ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-16-14997-2016The impact of historical land use change from 1850 to 2000 on secondary
particulate matter and ozoneHealdColette L.heald@mit.eduhttps://orcid.org/0000-0003-2894-5738GeddesJeffrey A.Department of Civil and Environmental Engineering, Massachusetts
Institute of Technology, Cambridge, MA, USADepartment of Earth and Environment, Boston University, Boston, MA,
USAColette L. Heald (heald@mit.edu)5December2016162314997150101September20165September201615November201621November2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/16/14997/2016/acp-16-14997-2016.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/16/14997/2016/acp-16-14997-2016.pdf
Anthropogenic land use change (LUC) since preindustrial
(1850) has altered the vegetation distribution and density around the world.
We use a global model (GEOS-Chem) to assess the attendant changes in surface
air quality and the direct radiative forcing (DRF). We focus our analysis on
secondary particulate matter and tropospheric ozone formation. The general
trend of expansion of managed ecosystems (croplands and pasturelands) at the
expense of natural ecosystems has led to an 11 % decline in global mean
biogenic volatile organic compound emissions. Concomitant growth in
agricultural activity has more than doubled ammonia emissions and increased
emissions of nitrogen oxides from soils by more than 50 %. Conversion to
croplands has also led to a widespread increase in ozone dry deposition
velocity. Together these changes in biosphere–atmosphere exchange have led
to a 14 % global mean increase in biogenic secondary organic aerosol
(BSOA) surface concentrations, a doubling of surface aerosol nitrate
concentrations, and local changes in surface ozone of up to 8.5 ppb. We
assess a global mean LUC-DRF of +0.017, -0.071, and
-0.01 W m-2 for BSOA, nitrate, and tropospheric ozone, respectively. We
conclude that the DRF and the perturbations in surface air quality
associated with LUC (and the associated changes in agricultural emissions)
are substantial and should be considered alongside changes in anthropogenic
emissions and climate feedbacks in chemistry–climate studies.
Introduction
Humans have dramatically altered the land surface of the Earth, affecting
over half of the land surface and permanently clearing over one-quarter of the
planet's forests (Hurtt et al., 2006; Vitousek et al., 1997). Land use
changes (LUCs) have accelerated with population growth, with 64 % of cropland
growth occurring since 1850 (Hurtt et al., 2011). These substantial shifts in
land use have perturbed the exchange of carbon, water, and energy between the
biosphere and atmosphere, impacting weather, and climate (Pielke et al.,
2002; Pitman et al., 2009). LUC also alters the
biosphere–atmosphere exchange of gases and particles that impact air quality
and contribute to short-lived radiative forcing; however, few studies have
quantified these effects (Heald and Spracklen, 2015).
Particulate matter (PM) and tropospheric ozone are deleterious to human
health and dominate uncertainty in current estimates of global climate
forcing (IPCC, 2013). Air pollution is the leading environmental cause of
premature mortality worldwide (OECD, 2012); exposure to ambient PM and
surface ozone was responsible for over 3.7 million premature deaths in 2010
(Lim et al., 2013). The most recent IPCC estimates that tropospheric ozone
and aerosols contribute +0.40 and -0.35 W m-2 respectively to
global direct radiative forcing (DRF) (IPCC, 2013). PM and ozone are
short-lived climate pollutants, with lifetimes of about a week and about a
month, respectively (Balkanski et al., 1993; Young et al., 2013). As a
result, reductions in the concentrations of the warming components (ozone,
black carbon) may be an effective strategy for mitigating near-term climate
change (Shindell et al., 2012). At the same time, the short lifetimes of
these species, coupled with the multitude of physical and chemical sources,
limit confidence in estimated global climate forcing from these species
(Myhre et al., 2013; Stevenson et al., 2013). In addition, the impact of
anthropogenic land use change are not included in these estimates of PM and
tropospheric ozone radiative forcing.
The terrestrial biosphere is a source of organics and nitrogen oxides (NOx)
that can contribute to PM and ozone formation. Biogenic volatile organic
compounds (BVOC) emitted from vegetation, such as isoprene and monoterpenes,
react quickly in the atmosphere to form low-volatility vapours that can
condense to the particle phase and produce secondary organic aerosol (SOA)
(Hallquist et al., 2009). Given sufficient NOx, this oxidation of BVOCs
can also produce ozone. However, in clean, NOx-poor conditions, these
BVOCs can react with and therefore consume ozone (Wang and Shallcross, 2000).
The emission of BVOC depends strongly on the type and density of vegetation
(Guenther et al., 2012). Similarly, microbial sources of nitrogen oxides from
soils vary with land use, and with canopy density (Hudman et al., 2012).
Managed ecosystems, such as croplands and pasturelands, are the dominant
source of ammonia emissions to the atmosphere through emissions from
fertilizer and domesticated animals (Erisman et al., 2008). In combination
with nitric acid formed from the oxidation of NOx, ammonia can produce
ammonium nitrate, an increasingly important source of inorganic PM in regions
where sulfur emissions controls substantially reduce sulfate (Paulot et al.,
2016; Pinder et al., 2007). The terrestrial biosphere is also a sink of gases
and particles. In particular, the dry deposition of ozone at the surface
accounts for ∼ 20 % of the ozone loss in the troposphere (Stevenson
et al., 2006). This removal is most efficient over high density vegetation
and croplands via stomatal uptake. Perturbation to vegetation and transitions
between land types alter these fluxes, with implications for PM and ozone.
Tree mortality, for example associated with insect infestation or disease,
can modulate biosphere–atmosphere exchange, generating transitory
perturbations in air quality (Berg et al., 2013; Geddes et al., 2016).
However, conversion of land cover, for example via clearing, can lead to
long-term changes in surface properties and therefore atmospheric
composition. A number of studies have explored how both natural and
anthropogenic future land use change may impact atmospheric chemistry
(Ganzeveld et al., 2010; Heald et al., 2008; Wu et al., 2012). Few studies
have explored the impact of historical land use change on PM and tropospheric
ozone. As a result, anthropogenic land use change is absent from most
estimates of radiative forcing from aerosols and tropospheric ozone. Ward et
al. (2014) investigate the impact of land use and land cover change (LULCC)
on greenhouse gases (including tropospheric ozone) and aerosols. They
estimate that historical changes in LULCC result in a radiative forcing of
+0.12 W m-2 for ozone and -0.04 W m-2 for aerosols
(-0.02 W m-2 direct, -0.02 W m-2 indirect) relative to
1850. In this study the increase in ozone associated with LULCC is largely
associated with the increase in methane and fires with partial compensation
due to a 6 % increase in ozone dry deposition. Their estimate of aerosol
forcing is not disaggregated by species, but includes dust, biogenic SOA, and
smoke. Unger (2014) suggests that land use change is responsible for
-0.13 W m-2 of radiative forcing from tropospheric ozone and
+0.09 W m-2 from biogenic SOA (direct only), primarily due to
decreases in BVOC emissions since 1850. These two assessments of radiative
forcing of ozone and PM associated with land use do not agree on the sign of
the forcing. However, it is critical to note that these studies differ
fundamentally in design and in the processes and species considered,
highlighting the complexity of this forcing and the need to quantify and
compare specific impacts. A review of the potential impacts of land use
change on air quality and climate suggests that historical LULCC has led to
an aerosol direct radiative cooling of ∼-0.10 W m-2, roughly
30 % of current estimates of aerosol DRF (Heald and Spracklen, 2015).
However, this review also points out the large uncertainty associated with
these changes and the need for additional modelling studies on this topic.
With this study, we aim to complement previous investigations and explore the
impacts of historical global anthropogenic land use change on
biosphere–atmosphere exchange processes and the resulting perturbations to
secondary PM and ozone.
Model description
To characterize the impact of historical land use change on air quality, we
use v9-02 of the global chemical transport model GEOS-Chem
(http://www.geos-chem.org). GEOS-Chem is driven by assimilated meteorology
from the Global Modeling and Assimilation Office (GMAO). Here we use GEOS-5
meteorology for the year 2010. The native resolution
(0.5∘× 0.67∘ horizontal resolution with 72 vertical
levels) is degraded to 2∘× 2.5∘ and 47 vertical
levels for computational efficiency.
The GEOS-Chem oxidant-aerosol simulation includes
H2SO4–HNO3–NH3 aerosol thermodynamics described by
ISORROPIA II (Fountoukis and Nenes, 2007; Pye et al., 2009) coupled to a
detailed HOx–NOx–VOC–O3 chemical mechanism. The model scheme
also includes primary carbonaceous aerosols (Park et al., 2003), sea salt
aerosol (Alexander et al., 2005; Jaeglé et al., 2011), and soil dust
(Fairlie et al., 2007; Ridley et al., 2013). SOA is produced from the
oxidation of biogenic hydrocarbons, aromatics, and IVOCs (intermediate volatility organic compounds) and represented with a
volatility basis set approach (Pye et al., 2010; Pye and Seinfeld, 2010).
In this study, global anthropogenic emissions for 1850 and 2000 follow the
Representative Concentration Pathway (RCP) historical emissions dataset (van
Vuuren et al., 2011) as implemented by Holmes et al. (2013). These include
fossil fuel, biofuel, and agricultural emissions. Fire emissions are
specified using GFED3 for the year 2010 (van der Werf et al., 2010),
consistent with the meteorology, and are fixed for all simulations. Methane
concentrations are similarly fixed at year 2010 levels.
We use the GEOS-Chem land use module recently developed by Geddes et
al. (2016) to specify consistent surface properties and to simulate
surface–atmosphere exchange processes. These include the emissions of BVOC,
the emission of NOx from soils, and dry deposition of gases and particles.
The land module uses 16 plant functional types (PFTs), consistent with those
described by the Community Land Model (CLM) (Lawrence et al., 2011). The
total leaf area index (LAI) is calculated interactively based on the PFT
distribution and PFT-specific seasonal LAI taken from the CLM, derived from
MODIS observations. BVOC emission factors for these PFTs are scaled online by
activity factors describing emission response to light, temperature, leaf
age, and CO2 following MEGAN v2.1 (Guenther et al., 2012). The PFTs are
mapped to the biomes used for the soil NOx emissions scheme described by
Hudman et al. (2012). This parameterization includes biome-specific
emissions, as well as re-emission of wet and dry deposited nitrogen and
fertilizer and manure nitrogen, all modulated online by temperature, soil
moisture, and rain. Finally, dry deposition is based on the
resistance-in-series scheme of Wesely (1989), with aerosol-specific
deposition described by Zhang et al. (2001). The surface resistance for gases
includes resistances to the ground, lower canopy, and vegetation, all of
which are driven by fixed parameters for 11 land use types specified in the
original Wesely (1989) parameterization. The PFTs are mapped to these 11 land
use types. In addition, the aerodynamic resistance and quasi-laminar
resistance calculations were altered to use biome-specific roughness heights
(which will reflect specified land use), rather than values from the
assimilated meteorological product.
List of GEOS-Chem simulations with relevant input parameters.
To estimate the shortwave and longwave flux perturbations associated with
tropospheric ozone and aerosols we apply the local (grid box) monthly mean
radiative flux-to-burden relationship for each species archived from previous
simulations (Heald et al., 2014) to changes in simulated burden. The
simulation of Heald et al. (2014) uses a similar version of GEOS-Chem
(v9.01.03) with identical meteorology and spatial resolution to the
simulations explored in this study, ensuring that this offline application of
radiative efficiency is a good approximation. We note that these radiative
efficiencies are estimated using present-day land reflectances. The physical
and optical properties assumed for aerosol species and the RRTMG radiative
transfer model are described in Heald et al. (2014).
Road map for how simulations are combined to estimate the impact of
land use change and the associated change in agricultural emissions on air
quality.
2000 anthropogenic1850 anthropogenicemissionsemissionsLand use change alone1–23–4Agricultural emissions alone1–56–3Land use change + Agricultural emissions1–76–4
In this study we perform a series of simulations to explore the impact of
land use change (and the associated changes in agricultural emissions) on
ozone and aerosols (Table 1). All simulations are performed with year 2010
meteorology, fire emissions, and methane concentrations. Land use change
modulates surface albedo, energy, and water exchange (Pielke et al., 2002,
2011; Pitman et al., 2009), which may feedback on atmospheric composition
(Ganzeveld et al., 2010; Ganzeveld and Lelieveld, 2004). Unger (2014)
suggests
that these feedbacks are small compared to the perturbation in BVOC emissions
from historical land use change. By design, by fixing meteorology at year
2010, we do not quantify these impacts in this study. Rather, our simulations
focus on the direct impact of changes in biosphere–atmosphere exchange. By
keeping methane concentrations constant we neglect changes in oxidative
capacity driven by changes in local methane sources associated with
agriculture (e.g. expansion of rice paddies, growth in livestock). Methane
concentrations also do not respond to the changes in oxidative capacity
associated with land-use-driven changes in short-lived precursor emissions
(assessed in Sect. 5). Given the challenges associated with identifying dust
regions produced from human-driven desertification (Ginoux et al., 2012), we
keep this source constant and do not characterize the land use change impacts
on dust. While land use change can produce large fire events, for example,
deforestation fires associated with land clearing, these fires are typically
transitory and vary considerably year to year (Hansen et al., 2013; van der
Werf et al., 2010). Regular fire emissions associated with land use change,
such as agricultural waste burning, make up less than 5 % of global
annual smoke emissions (van der Werf et al., 2010). Ward et al. (2014)
explore the impacts of historical LULCC impacts on dust and smoke. In this
study we focus on the impact of land use change on secondary aerosol and
ozone formation. We also perform a set of simulations to separately estimate
the impact of increasing agricultural emissions associated with land use
change. In these simulations we assume that all changes in agricultural
emissions of ammonia from 1850 to 2000 in the RCP emissions inventory are
associated with land use change (i.e. conversion to either croplands or
pastures). In addition, for 1850 agricultural emissions, we scale down the
fertilizer source of soil NOx emissions to 15.7 % of year 2000 values
(equivalent to the global 1850 : 2000 ratio for agricultural sources of
ammonia in the RCP emissions). We perform simulations to isolate the impact
of anthropogenic land use change alone, agricultural emissions changes alone,
and both together as described by Table 2. We perform each set of simulations
under both preindustrial (2000) and present-day (2000) anthropogenic
(nonagricultural) emissions to bracket the potential range of these impacts
depending on the background atmospheric conditions. We focus our results on
the net impacts of land use change along with the associated changes in
agricultural emissions (which we collectively refer to as LUC), unless
otherwise specified.
Present-day (year 2000) percentage of land area occupied by six
classes of vegetation.
Land use change from 1850 to 2000
Figure 1 shows the present-day (2000) distribution of vegetation used here
grouped from 15 vegetated PFTs to 6 main vegetation categories for
simplicity. The PFT distribution for the present day is the satellite phenology
dataset used by CLM4, which is based on MODIS data and cropping datasets
(Lawrence et al., 2011).
Change from preindustrial (1850) to present day (2000) in the
percentage of land area occupied by six classes of vegetation.
Figure 2 shows the change in vegetation distribution from preindustrial
(1850) to the present day (2000) used here. The historical (1850) PFT
distribution is specified as the Lawrence et al. (2012) CLM-specific
adaptation of the Hurtt et al. (2011) harmonized land use dataset. The
transition from
historical to present day highlights the global growth of
croplands, from 5.3 million to 14.7 million km2 at the expense of
forests and grasslands. The net increase of 9.4 million km2 of croplands
matches values provided by Hurtt et al. (2011), indicating that the mapping
of this dataset to the CLM PFTs preserved the change in cropland coverage.
The CLM PFTs do not include a separate pasturelands category; therefore
changes in pasturelands (increase by 25.5 million km2 from 1850 to 2000)
in the Hurtt et al. (2011) dataset are mapped to grasslands in the CLM
dataset. Figure 2 shows some regional increases in grassland coverage
consistent with pasture expansion. Finally, we note that much of the
agricultural expansion in western Europe and eastern North America pre-dates
1850, and thus a trend towards a return to forestlands is evident in these
regions in Fig. 2.
Annual average emissions impacted by historical land use change
alone; shown separately are changes in emissions due to both land use change
and associated agricultural emissions.
Land use change alone Land use change + associated agricultural emissions 18502000% change18502000% changeIsoprene (Tg yr-1)518459-11.4 %518459-11.4 %Monoterpenes (Tg yr-1)188165-12.0 %188165-12.0 %Sesquiterpenes (Tg yr-1)23.821.3-10.6 %23.821.3-10.6 %Ammonia (Tg yr-1)59.359.30.0 %28.459.3+109 %Soil NOx (TgN yr-1)*9.210.0+8.4 %6.310.0+58.5 %
* Soil NOx emissions tabulated here are when
nonagricultural anthropogenic emissions are held at year 2000 levels
(simulations 1 and 7). Reduced anthropogenic emissions in 1850 lower soil
NOx re-emissions levels slightly (but totals are within 2 %).
Figure 3 shows the change in LAI associated with the
historical to present-day change in land use. Expansion of croplands leads to
reductions in LAI, typically less than 20 % locally. Globally, there is a
3 % reduction in LAI due to land use alone. We note that the feedback of
increasing CO2 fertilization on terrestrial productivity is not included
here.
Annual average leaf area index (LAI) in present day (left) and the
change in LAI from preindustrial (1850) to present day (2000) (right).
Impact of historical anthropogenic land use change on emissions and
deposition
Table 3 summarizes the changes in emissions driven by land use change (and
associated agricultural activities) simulated in GEOS-Chem for the historical
transition from 1850 to 2000. Global annual mean BVOC emissions of isoprene,
monoterpenes, and sesquiterpenes decline by 10–12 % due to the expansion
of croplands (Fig. 2), a vegetation class with very low basal emission rates
for these BVOCs (Guenther et al., 2012). For example isoprene and α-pinene emission factors for croplands are at least 2 orders of magnitude
less than for needleleaf or broadleaf trees. The distribution of these
reductions is shown in Fig. 4. Fractional declines are consistent year-round,
with larger absolute decreases in summer at northern midlatitudes following
the seasonality of vegetation. These changes are more modest than the
35 % decrease in global BVOC emissions due to land use change estimated
by Unger (2014) over the same time period. Unger (2014) follows the same
historical land use trajectory used here (Hurtt et al., 2011) but the GISS
model mapping of this dataset includes pasturelands as part of the
cultivation biome, which also consists of croplands and does not emit BVOCs
(N. Unger, personal communication, 2016). In contrast, the CLM approach maps
pasturelands to grasslands, which are modest, but non-negligible, emitters of
BVOCs. Therefore, the substantial difference between our estimate and that of
Unger (2014) is associated with the uncertainty in characterizing BVOC basal
emission rates from pasturelands, which expand significantly from 1850 to
2000. Ward et al. (2014) estimate only a 1 % increase in all biogenic
emissions due to historical LULCC, but they do not disaggregate BVOCs and we
cannot compare simulated changes in terpenes directly.
Annual mean simulated emissions of BVOCs from vegetation. Total
emissions for present day (2000) shown on the left; the change due to
historical land use change is shown on the right. Global annual emission
values are shown inset.
Figure 5 shows the estimated increases in nitrogen emissions associated with
LUC. Global annual mean nitrogen oxide emissions from soils increase by
3.7 TgN yr-1 (more than 50 %) from 1850 to 2000. The majority of
this increase (2.9 TgN yr-1) is associated with enhanced fertilizer
usage in 2000 compared to 1850, but emissions increase by
0.8 TgN yr-1 due to shifts in biomes (and the associated emission
factors) as well as increased escape of NOx from the canopy due to lower
LAI in 2000 (Table 3). Relative changes in soil NOx emissions are
consistent year-round. Heald and Spracklen (2015) estimated a 50 %
increase in soil NOx emissions associated with LUC, in good agreement with
our estimate here, but to our knowledge no study has simulated the change in
soil NOx emissions due to historical LUC. These results highlight the need
to better constrain changes in soil NOx emissions due to fertilizer
application over the last 150 years (Felix and Elliott, 2013). Figure 5 also
shows that total ammonia emissions more than double from 1850 to 2000 due to
agricultural sources, following the RCP emissions (van Vuuren et al., 2011).
This reflects substantial increases in fertilizer usage on croplands and
domesticated animals on pasturelands.
Annual average tropospheric burden (Tg) of key species. Also shown
is the changes driven by historical land use change (including associated
agricultural emissions). Values estimated using year 2000 anthropogenic
emissions and 1850 anthropogenic emissions are shown.
Annual mean emissions of nitrogen oxides from soils (top row) and
ammonia (bottom). Total emissions for present day (2000) shown on the left;
the change due to historical land use change (and the associated agricultural
emissions) is shown on the right. Global annual emission values are shown
inset.
Historical LUC also modifies the surface properties that control the uptake
of gases at the surface. This loss is most significant for tropospheric
ozone, a relatively insoluble gas, which is biologically reactive and is
therefore readily taken up by vegetation (Stevenson et al., 2006; Wesely and
Hicks, 2000). The response of ozone dry deposition velocity to changes in
land use is dominated by changes to surface resistance. Therefore changes to
the aerodynamic resistances due to differences in roughness height (which
increases from grassland to agriculture to forests; see Table A1 of Geddes et
al., 2016) do not substantially impact the simulated ozone dry deposition.
Figure 6 shows that historical LUC has modestly increased O3 deposition
velocities over most regions where croplands have expanded. This increase is
driven by lower stomatal and surface resistance values associated with
croplands (compared to forests and grasslands) in the Wesely (1989) scheme.
This effect outweighs the decreases in deposition velocity associated with
decreases in LAI over croplands (Fig. 3). However, this is not the case in
Southeast Asia, where replacement of dense tropical forests with croplands
substantially decreases LAI (Fig. 3), driving down deposition velocities.
Local decreases in deposition velocity over western Europe and the eastern
United States are the result of reforestation of croplands since 1850. In
southeastern Brazil, expansion of pasturelands (shown as grasslands in
Fig. 2) at the expense of broadleaf trees leads to a decrease in deposition
velocity. Local differences do not exceed 20 % and are typically less
than 10 %. Historical LUC produces less than 1 % difference in global
mean ozone deposition velocity. Changes in deposition velocity shown in
Figure 6 are relatively aseasonal, with somewhat larger changes in summer at
northern midlatitudes associated with peak vegetation density. Verbeke et
al. (2015) explore the impact of future LUC in 2050 on the deposition of
ozone. Qualitatively their simulated response to cropland expansion and
reforestation are consistent with our results, with local changes to
deposition velocities that are within 10 %.
Impact of historical anthropogenic land use change on atmospheric
composition
The response of atmospheric composition to changes in biosphere–atmosphere
fluxes depends on the assumed anthropogenic emissions; we first present
results using present-day (2000) anthropogenic emissions and then comment
on differences when instead employing preindustrial (1850) anthropogenic
emissions (Tables 1 and 2).
Figures 7 and 8 show the impact of historical LUC on boreal summer
(June–August) and winter (December–February) mean surface concentrations of
key species. The decline in BVOC emissions driven by the expansion of
croplands leads directly to widespread decreases in biogenic SOA (BSOA).
Surface concentrations decrease by 14 % on average; local BSOA
concentrations in summertime decrease by up to 84 % and increase by up to
54 % over western Europe and eastern USA, where BVOC emissions increase
due to reforestation (see Figs. 2, 3, and 4). The global annual mean
tropospheric burden of BSOA decreases by 13 % due to historical LUC
(Table 4).
The more than doubling of ammonia emissions from preindustrial conditions to
present day associated with agricultural activities (Table 3) dramatically
enhances ammonium nitrate formation. This increase is particularly evident in
northern midlatitudes winter (Fig. 8), where cool temperatures favour nitrate
formation and mean surface nitrate concentrations more than double. The
global annual mean tropospheric burden of aerosol nitrate increases almost
4-fold due to historical LUC (Table 4). This increase is almost entirely the
result of ammonia emissions increases; land use change alone (simulations 1
vs. 2; see Tables 1 and 2) increases the tropospheric burden of nitrate by
only 1.1 %, stemming from the enhanced soil NOx emissions. These results
are consistent with Bauer et al. (2016), who estimate that agriculture is
responsible for 78 % of ammonia emissions and that this is the
prevailing source of ammonium nitrate formation in the Northern Hemisphere.
Annual mean simulated dry deposition velocity of ozone for
present day (2000) shown on the left; the change due to historical land use
change is shown on the right.
Boreal summertime (June–August) mean simulated surface
concentrations of biogenic SOA (BSOA), aerosol nitrate, nitric acid
(HNO3), nitrogen oxides (NOx), and ozone. Concentrations for
present day (2000) shown on the left; the change due to historical land use
change is shown on the right. All simulations performed with present-day
(2000) anthropogenic emissions; shown here are the differences between
simulations 1 and 7 (see Tables 1 and 2).
In summer, surface NOx concentrations are locally enhanced by LUC
(Fig. 7), driven by elevated soil NOx emissions. Despite this, we see that
surface ozone concentrations decrease in the Northern Hemisphere. These
decreases reflect elevated ozone deposition over croplands (Fig. 6) and
decreases in BVOC emissions (Fig. 4). Summertime mean surface ozone decreases
by up to 8.5 ppb, with at least a 1 ppb decrease throughout the Northern
Hemisphere. The changes in emissions and uptake over the Southern Hemisphere
lead to negligible changes in surface ozone (generally less than 1 ppb).
Boreal wintertime (December–February) mean simulated surface
concentrations of biogenic SOA (BSOA), aerosol nitrate, nitric acid
(HNO3), nitrogen oxides (NOx), and ozone. Concentrations for
present day (2000) shown on the left; the change due to historical land use
change is shown on the right. All simulations performed with present-day
(2000) anthropogenic emissions; shown here are the differences between
simulations 1 and 7 (see Tables 1 and 2).
Boreal summertime (June–August) mean simulated surface
concentrations of biogenic SOA (BSOA), aerosol nitrate, nitric acid
(HNO3), nitrogen oxides (NOx), and ozone. Concentrations for
present day (2000) shown on the left; the change due to historical land use
change is shown on the right. All simulations performed with preindustrial
(1850) anthropogenic emissions; shown here are the differences between
simulations 6 and 4 (see Tables 1 and 2). Shown with same colour bars as
Fig. 7 for comparison.
In winter, the large additional pool of atmospheric ammonia associated with
anthropogenic LUC pulls nitric acid into the particle phase. As a result,
nitric acid surface concentrations decrease by over 50 % throughout the
Northern Hemisphere (Fig. 8). This reduces NOx recycling from nitric acid,
leading to an overall decrease in NOx concentrations despite increases in
soil NOx emissions. Thus in winter, historical LUC has led to a drop in
NOx and BVOC concentrations in the Northern Hemisphere, while ozone
deposition velocities increase. Therefore, wintertime ozone decreases over
northern midlatitudes are of similar magnitude as in summer (up to 6.6 ppb,
generally 1–2 ppb) despite reduced photochemical production of ozone, and
thus lower absolute concentrations, in wintertime. Ozone changes in the
Southern Hemisphere in winter remain small, but local increases of up to
2.5 ppb are simulated. In these NOx limited regions, increases in soil
NOx emissions enhance ozone production and decreases in BVOC emissions
reduce the sink of ozone via isoprene oxidation. In some regions, such as
eastern Brazil, decreases in ozone deposition velocity due to expansion of
pasturelands (Fig. 6) bolster this enhancement.
Boreal wintertime (December–February) mean simulated surface
concentrations of biogenic SOA (BSOA), aerosol nitrate, nitric acid
(HNO3), nitrogen oxides (NOx), and ozone. Concentrations for
present day (2000) shown on the left; the change due to historical land use
change is shown on the right. All simulations performed with preindustrial
(1850) anthropogenic emissions; shown here are the differences between
simulations 6 and 4 (see Tables 1 and 2). Shown with same colour bars as
Fig. 8 for comparison.
While these changes in surface ozone concentrations are small, they are
comparable to the so-called “climate penalty” increases in ozone associated
with a warming climate (Tai et al., 2013; Wu et al., 2008). This suggests
that both historical analyses and future projections of ozone air quality
should consider land use conversion alongside emissions when characterizing
the impacts of anthropogenic activities. Table 4 shows that the net annual
mean tropospheric burden of ozone decreases only by 1.6 % due to
historical LUC, suggesting that ozone impacts on radiative forcing are
considerably more modest. Global mean tropospheric OH changes by less than
0.5 % due to historical LUC. Therefore in our simulations historical LUC
has little impact on the tropospheric oxidative capacity or the tropospheric
methane lifetime.
The above results characterize changes assuming that anthropogenic emissions
are fixed at year 2000 levels. While it is necessary to fix anthropogenic
emissions to isolate and quantify the effect of LUC, in reality,
anthropogenic emissions and land use co-evolve. Thus, it is equally valid to
assess the impact of LUC with simulations where anthropogenic emissions are
fixed at 1850 fluxes (note that methane remains at year 2010 levels in these
simulations). As shown in Table 2, we repeat all our simulations with these
alternate anthropogenic emissions. Table 4 shows the global mean tropospheric
burdens assessed under this scenario. Figures 9 and 10 can be compared to
Figs. 7 and 8 and show seasonal mean changes in surface concentrations when
anthropogenic (nonagricultural) emissions are fixed at 1850 levels. Biogenic
SOA burdens and concentrations are relatively unaffected by differences in
anthropogenic emissions; very minor differences are associated with changes
in oxidant levels. While the surface concentrations of NOx, HNO3, and
aerosol nitrate simulated under 1850 anthropogenic emissions are all
considerably lower than estimated using year 2000 emissions, the qualitative
patterns associated with LUC presented in Figs. 9 and 10 are consistent,
though more modest, than those presented in Figs. 7 and 8. We see from
Table 4 that, with 1850 anthropogenic emissions, ammonium nitrate formation
is NOx limited and a significant fraction of the ammonia emissions
increase due to agricultural sources remains in the gas phase. Thus, the
absolute increase in nitrate aerosol burden due to LUC is somewhat smaller
(by 17 %) than estimated using year 2000 anthropogenic emissions. As seen
in Figs. 9 and 10 surface concentrations are more sensitive to these effects
with much smaller absolute concentration changes when using 1850
anthropogenic emissions (increases of less than 1 µg m-3 in
Fig. 10 compared to widespread increases of more than
5 µg m-3 when using 2000 anthropogenic emissions in Fig. 8).
This suggests that while ammonium nitrate formation is dramatically curtailed
at the surface when anthropogenic NOx emissions are low, formation of
ammonium nitrate in the free troposphere is not substantially impacted by
reductions in anthropogenic NOx. Thus, the increase in surface nitrate
from preindustrial to present day is controlled more by the rise in
anthropogenic NOx emissions than the rise in agricultural ammonia
emissions, while the increase in the burden of tropospheric nitrate is driven
primarily by the increase in ammonia. Finally, while the change in global
mean tropospheric burden of ozone is similar whether assuming 1850 or 2000
anthropogenic emissions, some spatial differences are apparent in surface
concentrations. In particular, summertime surface O3 concentrations
locally increase (by up to 5 ppb) over northern hemispheric midlatitudes
regions (Fig. 9) where soil NOx emissions increase due to LUC (Fig. 5).
Ozone production is widely NOx limited under 1850 anthropogenic emissions,
and thus the ozone production efficiency of additional soil NOx emissions is
considerably higher, and outweighs the impact of elevated deposition
velocities for ozone due to LUC.
Direct radiative impacts of historical anthropogenic land use
change
The changes in annual mean tropospheric burden under 1850 and 2000
anthropogenic emissions shown in Table 4 bracket the potential impact of
historical LUC on secondary PM and ozone. To estimate the change in direct
radiative fluxes associated with historical LUC we apply monthly mean
radiative efficiencies for BSOA, nitrate, and tropospheric ozone estimated
from previous GEOS-Chem simulations (see Sect. 2) to our results using 2000
anthropogenic emissions. As this change is directly driven by anthropogenic
LUC it represents the direct radiative forcing associated with land use
change (LUC-DRF). Figure 11 summarizes these results.
Global annual mean direct radiative forcing associated with
anthropogenic land use change (LUC-DRF) from 1850 to 2000.
The largest radiative impact from historical LUC in our simulations is a
cooling of -0.071 W m-2 associated with the rise in nitrate aerosol
from preindustrial to the present day. This increase is driven almost entirely
by increases in ammonia emissions. The LUC-DRF of nitrate constitutes
81 % of the total direct radiative effect (DRE) of nitrate. Heald and
Spracklen (2015) estimate a stronger LUC-cooling associated with nitrate
(-0.094 W m-2), but this back-of-the-envelope calculation is
based on a stronger overall radiative effect of nitrate.
We estimate that decreases in BSOA due to historical LUC have produced a
warming of +0.017 W m-2. This LUC-DRF is ∼ 10 % of the DRE
of BSOA in our simulations. This value is smaller than the LULCC change in
DRE (+0.034 W m-2) estimated by Heald and Spracklen (2015), but
the later included CO2 fertilization and inhibition effects and is
therefore not directly comparable. The LUC-DRF of tropospheric ozone
associated with the very small changes in global burden discussed in Sect. 5
is a cooling of -0.01 W m-2. Ward et al. (2014) estimate a LUC-DRF
of opposite sign for ozone (+0.12 W m-2), but this value
primarily reflects changes in methane and fire emissions, which we do not
consider here; Ward et al. (2014) do not quantify the change in BVOC
emissions. Our results are qualitatively consistent with the LUC-DRF of BSOA
and tropospheric ozone estimated by Unger (2014) but are considerably more
modest. This largely arises from the smaller change in BVOC emissions
estimated in our study (∼ 11 %) compared to Unger (2014) (35 %)
due to different classifications of pasturelands and their associated BVOC
emissions (see Sects. 3 and 4).
Conclusions
This study explores the simulated impact of historical LUC on air quality and
DRF, with an emphasis on secondary formation of PM and tropospheric ozone.
Land use change from preindustrial (1850) to the present day (2000) is chiefly
defined by cropland and pastureland expansion worldwide, as well as local
reforestation in western Europe and the eastern United States. This has led
to a global decline in BVOC emissions (by ∼ 11 %), but the
associated agricultural sources have increased emissions of both ammonia (by
a factor of 2) and soil nitrogen oxides (by 50 %). At the same time,
surface uptake has been impacted by changes in vegetation type and density.
Generally, we find that ozone deposition velocities have increased due to
LUC, with some local exceptions associated with reforestation and expansion
of pasturelands.
These LUC-driven changes in biosphere–atmosphere exchange processes work in
concert to directly impact the secondary formation of BSOA, aerosol nitrate,
and ozone. Surface air quality is significantly impacted by these changes,
with a 14 % average decrease in BSOA concentrations, a more than doubling
of mean nitrate concentrations, and changes in surface O3 of up to
8.5 ppb. We find that changes to ozone surface concentrations in the
Northern Hemisphere are sensitive to the assumed anthropogenic emissions.
This reflects the changing balance of deposition and precursor emissions of
BVOCs and NOx in controlling ozone concentrations under varying NOx
levels. Associated with these changes we estimate a DRF associated with LUC
for nitrate (-0.071 W m-2), BSOA (+0.017 W m-2), and
tropospheric ozone (-0.01 W m-2). We note that these estimates are
obtained with fixed 2010 meteorology, and therefore we have not assessed the
interannual climate variability against which these values can be compared
for significance. While this is certainly not the first study to estimate the
DRF of nitrate, few models have routinely assess this (Myhre et al., 2013),
and to our knowledge this is the first that assesses the nitrate DRF
associated with LUC. This study suggests that BSOA concentrations were
elevated in the more extensively forested preindustrial era. This higher
preindustrial burden of natural aerosol may temper the indirect aerosol
effect (Carslaw et al., 2013; Menon et al., 2002), which we do not assess
here. We attribute differences between our more modest estimates of LUC-DRF
for BSOA and O3 and those of Unger (2014) to differing treatments of
pasturelands in the respective models, and thus the assumed BVOC basal
emission rate for pasturelands. These substantial differences in LUC-DRF
highlight how uncertainty in the representation of historical land use change
in Earth system models leads to large uncertainties in global chemical
composition.
This study examines only a subset of the emissions that may be impacted by
LUC. In particular, we do not assess the changes in primary PM associated
with LUC, including dust, smoke, and bioaerosol. It remains challenging to
disaggregate the natural and anthropogenic influences on these emissions. In
addition, we fix methane concentrations and therefore do not comprehensively
assess how changes in global oxidative capacity driven by LUC may impact
secondary aerosol and ozone formation. We also do not consider the
meteorological feedbacks on atmospheric composition associated with land use
change; more work is needed to quantify how these feedbacks compare to the
direct perturbations associated with biosphere–atmosphere exchange. Thus,
this study quantifies only part of the impacts of LUC. Furthermore, as our
results rely heavily on the parameterization of biosphere–atmosphere exchange
processes, more work is needed to validate these emissions and deposition
schemes (e.g. Hardacre et al., 2015). In addition, given uncertainties in
BSOA formation (Hallquist et al., 2009) and the general underestimate of
organic aerosol
in global models, including GEOS-Chem (Heald et al., 2011), the absolute
magnitude of the impact of LUC on both air quality and DRF via BSOA may be
underestimated here. Finally, uncertainties associated with the gas-phase
oxidation chemistry of isoprene, monoterpenes, and sesquiterpenes may impact
our simulated sensitivity of BSOA and O3 to LUC. The simulations
analysed in this study were performed with one chemical transport model
(GEOS-Chem); the degree to which model-specific treatments of chemical
oxidation, aerosol formation, emissions, removal, and meteorology may impact
the results cannot be assessed here. Thus, additional modelling
investigations using alternate model schemes are required to better
characterize the uncertainty surrounding the impact of land use change on air
quality and climate forcing.
We find that historical land use change has brought about substantial changes
in secondary PM and ozone formation, impacting air quality and direct
radiative forcing. The magnitude of these changes are comparable to the
feedbacks associated with climate change (Tai et al., 2012, 2013).
Furthermore, in an era of declining emissions of air pollution precursors
(Smith and Bond, 2014), anthropogenic land use change may become the dominant
human impact on atmospheric composition. Therefore, more work is needed to
improve our understanding and parameterization of biosphere–atmosphere
exchange processes and how these are altered by changing vegetation.
Data availability
The GEOS-Chem model output data used in this study are archived at MIT and
are available upon request from the authors (heald@mit.edu).
Acknowledgements
This work was supported by NSF (ATM-0929282 and ATM-1564495).
Jeffrey A. Geddes acknowledges support from an NSERC CREATE IACPES
postdoctoral fellowship and travel grant.
Edited by: Q. Zhang Reviewed by: N. Unger and one anonymous
referee
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