were based on the 2030 IIASA CLE pro-
jection (IIASA, 2012) for Europe and the Updated Energy
Projections (UEP, version 45) for the UK. The UEPs are de-
veloped and regularly updated by analysing and projecting
future energy use and are based on assumptions of future
economic growth, fossil fuel prices, UK population develop-
ment, and other key variables. A set of projections is based on
a range of assumptions to represent the uncertainty in mak-
ing such projections into the future. For this manuscript, the
mid-range estimates were used. For a full description of the
UEPs and the methodology for their compilation, see DECC
(2015). Emissions from shipping were 2020 emissions esti-
mate provided by ENTEC (now Amec Foster Wheeler) (EN-
TEC, 2010).
No change in the spatial distribution of emissions was
made. Whilst there will likely be some changes in the spatial
distribution of emissions, such changes are not easily pre-
dicted for a future scenario, and may be anticipated to be
smaller than the changes in absolute amounts of emissions.
The boundary and initial conditions for ozone and particles
outside the European domain were left unchanged to the year
2010, as was the meteorology. The use of the same meteo-
rology isolates the sensitivity of surface PM2.5to emissions
reductions at some future date from the effects on surface
PM2.5due to differences in meteorology.
As well as maps of annual-average surface PM2.5concen-
trations the following three summary statistics for UK PM2.5
were calculated: (i) the area-weighted average, i.e. the av-
erage of all 5km ×5 km model grids over the UK; (ii) the
population-weighted average, i.e. the 5km×5 km gridded
estimates of PM2.5surface concentrations re-projected onto
the British National Grid and multiplied by population es-
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268 M. Vieno et al.: The sensitivities of emissions reductions for the mitigation of UK PM2.5
Figure 2. Gridded UK population density based on the UK cen-
sus at the 5km×5 km grid spatial resolution. Units are popula-
tionkm−2.
timates at the same spatial resolution (derived from the UK
census, http://census.edina.ac.uk/) (Fig. 2) and divided by the
sum of the UK population; (iii) a value analogous to the av-
erage exposure indicator (AEI), calculated as the average of
the concentrations for the 45 model grids containing a PM2.5
monitor whose measurements are used to define the UK’s
2010 AEI value (Brookes et al., 2012).
3 Results
Example comparisons between EMEP4UK-modelled sur-
face concentrations of PM2.5components and total measured
PM2.5are shown in Fig. 3 for three UK national network
monitoring sites: Edinburgh St. Leonards, an urban back-
ground site in the north of the UK; London North Kens-
ington, an urban background site in central London in the
south-east of the UK; and Harwell, a rural background site in
central England. Monthly averages of the hourly measured
and modelled data are presented. Model simulations follow
Figure 3. 2010 monthly-averaged EMEP4UK simulated PM2.5
components and total PM2.5observations by TEOM-FDMS at the
Edinburgh St. Leonards, London North Kensington and Harwell
UK national network (AURN) monitoring sites. Both the modelled
and observed data are averaged from hourly values. The linear re-
gression between the monthly averaged observation and model is
also shown at the top of each panel, along with the correlation coef-
ficient, r, bias and mean square error.
the observational time trends well. The model simulations of
the SIA components SO2−
4, NO−
3, and NH+
4have previously
been individually evaluated by Vieno et al. (2014) against
10years of speciated observations made at ∼30 sites across
the UK in the AGANET network (Conolly et al., 2011). The
four UK sites included in Vieno et al. (2014) showed good
agreement between the monthly averaged EMEP4UK simu-
lation and the observed NO−
3and SO2−
4, with a bias range
of 0.28 to −0.62 and 0.8 to −0.27µg m−3, respectively. The
EMEP4UK model was also evaluated against observations
and other models in a UK model inter-comparison organized
by the UK Department for Environment, Food & Rural Af-
fairs (Defra) (Carslaw, 2011a, b). The persistent negative bias
in the sum of the modelled PM2.5against observation in
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M. Vieno et al.: The sensitivities of emissions reductions for the mitigation of UK PM2.5269
Figure 4. Model simulations of the impact of 30% UK emissions
reductions on annual-average surface concentration of PM2.5. Panel
(a) 2010 base-case scenario, no emissions reduction (bottom colour
scale); remaining panels, the change in annual-average PM2.5for
30% UK emissions reductions in (b) NH3,(c) NOx,(d) SOx,
(e) VOC, and (f) primary PM2.5(right colour scale). All units
areµgm−3.
Fig. 3 is consistent with the absence of re-suspended dust
in the model configuration used here, and possibly also re-
flects a difference in the treatment of particle-bound water in
model and measurement. The omission of re-suspended dust
does not impact on the investigations here of the sensitivities
of PM2.5concentrations to anthropogenic emissions reduc-
tions; however it is acknowledged that since particle-bound
water is related to the mass of secondary inorganic compo-
nents its omission will have some impact on the sensitivity of
PM2.5to inorganic precursor gas emissions reductions. Dif-
ferent measurement techniques and conditions incorporate
different proportions of the ambient PM2.5water content. We
focus here on changes to the dry mass concentrations of sur-
face PM2.5derived from changes in the emissions of primary
PM2.5and secondary PM2.5precursor gases. (It is also noted
that values of relative reductions in modelled PM2.5will be
slightly higher than if expressed relative to measured PM2.5
at that location). Some model underestimation may also de-
rive from dilution of primary PM2.5emissions into the 5km
grid of the model compared with the primary emissions more
local to an urban background monitor.
The simulated “baseline” 2010 annual-average surface
concentrations for PM2.5at 50km horizontal resolution
for the EMEP4UK European domain and for the nested
5km horizontal resolution Great Britain and Ireland do-
main are shown in Fig. 1. The UK 2010 annual-average sur-
face concentrations of PM2.5are generally lower compared
with neighbouring continental countries such as France, the
Figure 5. The impact of 30% UK terrestrial emissions reductions
in primary PM2.5, NH3, SOx, NOx, and VOC (individually) on
three measures of UK-average surface concentrations of PM2.5:
area weighted; population weighted; and the average for the 45
model grids containing the monitors used to calculate the UK PM2.5
average exposure indicator (AEI). Data are shown for simulations
for 2010, and for 2030 under a CLE emission scenario (using 2010
meteorology).
Netherlands, and Germany. The influence of emissions orig-
inating from continental Europe is revealed by the gradi-
ent of decreasing PM2.5concentrations away from the con-
tinent. An analysis presented in AQEG (2015) also using
the EMEP4UK model showed that UK emissions contribute
around 55% of the total PM2.5in the UK. This limits the
extent to which long-term average concentrations can be re-
duced by UK action alone.
Figure 4 shows maps of the impacts on 2010 surface PM2.5
for 30% reductions in UK terrestrial emissions of each of
NH3, NOx, SOx, VOC, and primary PM2.5. The effect of
these emissions reductions on the three measures of UK-
average surface concentrations of PM2.5are illustrated in
Fig. 5, based on the data given in Table 1. The principal
observations from the two figures are that PM2.5levels in
the UK do not show strong responses to UK-only reductions
in emissions of individual components and/or precursors of
PM2.5, and that the responses are highly geographically vari-
able. The maximum reduction in PM2.5concentrations (at
a 5km grid resolution) reaches ∼0.6 µg m−3(∼6% of the
modelled components) in response to a 30% reduction in
UK emissions of individual components, and in most loca-
tions the reductions in PM2.5concentrations are considerably
smaller. This again indicates the influence on PM2.5in the
UK (on an annual average basis) from emissions outside of
the UK. In the case of the formation of SIA components,
it also reflects the non-linearity in the precursor oxidation
chemistry and gas-particle phase partitioning that occurs be-
tween emission location and receptor location (Harrison et
al., 2013; Vieno et al., 2014).
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270 M. Vieno et al.: The sensitivities of emissions reductions for the mitigation of UK PM2.5
Table 1. EMEP4UK-modelled estimates of the impact of 30 % UK terrestrial emissions reductions on three measures of UK-average surface
concentrations of PM2.5(µgm−3): (i) the average of the model grids containing the 45 monitors used to calculate the UK PM2.5average
exposure indicator (AEI), (ii) the population-weighted average, and (iii) the area-weighted (i.e. geographical) average, for 2010, and for 2030
under a CLE emission scenario (using 2010 meteorology). For context, the modelled reductions in the baselines between 2010 and 2030 CLE
for the three measures of UK-average PM2.5are 2.42, 2.24, and 1.70µgm−3, respectively.
Emissions reduced AEI Population-weighted Area-weighted
2010 2030 CLE 2010 2030 CLE 2010 2030 CLE
Primary PM2.50.37 0.29 0.31 0.24 0.16 0.13
NH30.35 0.19 0.34 0.19 0.28 0.16
SOx0.27 0.15 0.26 0.15 0.19 0.11
NOx0.10 0.14 0.10 0.15 0.11 0.13
VOC 0.08 0.05 0.08 0.05 0.07 0.03
Total 1.17 0.82 1.10 0.77 0.82 0.57
Figures 4 and 5 show that, on average across the UK, the
sensitivity of PM2.5concentrations to a 30 % reduction in UK
emissions of individual contributing components increases in
the order VOC, NOx, SOx, primary PM2.5, and NH3. The ex-
act order varies slightly with the UK-average measure used
(Fig. 5). This is due to differences in the spatial patterns of
the PM2.5reductions shown in Fig. 4 in relation to the distri-
bution of UK population shown in Fig. 2.
The 30% reductions in UK VOC emissions gives maxi-
mum reductions of ∼0.15µg m−3(1.5 %) in PM2.5concen-
trations in central and northern England and central Scotland
(Fig. 4e). The 30% reductions in UK NOxemissions yield
around 0.2µg m−3(3 %) reductions in PM2.5over some ru-
ral areas (Fig. 4c), and generally a maximum of 0.15µg m−3
(1.5%) reductions in PM2.5over other rural areas. An im-
portant observation is that reductions of PM2.5over urban
centres are smaller (no more than 0.15µg m−3)than in rural
areas for these reductions in NOxemissions. The 30 % reduc-
tions in UK SOxemissions yield up to ∼0.45–0.5µg m−3
(5%) reductions in PM2.5in the Trent valley and up to
around 0.3–0.35 µgm−3(3 %) reductions in PM2.5over large
areas of central and northern England and central Scotland
(Fig. 4d). The locations with greatest sensitivities to the 30 %
NOxemissions reductions (Fig. 4c) are generally those with
the lowest sensitivities to SOxemissions reductions (Fig. 4d).
As with the NOxemissions reductions, the reductions in
PM2.5concentrations for reductions in SOxemissions is not,
in general, associated with the major urban areas, except
where these also have major SOxsources in the vicinity (e.g.
Trent Valley, West Midlands, Cheshire). This is primarily
caused by the spatial distribution of major sources of SOx
emissions. As ∼80% of UK SOx2010 emissions originate
from large point sources (power plants, industrial facilities),
which are not located in the heart of urban areas, associated
emission reductions have the most profound effects in ru-
ral areas. However, the greater sensitivity to SOxclose to
large point sources (e.g. coal-fired power plants) may in part
be an artefact due to the model assumption that 5% of SOx
emissions are directly in the form of SO2−
4, which may no
longer be appropriate for these sources or for models run-
ning at relatively high horizontal spatial resolution. The SOx
and NOxgases compete in their reaction with NH3to form
particulate ammonium sulphate ((NH4)2SO4)or ammonium
nitrate (NH4NO3). The larger sensitivity of PM2.5formation
to NH3emissions reductions indicates that NH3is the limit-
ing species; whilst the greater sensitivity to SOxthan to NOx
emissions reductions reflects that the reaction between NH3
and SOxis fast and essentially irreversible compared with
the equilibrium reactions between gaseous NH3and NOx
species and NH4NO3.
The largest reductions in PM2.5(when weighted towards
areas of greatest population) derive from 30% reductions in
UK NH3and primary PM2.5emissions (Fig. 4b and f), up
to 0.45µg m−3for NH3reductions and greater for primary
PM2.5reductions (up to ∼6% of modelled PM2.5in both
cases). There is a distinct inverse geographic relationship in
the PM2.5sensitivity to reductions of these two components.
The reductions in NH3emissions give greatest PM2.5de-
creases in agricultural areas, whereas the reductions in pri-
mary PM2.5give greatest decreases in the large conurba-
tions and other areas of high population density. The dif-
ference in geographical patterns is highlighted more clearly
in Fig. 6a which shows the data in Fig. 4b minus the data
in Fig. 4f. Blue colours in Fig. 6a indicate where reduc-
tions in PM2.5from a 30% reduction in NH3emissions ex-
ceed the reductions in PM2.5from a 30% reduction in pri-
mary PM2.5emissions, and vice-versa for red colours. White
colours indicate comparable reductions in PM2.5via primary
PM2.5or NH3emissions reductions. The geographical pat-
tern in PM2.5sensitivity reflects the geographical pattern of
the emission sources and the fact that, because of the short at-
mospheric lifetime of NH3, UK emissions of NH3also gen-
erally have short-range influence.
Figure 7 shows the map of annual-average surface con-
centration of PM2.5estimated for the 2030 CLE emissions
projections, and of the difference between the PM2.5concen-
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M. Vieno et al.: The sensitivities of emissions reductions for the mitigation of UK PM2.5271
Figure 6. The difference between changes in simulated annual-
average PM2.5(µgm−3)for 30 % reductions in UK NH3emissions
reduction and for 30% reductions in UK primary PM2.5emissions
reduction: (a) for the year 2010 (i.e. the data in Fig. 4b minus the
data in Fig. 4f); and (b) for the year 2030 (i.e. the data in Figure 8b
minus the data in Fig. 8f). Blue colours indicate where reductions in
PM2.5for 30% reduction in NH3emissions exceed the reductions
in PM2.5for 30% reduction in primary PM2.5emissions, and vice
versa for the red colours. The same meteorological year 2010 was
used.
trations in 2030 and 2010. Surface concentrations of PM2.5
over the UK are simulated to reduce by up to 2.8µgm−3
between 2010 and the 2030 CLE emissions scenario used.
The UK-wide reductions in PM2.5between 2010 and 2030
CLE are 1.70, 2.24, and 2.42µg m−3for the area-weighted,
population-weighted and AEI summary measures, respec-
tively. The impacts on surface PM2.5in 2030 of additional
30% reductions applied to UK-only terrestrial emissions of
each of NH3, NOx, SOx, VOC, and primary PM2.5individu-
ally are shown in Fig. 8. Figure 5 illustrates the quantitative
effect of these further emissions reductions against the 2030
CLE scenario on the three summary measures of UK-average
surface concentrations of PM2.5.
The maps in Fig. 8 show qualitatively very similar find-
ings to their equivalent maps in Fig. 4. In 2030, UK PM2.5
is projected to remain more sensitive to reductions in UK
emissions of NH3and primary PM2.5than to reductions in
UK SOxand NOx; and, from a population-weighted perspec-
tive, to be relatively more sensitive to further primary PM2.5
and NH3emissions reductions, particularly to primary PM2.5
emissions reductions, than was the case for the 2010 sim-
ulations (Fig. 5). For the 2030 simulations, additional 30%
reductions in UK primary PM2.5or NH3emissions yield re-
ductions in PM2.5of up to 0.5 or 0.25µg m−3, respectively
(Fig. 8), whilst in 2010 additional 30 % reductions in primary
PM2.5or NH3emissions yield reductions in PM2.5of up to
0.6 or 0.45µg m−3, respectively (Fig. 4). The 2030 results
again emphasize a geographic pattern of greatest sensitivity
Figure 7. EMEP4UK annual-average surface concentration of
PM2.5(µgm−3)for (a) 2010 emissions, and (b) 2030 CLE emis-
sions projection (bottom colour scale), and (c) the difference 2030
CLE – 2010 CLE (right colour scale). The same meteorological year
2010 was used.
of PM2.5to reductions in the areas of high population density.
Figure 6b plots the difference in response to the NH3and pri-
mary PM2.5emissions reductions in 2030, analogous to the
plot in Fig. 6a for the 2010 sensitivities. Figure 6b clearly
emphasizes that for this projection for 2030, UK PM2.5is
relatively even more sensitive to further reductions in UK
primary PM2.5emissions compared with further reductions
in UK NH3emissions, particularly in populated areas, than
is the case for 2010; albeit that the additional absolute reduc-
tions in PM2.5for a given percentage of emissions reductions
is smaller in 2030 than in 2010 (Fig. 5) because of the gen-
eral decline in emissions across Europe during this period for
this scenario.
4 Discussion
Simulations were undertaken for both 2010 and a 2030 sce-
nario to investigate whether conclusions on effectiveness of
potential UK mitigation differ between the two time points. It
is recognized that reductions in emissions of primary PM2.5
and precursor gases from many anthropogenic sources are al-
ready anticipated going forward under current legislation, so
it is important to know, for a future policy perspective, the
anticipated sensitivities of UK PM2.5to additional UK emis-
sion reductions in the future.
The simulations for both 2010 and 2030 CLE show that
if the focus is on the reduction of spatially averaged PM2.5
concentrations then the most effective UK control, via an in-
dividual component, is achieved through reduction of UK
emissions of NH3, as shown in Fig. 5. However, the con-
clusion is different when considering population-weighted
PM2.5reductions for the mitigation of human health effects.
For a full population weighting across all 5 km×5km model
grids, reductions in UK primary PM2.5emissions are al-
most as effective as reductions in UK NH3emissions for the
2010 simulations, but primary PM2.5emissions reductions
are simulated to be the most effective additional control in the
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272 M. Vieno et al.: The sensitivities of emissions reductions for the mitigation of UK PM2.5
Figure 8. Model simulations of impact of 30% UK emissions re-
ductions on annual-average surface concentration of PM2.5for a
future scenario (with 2010 meteorology). Panel (a), 2030 CLE sce-
nario, no emissions reduction (bottom colour scale); remaining pan-
els, the change in annual-average PM2.5for 30% UK emissions re-
ductions in (b) NH3,(c) NOx,(d) SOx,(e) VOC, and (f) primary
PM2.5(right colour scale). All units are µg m−3.
2030 CLE future (Fig. 5). Emphasis on population weight-
ing also increases the sensitivities of PM2.5to reductions in
NOxemissions in both 2010 and 2030 CLE because a major
source of NOxis road traffic whose emissions are associated
with where the population live. On the other hand, the sen-
sitivity of PM2.5to further reductions in UK SOxemissions
is markedly lower in 2030 than in 2010 because of the large
reductions in SOxemissions already implemented under the
CLE scenario. It is also recognized that reductions in NOx
and VOC emissions have the potential to deliver health ben-
efits separately from their contribution to reduction in PM2.5
through reductions in population exposure to surface NO2
and O3.
An important observation is that the effectiveness of emis-
sions reductions on PM2.5using a population weighting for
the quantification differs between evaluation via full nation-
wide gridded population-weighting or via use of data only at
the locations used to derive the AEI. Quantification through
the AEI puts greater emphasis on the effectiveness of pri-
mary PM2.5emissions reduction, and on NOxemissions re-
ductions, (Fig. 5) because the monitor locations contributing
to the AEI are sited in the largest cities and towns where
emissions of primary PM2.5and NOxare prevalent. Based
on the AEI, control of primary PM2.5is the most effective
individual component in 2010 as well as in 2030 CLE. These
observations are pertinent given that the AEI is the air quality
metric for PM2.5.
Analyses from the EUCAARI study in Kulmala et
al. (2011) and a more recent European study in Megaritis
et al. (2013) both suggest that reducing NH3emissions is the
most effective way to reduce PM2.5under present-day con-
ditions. Whilst the current study also emphasizes the sensi-
tivity of PM2.5to NH3emissions reductions, it also empha-
sizes that, for the UK, a sensitivity to primary PM2.5emis-
sions reductions is at least as great as for NH3when consider-
ing population-weighting of PM2.5concentrations, both cur-
rently and for a future CLE scenario. In fact the sensitivity to
primary PM2.5emissions may be underestimated by the sim-
ulations because of dilution of primary PM2.5emissions into
the 5 km×5km grid resolution of the model. It has been cal-
culated that a 1 :1 relationship between UK primary PM2.5
emissions reductions and the reduction in the primary PM2.5
component of the UK 2010 AEI would lead to a reduction in
the 2010 AEI of 0.8µg m−3(AQEG, 2015), compared with
the 0.37µg m−3derived from the model simulations in this
work (Table 1). Even so, the total impact of 30% reductions
in UK emissions of all the components and/or precursors
listed in Table 1 on the 2010 baseline, is only of comparable
magnitude (1.2µg m−3)to the 15 % (or 1.3µg m−3)reduc-
tion required in the UK AEI by 2020. However, reductions
in these emissions from outside the UK will also contribute
to reducing the UK PM2.5AEI. Conversely, reductions of
emissions in the UK will also yield benefits for surface PM2.5
concentrations elsewhere in Europe. The country-to-country
source-receptor matrices developed by EMEP MSC-W at the
50km resolution indicate that reductions in the UK of the
same primary and precursor species considered in this work
would (for 2011 emissions) lead to reductions in PM2.5in
neighbouring countries up to about one-third the magnitude
of the PM2.5reductions in the UK (Fagerli et al., 2014). Re-
ductions of emissions in the UK would also lead to other ben-
efits outside the UK on, for example, NO2and O3exposure
and on N and S deposition.
Although the model used in this study is widely applied
across Europe for air quality policy development (Fagerli et
al., 2014), the data presented here are from simulations from
a single model. The model simulations of the effect of inor-
ganic precursor gases on the secondary inorganic PM2.5are
dependent on accurate representation of the relevant chem-
istry and phase partitioning. It is possible that the SIA rep-
resentation in the EMEP4UK model may underestimate the
nitrate in the PM2.5size fraction, and hence downplay some-
what the sensitivity of PM2.5to NOxemissions reductions.
In addition, not explicitly calculating the uptake of HNO3by
mineral dust may reduce the NO−
3changes due to NOxemis-
sions reduction. However, the EMEP4UK particle sulphate,
nitrate and ammonium concentrations all compare well with
the multi-year time series of measurements of these compo-
nents at ∼30 sites across the UK in the Acid Gas and Aerosol
Network (AGANet) and National Ammonia Monitoring Net-
work (NAMN) (Vieno et al., 2014). Variation in particle-
bound water may also impact on the exact PM2.5mass sen-
Atmos. Chem. Phys., 16, 265–276, 2016 www.atmos-chem-phys.net/16/265/2016/

M. Vieno et al.: The sensitivities of emissions reductions for the mitigation of UK PM2.5273
sitivities associated with inorganic precursor gas emissions
reductions.
Inter-annual variability in meteorology may also have an
influence, in particular in determining the balance in any
year between PM2.5in the UK derived from UK emissions
and that derived from emissions outside the UK (Vieno et
al., 2014). However, whilst the precise quantitative sensitivi-
ties of annual average PM2.5to emissions reductions will be
subject to inter-annual meteorological variability, it is antici-
pated that the broad findings of this study will hold.
The interpretation of the modelling results has been under-
taken from the perspective that reduction in all anthropogeni-
cally derived components of PM2.5is equally important. This
remains the current position for the EU legislation that sets
limits and targets for concentrations of PM2.5(Heal et al.,
2012); i.e. no consideration is given to the potential different
toxicity to human health of different components of PM2.5.
The UK Committee on the Medical Effects of Air Pollutants
has also recently concluded that reductions in concentrations
of both primary and secondary particles are likely to ben-
efit public health (COMEAP, 2015). Nevertheless, although
not conclusive, there is evidence that traffic-related sources
of PM, or combustion sources more generally, are particu-
larly associated with adverse health outcomes (Grahame and
Schlesinger, 2007, 2010; Janssen et al., 2011; Stanek et al.,
2011; WHO, 2013; Grahame et al., 2014). The possibility
that primary PM2.5is more toxic per unit mass than sec-
ondary PM2.5, places greater emphasis on the finding from
this work on the effectiveness of reductions in emissions of
primary PM2.5. Interpretation of the modelling results has
also not considered the relative costs or feasibilities of imple-
menting further reductions in the emissions of the individual
precursors and components investigated.
Finally, it should be remembered that measures taken in
the UK to reduce concentrations of ambient PM2.5and of
precursor gases, both within and outside of populated areas,
will have multiple co-benefits on human health, N and S de-
position, ozone formation and radiative forcing, not just in
the UK but elsewhere.
5 Conclusions
The sensitivity of annual-average surface concentrations of
PM2.5across the UK to reductions in UK terrestrial anthro-
pogenic emissions in primary PM2.5, NH3, NOx, SOx, and
non-methane VOC was investigated using the EMEP4UK
atmospheric chemistry transport model for 2010 and for
a 2030 current legislation scenario that includes projected
pan-European emission changes. In general, the sensitivity
of modelled concentrations to UK-only mitigation is rather
small. A 30% reduction in UK emissions of any one of the
above listed PM components yields (for the 2010 simula-
tion) a maximum reduction in PM2.5concentrations in any
given location of ∼0.6µgm−3(equivalent to ∼6% of the
total modelled PM2.5mass concentration). On average across
the UK, the sensitivity of PM2.5concentrations to a 30% re-
duction in UK emissions of individual contributing compo-
nents, for both the 2010 and 2030 CLE baselines, increases
in the order NMVOC, NOx, SOx, NH3, and primary PM2.5,
but there are strong spatial differences in the PM2.5sensitivi-
ties across the UK. Consequently, the sensitivity of PM2.5to
individual component emissions reductions varies between
area and population weighting. Reductions in NH3have the
greatest area-weighted effect on PM2.5. A full UK population
weighting places greater emphasis on reductions of primary
PM2.5emissions, which is simulated to be the most effective
single-component control on PM2.5for the 2030 scenario. An
important observation is that weighting corresponding to the
average exposure indicator metric (using data from the 45
model grids containing a monitor whose measurements are
used to calculate the UK AEI) further increases the empha-
sis on the effectiveness of primary PM2.5emissions reduc-
tions (and of NOxemissions reductions) relative to the effec-
tiveness of NH3emissions reductions. Reductions in primary
PM2.5has the largest impact on the AEI in 2010 as well as
the 2030 CLE scenario. The summation of the reductions to
the UK PM2.5AEI of the 30 % reductions in UK emissions of
primary PM2.5and of NH3, SOx, NOxand VOC totals ∼1.2
and ∼0.8µg m−3with respect to the 2010 and 2030 CLE
baselines, respectively (not accounting for non-linearity).
Acknowledgements. This work is funded jointly by the UK
Department for the Environment, Food and Rural Affairs (Defra),
the NERC Centre for Ecology and Hydrology (CEH), the EMEP
programme under the United Nations Economic Commission for
Europe Convention on Long-range Transboundary Air Pollution,
the Norwegian Meteorological Institute (Met.No) and the European
Union projects; NitroEurope IP and ÉCLAIRE.
Edited by: J. G. Murphy
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