ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-17-12813-2017Impact of agricultural emission reductions on fine-particulate matter and public healthPozzerAndreaandrea.pozzer@mpic.dehttps://orcid.org/0000-0003-2440-6104TsimpidiAlexandra P.KarydisVlassis A.de MeijAlexanderhttps://orcid.org/0000-0003-3799-7951LelieveldJoshttps://orcid.org/0000-0001-6307-3846Atmospheric Chemistry Department, Max Planck Institute for Chemistry, Mainz, GermanyNoveltis, Sustainable Development, Rue du Lac, 31670 Labege, FranceEnergy, Environment and Water Research Center, The Cyprus Institute, Nicosia, Cyprusnow at: MetClim, Varese, ItalyAndrea Pozzer (andrea.pozzer@mpic.de)27October20171720128131282627April201711May201729August201726September2017This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/17/12813/2017/acp-17-12813-2017.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/17/12813/2017/acp-17-12813-2017.pdf
A global chemistry-climate model has been used to study
the impacts of pollutants released by agriculture on
fine-particulate matter (PM2.5), with a focus on
Europe, North America, East and South Asia.
Simulations reveal that a relatively strong reduction in PM2.5 levels
can be achieved by decreasing agricultural emissions,
notably of ammonia (NH3) released from fertilizer use and animal husbandry.
The absolute impact on PM2.5 reduction is strongest in East Asia,
even for small emission decreases. Conversely, over Europe and North America, aerosol formation
is not immediately limited by the availability of ammonia.
Nevertheless, reduction of NH3 can also substantially
decrease PM2.5 concentrations over the latter regions,
especially when emissions are abated systematically.
Our results document how reduction of agricultural emissions
decreases aerosol pH due to the depletion
of aerosol ammonium, which affects particle liquid phase
and heterogeneous chemistry.
Further, it is shown that a 50 % reduction of agricultural emissions
could prevent the mortality attributable to air pollution by
∼250000 people yr-1 worldwide, amounting
to reductions of 30, 19, 8 and 3 % over North America, Europe, East and South Asia, respectively.
A theoretical 100 % reduction could even reduce the number of deaths
globally by about 800 000 per year.
Introduction
Atmospheric aerosol particles are a major constituent
of ambient air and have a large impact
on atmospheric chemistry, clouds, radiative transfer and climate and also induce adverse human
health effects that contribute to mortality
. Particulate matter (PM) with
an aerodynamic diameter smaller
than 2.5 µm (PM2.5) contributes to air pollution
through intricate interactions between emissions of primary particles
and gaseous precursors, photochemical transformation pathways and
meteorological processes that control transport and deposition.
As shown by and , agricultural
emissions play a leading role in the formation of PM2.5 in various
regions of the world, for example in central and eastern Europe. Agricultural
emissions are mostly related to animal husbandry and fertilizer use and to a
lesser extent also to the burning of crop residues : around
10 % of worldwide biomass burning emissions can be ascribed to agricultural
activities . The general importance of agricultural
emissions for air quality was also previously identified by a number of
studies e.g., and
recognized through environmental policies, (e.g., the establishment of
ceilings for national emissions for ammonia by the European Union Clean Air
Program). The dominant trace gas emitted by agricultural
activities is ammonia (NH3). Around 80–90 % of the atmospheric
NH3 emissions in industrialized regions are from the agricultural
sector . NH3 is formed and released during the decomposition
of manure and organic matter, mostly from animal farming and the associated
manure storage and field application, with an additional contribution from
(synthetic) nitrogen fertilizer use. NH3 is a toxic gas at very high
concentrations, with a pungent smell that irritates the eyes and respiratory
system. NH3 is also a major alkaline gas in the atmosphere and plays
an important role in neutralizing acids in the aerosol and cloud liquid
phase, forming ammonium sulfate and ammonium nitrate (ammonium salts)
. Therefore NH3 contributes to secondary aerosol
formation and the overall particulate matter burden, and decreases the
acidity of the aerosols, which in turn increases the solubility of weak acids
(e.g., HCOOH, SO2). The aerosol pH plays an important role in
the reactive uptake and release of gases, which can affect ozone chemistry,
particle properties such as hygroscopic growth and scattering efficiency of
sunlight and deposition processes
.
showed that a 50 % reduction of
NH3 emissions would lead to a 4 and 9 % decrease in PM2.5
over the eastern USA in July and January, respectively.
The reduction of NH3 emissions was found to be
the most effective PM2.5 control measure for the winter period
over the eastern USA compared to similar reductions of
SO2, NOx and VOC
emissions .
and
found that over Europe the reduction of NH3 emissions is the
most effective control strategy used to mitigate PM2.5
in both summer and winter,
mainly due to a significant decrease of ammonium nitrate.
Further, ,
showed that reducing the NH3 emissions from agriculture by 50 %
could result in a decrease of PM2.5 concentrations
up to 2.4 µgm-3 over the Po Valley region (Italy).
This confirms the finding of , who showed that for
short-lived species like NOx and NH3,
short-term fluctuations of the emissions play an important
role in the formation of nitrate aerosol.
According to , NH3 emissions contribute
8–11 % to PM2.5 concentrations in eastern China, which is comparable
to the contributions of SO2 (9–11 %) and NOx (5–11 %) emissions.
However, the air quality benefits of controlling NH3 emissions
could be offset by the potential enhancement of aerosol acidity.
showed that, despite the large investments
in sulfur dioxide emission reductions,
the acid/base gas particle system in the southeastern USA
is buffered by the partitioning of semivolatile NH3,
making the pH insensitive to SO2 controls.
Several studies have been performed on the impact of NH3 on aerosol nitrate
and sulfate ,
mostly with a regional rather than a global view.
As PM2.5 has been clearly associated with many health impacts,
including acute lower respiratory infections (ALRI), cerebrovascular disease
(CEV), ischaemic heart disease (IHD), chronic obstructive pulmonary disease
(COPD) and lung cancer (LC) . Due to its strong
contribution to the PM2.5 mass, control strategies in NH3
emissions could possibly reduce the mortality attributable to air pollution,
and air quality policy in Europe does indeed include ceilings for NH3
emissions . Studies on PM2.5 reduction due to
NH3 control have been performed regionally both for Europe
and the USA , while a
detailed analysis on the global scale was performed by , who
showed the importance of ammonia as a contributor to mortality attributable
to air pollution. Nevertheless, assumed an ammonia reduction
of 10 %, and the health effects were linearized around the present-day
concentrations. As the exposure-response functions, linking PM2.5
to mortality attributable to air pollution, are highly nonlinear at
relatively low concentrations, the mortality reduction estimation could
change drastically for strong reductions of ammonia emissions. Therefore, in
this work, more aggressive reductions are studied (see
Sect. ).
Furthermore, there is a need to not only investigate the impact of NH3
emission reductions on PM2.5 concentrations, but also
account for particle acidity and aerosol composition. The goal of this work
is to understand the impact of global agricultural emissions on model-simulated PM2.5 concentrations, the effects on aerosol pH and the
potential consequences for human health, with a focus on four continental
regions where air quality limits and guidelines for PM2.5 are often
exceeded, i.e., North America, Europe, South and East Asia. North America is
defined as the region that encompasses the USA and Canada; Europe is
represented by the European continent (including Turkey) excluding Russia;
South Asia includes India; Sri Lanka, Pakistan, Bangladesh, Nepal and Buthan;
while the East Asia region includes China, North and South Korea and Japan
(see Fig. ).
Regions addressed in this study, i.e., North America (blue), Europe (green),
South Asia (purple) and East Asia (red).
This work may also support policy actions aimed at controlling ammonia
emissions, e.g., formulated in the European Union Clean Air Program
(http://www.consilium.europa.eu/en/policies/clean-air/), which sets ceilings for national emissions for sulfur dioxide,
nitrogen oxides, volatile organic compounds, fine-particulate matter and
ammonia.
Methodology
Scatter plot of observed and modeled yearly averaged
concentrations of PM2.5 (in µgm-3).
The colors denote the regions, i.e., blue is North America,
green is Europe, purple is South Asia and red is East Asia. Black are locations
outside these regions.
In this study the EMAC (ECHAM5/MESSy Atmospheric Chemistry) model version 1.9
was used. EMAC is a combination of the general circulation model ECHAM5
version 5.3.01 and the Modular Earth Submodel System
MESSy, version 1.9. Extensive evaluation of the model
can be found in , ,
and . ECHAM5 has been used at the
T106L31 resolution, corresponding to a horizontal resolution of ∼1.1×1.1∘ of the quadratic Gaussian grid and with 31 vertical
levels up to 10 hPa in the lower stratosphere. The model setup is the same
as that presented by and is briefly
summarized here. The anthropogenic emissions are for the year 2010 from the
EDGAR-CIRCE Emission Database for Global Atmospheric
Research database, distributed vertically to
account for different injection altitudes . Bulk natural
aerosol emissions (i.e., desert dust and sea spray), are treated using
offline monthly emissions files based on AEROCOM and
hence are independent of the meteorological conditions. The atmospheric
chemistry is simulated with the MECCA (Module Efficiently Calculating the
Chemistry of the Atmosphere) submodel by ,
and the aerosol microphysics and gas-aerosol partitioning are calculated by
the Global Modal-aerosol eXtension (GMXe) aerosol module
. Gas/aerosol partitioning is calculated
using the ISORROPIA-II model .
Following the approach of , the year 2010 is used as
the reference year, the feedback between chemistry and dynamics was
switched off, and therefore all simulations described here are based on the
same (binary identical) dynamics and consequent transport of tracers.
Although evaluated the model for the same configuration
and emissions database, the emissions referred to the year 2005, while
here the emissions for the year 2010 are used. Therefore the model is
re-evaluated for the species of interest (i.e., SO42-, NO3-,
NH4+ and PM2.5). The model results of this study have been
evaluated against satellite based PM2.5 estimates
; the results are shown in Fig.
and are summarized in Table , also focusing on the four
regions focus of this study (i.e., North America, Europe, South and East
Asia). Compared to global satellite-derived PM2.5 concentrations
this model version, with prescribed dust emissions, consistently
overestimates PM2.5 over desert areas (see
Fig. ). However, the average concentration of
PM2.5 at the surface in the regions of interest is within 30 % of
the observations. For Europe and South Asia, 95 % of the simulated
PM2.5 concentrations are within a factor of 2 of the observations,
while for North America and East Asia this is about 80 %.
(a) Observed annual mean PM2.5 from ,
(b) simulated annual mean PM2.5 (REF simulation),
both in µgm-3.
Summary of the comparison of model data to pseudo-observations of
PM2.5 concentrations . OAM and MAM are the
spatial arithmetic mean of the observations and of the model results (REF
simulation), respectively (in µgm-3), based on the annual
averages. The model results were masked in locations where no observations
are available. PF2 is the percentage of model results within a factor of 2
of the observations.
Further, SO42-, NO3- and NH4+ have been compared with station observations
from different databases, such as from EPA (United States Environmental
Protection Agency), EMEP (European Monitoring and Evaluation Programme) and
EANET (Acid Deposition Monitoring Network in East Asia) for the year 2010.
The results are shown in Fig. and summarized in
Table .
Summary of the comparison of model data to the observations of aerosol
component concentrations. OAM and MAM are the spatial arithmetic mean of the
observations and the model, respectively (in µgm-3). PF2 is
the percentage of model results within a factor of 2 in the observations.
While sulfate is well reproduced, with more than ∼85 % of the model
results within a factor of 2 compared to the observations, nitrate is
overestimated in North America and Europe by ∼50 %, although nitric
acid is reproduced accurately by the model (based on comparison with
observations from ; see ). As the
nitrate concentrations seem to be on the high end of the observations, it
must be acknowledged that the effect of reducing ammonia emissions from
agriculture could be overestimated. On the other hand, nitrate predictions
are in good agreement with the measurements over East Asia. Further,
ammonium concentrations are well captured by the model, with more than 75 %
of the modeled results being within a factor of 2 compared to the observations.
For ammonium, the annual averages estimated from model results compare well
with the observations (see Table ). Further, as shown by
, simulated seasonal cycle of ammonium concentrations
compares well with the observed one, both for Europe and Asia (with temporal
correlations between model results and observations above 0.7 and 0.5,
respectively). However, this is not the case on the east coast of the USA,
where the correlation is below 0.2. As suggested by ,
this is due to the wrong seasonality of the ammonia emissions, driven by an
underestimation of the livestock emissions, which have a maximum in summer and
should account for 80 % of the annual NH3 emissions in the region
. The agricultural emissions of ammonia in this region in
the model reproduce mostly the fertilizer application as described by
and therefore the real seasonality of the ammonia
emissions is missing . The seasonal results over the USA
should hence be taken with caution. Further evaluation can be found in
and .
In the current analysis four simulations with the EMAC model have been
performed to study the impacts on PM2.5 components: the evaluated
reference simulation (REF) and three sensitivity calculations in which the
agricultural emissions have been reduced by different percentages, 50 % in
simulation REF_50, 75 % in simulation REF_75 and 100 % (i.e.,
removing all agricultural emissions) in simulation REF_100.
Simulated mean concentrations of PM2.5 components (SO42-, NO3- and NH4+)
in µgm-3 at the surface for the year 2010, with observations from EPA, EMEP and EANET
(averaged over the same period) overlaid.
The NOx emissions from agriculture are 0.7 Tg(N)yr-1,
i.e., only ∼ 1.7 % of the total NOx emissions. Most
importantly, 34.3 Tg(N)yr-1 of NH3 are emitted by
agricultural activities, such as livestock manure and N mineral fertilizers,
accounting for ∼80 % of the anthropogenic and ∼67 % of the
total global ammonia emissions.
Agricultural waste burning is responsible for the emissions of
0.1 Tg(S)yr-1 of SO2 (less than 1 % of the total
SO2 emissions) and 23.2 Tg(C)yr-1 of CO
(∼ 5 % of the total CO emissions), as well as 0.4 and
1.9 Tg(C)yr-1 of black carbon (BC) and organic carbon
(OC), respectively, representing in both cases ∼ 5 % of their
total emissions.
Relative annual average surface PM2.5 concentration
changes (in %) from the three scenarios with agricultural emissions
reductions of 50, 75 and 100 % (a, b and c,
respectively).
Considering these emission magnitudes, the main effects of agricultural
emissions on PM2.5 are expected from NH3 through
gas-particle partitioning. Therefore, the ammonia emissions used in this work
have been compared to other used databases, such as EDGARv4.3.1
Emission Database for Global Atmospheric Research, and
RCP85 Representative Concentration
Pathways. These data sets differ globally
by ∼15 % (40.26, 47.49 and 40.62 Tgyr-1 for
EDGAR-CIRCE, EDGARv4.3.1 and RCP85). This reflects the
uncertainties in the emission estimates of ammonia, which could be up to
50 % on a local scale . The implementation of
bidirectional exchange of ammonia between the soil and atmosphere may improve the
emissions from livestock, although this approach is still associated with
underestimates of emissions . Further, ammonia emitted from
traffic is included (∼1 % of total ammonia emissions), although toward
the lower end of what has been estimated by .
As shown by , and , a
sustainable reduction of ammonia emissions between 20 to 90 % could be
achieved, depending on the emission process and the methodology applied
(e.g., slurry acidification, adjustment in slurry application, under-floor
drying of broiler manure in buildings, replacing urea with ammonium nitrate).
As the efficiencies of the abatement processes are not well established
, fixed relative reductions have been applied here to
all agricultural emissions. showed that for the United
Kingdom a moderate reduction in ammonia emission is easily affordable, while
the costs are likely to increase exponentially for reductions above 25 %.
The same control measures would be even more difficult to apply in
countries in which livestock production is projected to largely increase (such
as Asia; ), where they should be adopted
on a large scale.
Absolute annual average surface aerosol pH changes (all modes) from
three scenarios with agricultural emission reductions of 50, 75 and 100 %
(a, b and c, respectively).
Results and discussionImpact on PM2.5
In Figure the relative annual average surface PM2.5
concentration changes between simulations REF_50, REF_75, REF_100
and REF are presented. These simulations reflect the impact on
PM2.5 of policies imposing an overall decrease in the agricultural
emissions of 50, 75 and 100 %, respectively. In Table the
predicted PM2.5 concentrations and pH for all simulations are also
listed. The largest effects are found over Europe, North America and China;
the latter have a smaller relative intensity. A 50, 75 and 100 % reduction of
ammonia emissions would reduce the annual and geographical mean
PM2.5 levels over Europe by ∼ 1.0 µgm-3
(11 %), 1.8 µgm-3 (19 %) and 3.1 µgm-3
(34 %) compared to the reference annual surface
concentration of 8.9 µgm-3. The same relative emission
decreases in North America lead to PM2.5 concentration reductions
of 0.3 µgm-3 (8 %), 0.5 µgm-3 (12 %) and
0.69 µgm-3 (16 %), respectively, compared to a reference
annual surface concentration of 4.0 µgm-3. Over East Asia the
absolute decrease in the annual average PM2.5 concentration near
the surface is 1.6 µgm-3 (5 %), 2.7 µgm-3
(8 %) and 4.08 µgm-3 (13 %) for the three
scenarios. Although the absolute changes in East Asia (relative to a
reference value of 31.1 µgm-3), are larger than the
corresponding changes estimated over Europe and North America, the relative
changes are smaller. In fact, the fraction of fine-particle mass that is
directly ammonia sensitive (i.e., (NH4++NO3-) /PM2.5) is relatively smaller in East Asia
(∼ 13 %) than in Europe (∼ 27 %) and North America
(∼ 17 %), and a reduction of NH3 emissions would mainly
decrease the nitrate and ammonium components rather than the predominant
components of PM2.5 in this part of the world. Over South Asia,
this effect is even more pronounced. The decreased emissions, in fact, have a
negligible impact on annual average PM2.5, reducing it by 0.62
(2 %), 0.76 (3 %) and 1.44 (6 %) µgm-3, for reductions
of ammonia emissions of 50, 75 and 100 %. The fraction of
fine-particle mass sensitive to ammonia in this region is very low (3 %),
since more than 90 % of the aerosol mass is not formed by the
ammonium-sulfate-nitrate components, but rather by organic carbon
(∼ 45 % of the total mass) and dust (∼ 35 % of the total
mass).
In all four regions considered here, the impact of NH3 emission
reduction on PM2.5 concentrations is strongest in winter. This
is related to the enhanced NH4NO3 partitioning in the gas phase due
to the higher temperatures in summer, so that a reduction of NH3
influences the gas-phase concentrations more strongly than the particulate
phase during this season. The opposite happens during the winter season.
Additionally, in the REF simulation, the winter total nitrate (gas and
aerosol) concentrations are somewhat higher than during the summer over
Europe (5.3 vs 4.5 µgm-3), USA (1.5 vs 1.0 µgm-3), South Asia (10.0 vs 3.4) and East Asia (8.2 vs 4.5 µgm-3). This is related to the lower boundary layer height in winter, causing less dilution of the emitted tracers, although in the Northern
Hemisphere the ammonia winter emissions are generally lower than in
summertime.
Average concentration of PM2.5 and PM2.5
components (in µgm-3). SO42- represents total
sulfate (i.e., SO42- and HSO4-). pH average values are
also listed.
The total PM2.5 sulfate (i.e., SO42-+HSO4-) is not
directly affected by NH3 emission reductions since it can exist in
the aerosol phase in the form of ammonium sulfate or ammonium bisulfate,
depending on the ammonium concentration. However, sulfate formation in the
aqueous phase is limited by high acidity. As a consequence, the
SO42- concentration in PM2.5 decreases, annually
averaged, by 11, 23 and 75 % over Europe, by 15, 28 and 57 % over North
America, by 3, 7 and 50 % over South Asia and by 18, 36 and 74 % over
East Asia for a reduction of 50, 75 and 100 % of agricultural emissions. This is counterbalanced by an increase of HSO4-
concentrations.
For Europe and North America, the simultaneous decrease of nitrate and
ammonium makes the reduction of agricultural emissions very effective,
especially in winter, in accordance with the findings of
and . Furthermore, the
relationship between ammonia and PM2.5 concentrations is not
linear and is governed by the sulfate / nitrate ratio .
Our EMAC simulations reveal that the PM2.5 response to NH3
emissions is more linear in winter (compared to summer), since the
sulfate / nitrate ratio is generally lower.
Following , the particle neutralization ratio (PNR,
i.e., (NH4+)/(2(SO42-+HSO4-)+NO3-))
calculations indicate that in Europe and East Asia
(both with PNR equal to 0.20) ammonia concentrations must be decreased relatively more strongly than
in North America and South Asia (PNR equal to 0.13 for both regions) to reach
the ammonia-limited regime, i.e., before PM2.5 can be efficiently
controlled by decreasing NH3 emissions.
Annual average mortality attributable to PM2.5 concentration changes
(in people/10 000 km2)
from the three scenarios with
agricultural emissions reductions of 50, 75 and 100 % (a,
b and c, respectively).
On the other hand, the absolute reduction in PM2.5 depends on the
fraction of fine-particulate mass that is directly ammonia sensitive. As a
consequence, Europe has the overall largest potential of reducing annual
averaged PM2.5 by strongly controlling NH3 emissions (up to
34 %), followed by North America (up to 16 %) and East Asia (up to
13 %), while South Asia has very limited potential (up to 6 %). Thus it
follows that, although the emission decrease needed in Europe to reach the
ammonia-limited regime is larger than in North America, the effective gain of
further reduction – once this regime is reached – is considerably larger.
In East Asia, where PM2.5 is not ammonia limited, even strong
emission decreases would reduce the PM2.5 mass by up to 13 %
on the annual average.
Impact on particle pH
In addition to the significant reductions in PM2.5
from ammonia emission controls, which are considered beneficial to
human health, we note that the aerosol pH can change substantially.
This has the potential of altering the particle liquid phase
and heterogeneous chemistry, including reactive uptake coefficients,
the outgassing of relatively weak acids and the pH of cloud
droplets that grow on aerosols, which in turn affects aqueous-phase sulfate formation.
Ammonia is in fact the most abundant and efficient base
for controlling the aerosol composition over anthropogenically influenced regions and neutralizes sulfuric, nitric and other acids.
In the REF simulation, the particles over the focal regions are highly
acidic, consisting mainly of ammonium sulfate and ammonium nitrate, as also
shown by . Figure illustrates how the
aerosol pH can drop due to NH3 emission decreases. Over Europe, the
calculated mean aerosol pH decreases by 0.35, 0.62 and 1.05 pH units for the
REF_50, REF_75 and REF_100 simulations. The
calculations indicate similar decreases over East Asia (0.35, 0.62 and
1.11 pH units) and smaller decreases over North America (0.16,
0.29 and 0.51 pH units), while the largest decreases are
present over South Asia (0.56, 0.99 and 1.72 pH units). Over
South Asia, the impact of ammonia emissions reduction on pH is the largest
(see Fig. ) despite the relatively small impact of the same
changes on PM2.5. This is due to the high sulfate concentrations,
which are neutralized in decreasing order by the presence of ammonium in the
three sensitivity simulations. The pH of PM2.5 is therefore more
sensitive to ammonia emissions (and its atmospheric concentrations) than
sulfate, as shown by . This increase of acidity for reduced
ammonia emissions would have a strong influence on halogen activation and
aerosol-gas equilibrium of weak acids in the atmosphere.
Contrary to what was found for PM2.5, the reduction of
pH is larger in summer than in winter. This is due to the
lower concentrations of ammonia in the aerosol phase in summer
(see Sect. ), i.e., with relatively low neutralization capability
in this season. Therefore, any further reduction of ammonia
emissions would strongly reduce the neutralization potential and therefore increase even more drastically the acidity
of the particles.
It should be mentioned that in the present calculations
the chemical impact of alkaline desert dust is not taken into
account, which can contribute significantly to
PM2.5 over areas downwind of the deserts
, e.g., over the Indian subcontinent in the dry season and
over eastern China in spring , so that the
pH effect described here is probably an upper limit.
This topic is subject of a publication in preparation.
Mortality attributable to air pollution in 1000 people yr-1. In parenthesis the minimum-maximum range.
RegionREF REF_50REF_75REF_100averagerangeaveragerangeaveragerangeaveragerangeEurope277(148–414)225(107–361)176(66–313)55(9–165)North America54(21–100)38(11–81)26(6–65)14(4–39)South Asia778(410–1140)753(396–1107)750(395–1102)696(365–1030)East Asia1381(607–1929)1275(553–1812)1195(514–1719)1037(447–1527)World3155(1523–4603)2905(1375–4313)2739(1280–4123)2353(1106–3619)Impact on public health
From the simulated PM2.5 concentrations, the mortality attributable
to air pollution has been calculated following the method of
and described in detail in . The exposure-response
functions of are used, which shows how fine-particulate
matter is associated with health impacts, through chronic obstructive
pulmonary disease (COPD), acute lower respiratory infections (ALRI),
cerebrovascular disease (CEV), ischaemic heart disease (IHD) and lung cancer
(LC). Here mortality attributable to PM2.5 at 50 % relative
humidity has been estimated; thus it does not account for ozone-related mortality
through COPD, which is ∼5 % of the total mortality attributable to
air pollution . The model results were interpolated to
the finer grid of the population map and, due to the coarse
model resolution used in this study, it is expected to have an
underestimation of exposure in urban areas. As discussed in the supplement of
, an uncertainty range of about ±50 % is
estimated for the mortality attributable to air pollution. The results,
presented in Table and Fig. , show
that a reduction of 50 % in agricultural emissions could have a large
impact on air-pollution-related mortality, reducing it worldwide by ∼8 %, i.e., affecting 250 000 people yr-1 (95 % confidence interval
(CI): 148–290). North America would benefit from a large relative
change, reducing the number of deaths by ∼30 % (16 000 people yr-1; 95 % CI:
10–19), followed by Europe (∼19 %, 52 000
people yr-1; 95 % CI: 41–53) and East Asia (∼8 %,
105 000 people yr-1; 95 % CI: 53–116), while almost no effects
are found over South Asia (∼3 %, 25 000
people yr-1; 95 % CI: 14–33). The relatively large effect in North America is explained
by the shape of the integrated response function , which
predicts a steep change in the attributable fraction at relatively low
PM2.5 concentrations. If it were possible to fully phase out
agricultural emissions, the global reduction of PM2.5-related
mortality would reduce by about 801 000 people yr-1 (95 % CI:
417–984). In Europe the number would be reduced by about 222 000
(95 % CI: 139–249), in North America by 40 000 (95 % CI: 17–61),
in East Asia by about 343 000 per year (95 % CI: 159-401) and in South
Asia by 82 000 per year (95 % CI: 45-110) (Table ).
Ammonia reduction policies should consider the intricate and nonlinear
effects through gas-aerosol partitioning and multiphase chemistry (including
aerosol pH changes), and therefore a coherent decrease of ammonia, nitrogen
and sulfur emissions is recommended. A coupled reduction of NH3 and
acid precursor emissions (e.g., SO2) cannot only limit the decrease
in aerosol pH but can also lead to a more efficient reduction of
PM2.5 concentrations than an NH3 emission control alone, as
shown by . In the electronic supplement, a table showing
the changes in mortality for the top 100 most populated countries is
presented. Consistently with the results of , central and
eastern European countries would benefit strongly from agricultural emission
reductions, drastically decreasing the per capita air-pollution-related
mortality. This can be seen also in Fig. , as the strongest
relative changes in PM2.5 due to agricultural emissions reduction
are found in central and eastern Europe, where a 50 % emission reduction would
decrease mortality attributable to air pollution by ∼ 15–20 %.
It must be emphasized that, although many epidemiological studies have linked
long-term PM2.5 exposure to public health outcome, it is yet
unclear whether any particular aerosol components and/or source categories are
predominantly responsible for air-pollution-related mortality. The debate is
open and firm conclusions of a specific relationship have not been reached
, although it is expected that some aerosol
components may be more toxic than others .
Conclusions
showed that in North America emission controls of
SO2 and NOx are likely to be very costly and probably less
efficient than decreasing agricultural emissions. Therefore, the regulation
of ammonia emissions from agricultural activities offers the possibility of
relatively cost-effective control policies for PM2.5. Our model
simulations indicate that a 50 % decrease of ammonia emissions could reduce
the annual, geographical average near-surface PM2.5 concentrations
up to ∼ 1.0 (11 %), 0.3 (8 %), 1.6 (5 %) and 0.6
(2 %) µgm-3 in Europe, North America, East Asia and South
Asia, respectively. The reduction can even be larger in winter (up to
∼ 1.3 (11 %), 0.6 (15 %), 2.2 (5 %) and 1.0 (3 %) µgm-3, respectively) when particulate ammonium nitrate concentrations
are typically higher than in summer.
Our model simulations underscore the strong nonlinearity that plays a role in
the sulfate-nitrate-ammonia system, which affects the efficiency of
PM2.5 controls, especially in summer when the
sulfate / nitrate ratio is high. A strong reduction of PM2.5 in
response to NH3 emission regulation is expected once the
ammonia-limited regime is reached. As a result, the possible PM2.5
reduction could be as large as ∼ 34 and ∼ 17 % in Europe and
North America, respectively. Our results also suggest that ammonia emission
controls could reduce the particle pH up to 1.5 pH units in East Asia
in winter and more than 1.7 pH units in South Asia, theoretically
assuming complete agricultural emission removal, which could have
repercussions for the reactive uptake of gases from the gas phase and the
outgassing of relative weak acids.
Furthermore, the global mortality attributable to PM2.5 could be
reduced by ∼250000 (95 % CI: 148–290) people yr-1
worldwide worldwide by decreasing agricultural emissions by
50 %, with a gain of 16 000 (30 %), 52 000 (19 %),
25 000 (3 %) and 105 000 (8 %) people yr-1 in North America, Europe, South and East Asia, respectively.
A total
phase-out of agricultural emissions would even reduce the mortality
attributable to air pollution worldwide by about 801 000 people yr-1 (25 %),
in Europe by about 222 000 people yr-1 (80 %), in North America by
about 40 000 people yr-1 (74 %), in South Asia by about 82 000
people yr-1 (10 %) and in East Asia by about 343 000 people yr-1
(25 %). These strong impacts are related to the nonlinear
responses in both the sulfate-nitrate-ammonia system and the
exposure-response functions at relatively low PM2.5 concentrations.
Therefore, emission control policies, especially in North America and Europe,
should involve strong ammonia emission decreases to optimally reduce
PM2.5 concentrations as well as further reductions in sulfur and
nitrogen oxides emissions to avoid strong acidification of particles.
The data from all model integrations are available from the
authors upon request.
The Supplement related to this article is available online at https://doi.org/10.5194/acp-17-12813-2017-supplement.
The authors declare that they have no conflict of
interest.
This article is part of the special issue “The Modular Earth
Submodel System (MESSy) (ACP/GMD inter-journal SI)”. It is not associated with a
conference.
Acknowledgements
Vlassis A. Karydis acknowledges support from a FP7 Marie Curie Career
Integration Grant (project reference 618349). Alexandra P. Tsimpidi
acknowledges support from a DFG Individual Grant Programme (project reference
TS 335/2-1). The article processing charges for
this open-access publication were covered by the Max Planck
Society. Edited by: Qiang Zhang
Reviewed by: two anonymous referees
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