Introduction
Increased nitrogen and sulfur deposition is detrimental to ecosystems, since
it leads to decreased biological diversity (Clark and Tilman, 2008; Clark et
al., 2013; Stevens et al., 2004), increased terrestrial and aquatic
eutrophication (Bouwman et al., 2002; Bowman et al., 2008; Fisher et al.,
2011), and acidification (Greaver et al., 2012; Savva and Berninger, 2010).
The primary sources for nitrogen deposition are nitrogen oxides
(NOx ≡ NO + NO2) and ammonia
(NH3), both of which have anthropogenic and natural sources. The
major source for NOx is from the combustion of fossil fuels
in industry and energy use (Elliott et al., 2007; Lamarque et al., 2010). For
NH3, 80 % of the total emissions are from livestock manure
management and chemical fertilizer in 2005 as estimated from the US National
Emission Inventory (Reis et al., 2009), which are not regulated under current
legislation and underwent significant increases over the past decades (Xing
et al., 2013; Warner et al., 2017). Another possible source of NH3
emissions are vehicles, which may be twice as high as the emission estimates
in the current National Emissions Inventory (K. Sun et al., 2016). The primary emission source for
sulfur deposition is sulfur dioxide (SO2), which also mainly
originates from fossil-fuel combustion (Smith et al., 2011).
The ultimate fate for NOx, NH3, and SO2
is removal by wet scavenging and uptake by terrestrial and aquatic ecosystems
(Greaver et al., 2012). Wet deposition (WDEP), in the form of rain or snow,
is relatively easy to measure. Several observation networks were established
to provide reliable long-term records of WDEP, such as the European
Monitoring and Evaluation Programme (EMEP) in Europe, the National Acid
Deposition Monitoring Network (NADMN) in China, the Canadian Air and
Precipitation Monitoring Network (CAPMoN) in Canada, and the National
Atmospheric Deposition Program's National Trends Network (NADP/NTN) in the US
(Xu et al., 2015). These data have been extensively used to quantity the
sources, patterns, and temporal trends of WDEP of major species worldwide
(e.g., EEA, 2011; Jia et al., 2014; Cheng and Zhang, 2017; Lajtha and Jones,
2013; Du et al., 2014; Sickles II and Shadwick, 2015, 2007a, b). However, the
majority of these studies discussed WDEP based on the measurements only and
neglected the discussion of the spatial distribution and trends of dry
deposition (DDEP), as no direct DDEP measurements are available at these
networks. The calculated values at some sites, such as for the Clean Air
Status and Trends Network (CASTNET) and CAPMoN, cannot be easily spatially
interpolated due to limited availability of sufficient number of sites in a
region as well as the representativeness of the derived fields due to
assumptions in the spatial interpolation method (Schwede and Lear, 2014).
DDEP can contribute up to two-thirds of total deposition (TDEP) of nitrogen,
and neglecting it can lead to substantial underestimation of the total flux
(Flechard et al., 2011; Vet et al., 2014). Also, accurate estimates of TDEP
are usually required to assess the impacts of excess nitrogen and sulfur
deposition on ecosystem health, such as critical load exceedances and species
loss (Simkin et al., 2016).
To address these challenges, global and regional chemical transport models
(CTMs) have been extensively used in recent years to quantify the sources and
distribution of both WDEP and DDEP (Mathur and Dennis, 2003; Galloway et al.,
2008; Paulot et al., 2013; Sanderson et al., 2008; Zhang et al., 2012; Y.
Zhao et al., 2009; Y. H. Zhao et al., 2015, 2017), to study the projected
deposition changes in the future (Dentener et al., 2006; Larmarque et al.,
2013; Ellis et al., 2013; Kanakidou et al., 2016; J. Sun et al., 2017), and also
their effect on ecosystems (Simkin et al., 2016). CTMs can link the sources to
the deposition through atmospheric chemistry and transport processes and can
provide insights on the trends of TDEP and its components. In this study we
quantify the long-term geographical patterns and temporal trends of TDEP,
WDEP, and DDEP of total inorganic nitrogen (TIN) and sulfur over the continental
US (CONUS) based on a 21-year model simulation from 1990 to 2010 at
36 km × 36 km. The paper is organized as follows. Section 2
describes the model configuration and observation datasets as used for model
evaluation. The model evaluation results and the patterns and trends of
inorganic nitrogen and sulfur deposition are presented in Sect. 3, followed
by the conclusions in Sect. 4.
Methods
Model setup
The long-term simulations were previously performed using the coupled Weather
Research and Forecasting and the Community Multiscale Air Quality (WRF-CMAQ
model; Wong et al., 2012) with WRFv3.4 coupled with CMAQv5.02 driven by
internally consistent US emission inventories (Xing et al., 2013) covering
the CONUS domain discretized with a grid of 36 km horizontal resolution.
Spatial and time-varying chemical lateral boundary conditions were provided
by the hemispheric WRF-CMAQ (Mathur et al., 2017) running over the same
period (Xing et al., 2015a, b). Interested readers are referred to Gan et
al. (2015, 2016) for a detailed description of the settings of the CMAQ model
and physical configurations of the
WRF model (Table S1 in the Supplement). The performance of the coupled
WRF-CMAQ model for major trace gases, aerosol species, and meteorological
variables such as ozone (O3), fine particular matter
(PM2.5), and aerosol optical depth at both the hemispheric and
regional scale has been extensively evaluated in previous studies (Xing et
al., 2015a, b; Mathur et al., 2017; Gan et al., 2015, 2016; Astitha et al.,
2017; Porter et al., 2017) and has shown skill in simulating the magnitudes
and long-term trends of these variables. The dry deposition of each species
in the CMAQ model is calculated by multiplying the concentration in the
lowest model layer by the dry deposition velocity (Vd). The
Vd is calculated as the reciprocal of the sum of the
atmospheric aerodynamic resistance (Ra, the
resistance to transport through the atmosphere above the surface receptors),
quasi-laminar boundary layer (Rb, the resistance to transport
across the thin layer of air that is in contact with the surface and varies
with the diffusion of the pollutant transported), and surface resistances
(Rs, the resistance to the uptake of the pollutant by the surface
receptor, typically vegetation or soil).
Deposition observations in the US
A previous study using the offline CMAQ model has demonstrated moderate skill
simulating WDEP from 2002 to 2006 (Appel et al., 2011). Here we evaluate the
coupled WRF-CMAQ model's ability to simulate WDEP of nitrate
(TNO3), ammonium (NHx), and sulfate (TS) during
1990–2010 over the US, including both the interannual variability and
long-term trends. This is accomplished by comparing the model results with
observations from the US NADP (http://nadp.sws.uiuc.edu/ntn/, last
access: 21 June 2018), which measures total weekly wet deposition of these
species. The deposition is measured by wet-only samples, which are triggered
by precipitation. The deposition of sulfate and nitrate are analyzed by ion
chromatography and ammonium by flow injection analysis
(http://nadp.slh.wisc.edu/educ/sample.aspx, last access: 4 May 2018).
We first pair the wet deposition data between the observation and the model
results in time and space, and then extract the annual deposition for the
sites matching our criteria (at least 18 available years with 75 % annual
coverage for each year). Model data during periods of missing observations
are not considered in either the statistical evaluation or the trends
analysis. By applying the criteria, we use information at 170 of 359 sites,
with 141 sites in the eastern US (east of 110∘ W longitude) and 29
sites in the western US (west of 110∘ W longitude). The detailed
site information and the number of years of observational data used for the
model evaluation can be found in Table S2 and Fig. S1 in the Supplement. In
pairing the observed and modeled TNO3 WDEP values (which combines
WDEP of NO3- and HNO3), we multiply the model
estimated HNO3 WDEP by 0.984 to account for the transformation of
HNO3 to NO3- in solution in the measurements. In
pairing the observed and modeled NHx WDEP values (which
combines WDEP of NH4+ and NH3), we multiply the model
estimated NH3 WDEP by 1.06 to account for the transformation of
NH3 to NH4+ in the rainwater in the measurements. In
pairing the observed and modeled TS WDEP values (which combines WDEP of
SO42- and SO2), we multiply the model estimated
SO2 WDEP by 1.50 to account for the fact that SO2 will be
fully oxidized into SO42- during sampling (Appel et al., 2011).
For the model evaluation, we examine the correlation coefficients (R), mean
bias (MB), and the normalized mean bias (NMB):
NMB=∑1N(model-obs)∑1Nobs.
When discussing the model evaluation and deposition trends, we divide the US
into 10 ecological regions, following the North America Level I ecoregion
definition (https://www.epa.gov/eco-research/ecoregions-north-america,
last access: 21 June 2018), including Northern Forests, Northwestern Forested
Mountains, Marine West Coast Forest, Eastern Temperate Forests, Great Plains,
North American Deserts, Mediterranean California, Southern Semi-arid
Highlands, Temperate Sierras, and Tropical Wet Forests (Fig. S1 in the
Supplement). For the trend analysis, we focus on the linear trends (Colette
et al., 2011; Xing et al., 2015a), in which the linear least square fit
method is employed, and significance of trends is examined with a Student t
test at the 95 % confidence level (p = 0.05).
Errors in the simulated meteorology and precipitation in particular, can lead
to errors in estimating WDEP in the CMAQ model. We follow the previous
approach of Appel et al. (2011) to account for biases in modeled
precipitation by adjusting the modeled WDEP as
Bias adjusted
WDmod=PrecipobsPrecipmod×WDmod.
In Eq. (2), WDmod represents the WDEP from the model,
Precipobs represents annual or monthly accumulated
observed precipitation, and Precipmod represents the
corresponding annual or monthly accumulated precipitation from the model.
The US CASTNET provides long-term observations of atmospheric concentrations
as well as the dry deposition (https://www.epa.gov/castnet, last
access: 7 May 2018). However, the dry deposition values reported are not
directly measured, but estimated using the inferential method, pairing the
measured air pollutant concentration with a modeled deposition velocity from
the MLM model (Meyers et al., 1998). So rather than comparing dry deposition
estimates from two models, we choose to evaluate the model's performance in
simulating the ambient air concentrations (sulfur dioxide (SO2),
sulfate (SO42-), total nitrate
(TNO3 = NO3- + HNO3), and ammonium
(NH4)). We apply the same criteria in selecting valid observation
sites as the NADP/NTN. By doing this, we have chosen 39 valid sites out of
total 145 sites. The detailed site information and the number of years of
observational data used for the model evaluation can be found in Table S3 in
the Supplement.
Results
Model evaluation for WDEP and DDEP
The coupled WRF-CMAQ model generally overestimates the precipitation
throughout US (Fig. 2d, Fig. S2 in the Supplement), consistent with
previous findings (Ran et al., 2015). After performing the annual
precipitation adjustment for model simulated WDEP, we see that the
correlation coefficients (R) are slightly improved relative to using the
unadjusted WDEP values (Table 1), increasing from 0.89 to 0.92 for
TNO3, from 0.77 to 0.81 for NHx, and from 0.92 to
0.94 for TS (Fig. S3 in the Supplement). There are no significant changes for
R when we use the monthly precipitation adjustment compared with the annual
precipitation adjustment (Table 1). The model generally underestimates WDEP
for both the eastern and western US, except for TS where the model tends to
overestimate WDEP in the western US (Figs. 1 and 2). After performing the
precipitation adjustment, the NMB values increase for all three species
(Table 1). The model exhibited better performance for WDEP in the east than
the west, considering both the R and the NMB, largely because of the complex
terrain in the western US (Appel et al., 2011).
Correlation coefficient (R), mean bias (MB, kg ha-1), and
normalized mean bias (NMB, %) for the sum of the annual accumulated wet
deposition (WDEP) between the model and NADP sites from 1990 to 2010,
including both the model values with and without applying monthly and annual
precipitation adjustment (precip-adjust). The R for trends are the correlation coefficient
for the 21-year changes of the wet deposition (TNO3,
NHx, and TS) between the model and the observations.
TNO3
NHx
TS
R
No adjustment
0.89
0.77
0.92
Monthly precip-adjust
0.91
0.81
0.94
Annual precip-adjust
0.92
0.81
0.94
MB
No adjustment
-1.92
-0.50
-0.37
Monthly precip-adjust
-1.89
-0.52
-0.53
Annual precip-adjust
-2.16
-0.56
-0.77
NMB
No adjustment
-31.6
-30.9
-5.1
Monthly precip-adjust
-32.1
-33.7
-7.5
Annual precip-adjust
-35.6
-35.1
-10.5
R for trends
No adjustment
0.85
0.35
0.86
Monthly precip-adjust
0.94
0.64
0.95
Annual precip-adjust
0.94
0.66
0.95
The 21-year average TNO3 WDEP is highest in the Eastern Temperate
Forest region and lowest in the Southern Semi-arid Highlands, as seen from
both the observations and model results (Table 2). The model generally
underestimates the TNO3 deposition for all the regions with MB
values ranging from -1.11 kg ha-1 in the Southern Semi-arid
Highlands to -3.73 kg ha-1 in the Tropical Wet Forests, except for
the Marine West Coast Forest region where the model overestimates the
TNO3 WDEP, with MB values of 0.79 kg ha-1. The correlation
coefficients between the model and observations are generally much higher in
the eastern US (R larger than 0.80) than in the western US (R less than
0.70). The 21-year average NHx WDEP is also highest in the
Eastern Temperate Forest region and lowest in the Southern Semi-arid
Highlands (Table 3). The model generally underestimates the
NHx WDEP, with MB values ranging from
-0.26 kg ha-1 yr-1 in the Northwestern Forested Mountains to
-0.81 kg ha-1 in Tropical Wet Forests, and overestimates in the
Marine West Coast Forest, with MB of 0.24 kg ha-1. The correlation
coefficients between model and observations for NHx WDEP
share similar spatial patterns with TNO3 WDEP but have lower R
values. The 21-year average TS deposition is highest in the Eastern Temperate
Forests region and lowest in the North American Desserts. Similar to
TNO3 and NHx, the model underestimates the TS WDEP
over most of the regions, but overestimates observed values in the Marine
West Coast Forest and Mediterranean California. The R between the model and
the observations is generally larger than 0.9 in the eastern US but ranges
from 0.46 to 0.79 in the western US.
Scatter plots for the annual accumulated WDEP (total oxidized
nitrogen (TNO3, a), reduced nitrogen (NHx, b), and total
sulfate (TS, c)) between precipitation-adjusted model results and
observations from 1990 to 2010 for 170 valid sites with 3531 valid data
points. The data at each NADP are assumed to be valid for our analysis only if
at least 18 years of observation data are available at that site and the data
coverage is at least 75 % for each year. Each point in the plots represents
the annual accumulated WDEP for a given site and year. Note that the annual
accumulated WDEP values used in this analysis may not be the actual annual
totals due to missing data in the observations. The green color is for the
eastern US, and the red color is for the western US, with the dashed line
for the 1 : 2 and 2 : 1 ratio and the solid line for the 1 : 1 ratio.
Evaluation results for the 10 ecoregions for TNO3 WDEP.
The units are kg ha-1 for the means and MB and kg ha-1 yr-1 for the trends. The bolded values indicate trends that are statistically
significant, with the p value less than 0.05 for the standard Student's
t test.
ID
Region name
No. of sites
Mean
MB
NMB
R
Trends
Obs
Mod
Obs
Mod
5
Northern Forests
18
7.56
4.97
-2.59
-0.34
0.93
-0.22
-0.16
6
Northwestern Forested Mountains
28
3.23
1.28
-1.95
-0.60
0.70
-0.03
-0.01
7
Marine West Coast Forest
3
1.55
2.34
0.79
0.51
0.44
-0.02
0.01
8
Eastern Temperate Forests
72
8.77
6.14
-2.63
-0.30
0.97
-0.20
-0.17
9
Great Plains
24
4.73
2.62
-2.11
-0.45
0.87
-0.05
-0.04
10
North American Deserts
17
1.81
0.66
-1.15
-0.63
0.82
-0.02
-0.01
11
Mediterranean California
4
2.34
2.39
0.05
0.02
0.76
-0.09
-0.03
12
Southern Semi-arid Highlands
1
1.59
0.49
-1.11
-0.69
0.85
-0.02
-0.01
13
Temperate Sierras
2
2.49
0.80
-1.68
-0.68
0.61
-0.01
0.00
15
Tropical Wet Forests
1
5.80
2.07
-3.73
-0.64
0.88
0.11
0.04
Clear downward trends are seen for TNO3 and TS WDEP from both the
observations and model in Fig. 2a, c, while NHx deposition
exhibits much larger interannual fluctuations (Fig. 2b). In Fig. 3 we see
much larger decreasing trends for TNO3 and TS WDEP in the eastern
US than those in the western US. This is due to the fact that the emission
reductions mostly occurred in the eastern US (Xing et al., 2013; Simon et
al., 2015), and the model captures this trend very well especially for
TNO3 and TS WDEP with R values of 0.94 and 0.95, respectively. A
stronger decreasing trend over the Northern Forests and Eastern Temperate
Forests regions compared to other regions is observed for both TNO3
and TS WDEP, and the model is also able to capture these very well but a
slightly distinctions in the trends for each ecoregion (Tables 2 and 4). We
see that the model generally underestimates the magnitude of the decreasing
WDEP trends at many sites for TNO3 and TS (Tables 2 and 4), which
may be caused by the coarse model resolution (36 km) and uncertainties in
the emission inventories. For NHx, we see increasing WDEP
trends for most of the sites but the trends are not statistically significant
(Table 3).
Comparison of the temporal trends for the annual accumulated WDEP
(across all the 170 valid sites) for (a) TNO3, (b) TNHx,
(c) TS, and (d) precipitation, for the eastern US (green, averaged over 141
sites) and western US (red, average over 29 sites) between observations
(dashed lines) and annual precipitation-adjusted model values (solid lines).
The scale shown on the left is for the eastern US and on the right for the
western US.
The same as Table 2 but for NHx
ID
Region name
No. of sites
Mean
MB
NMB
R
Trends
Obs
Mod
Obs
Mod
5
Northern Forests
18
1.92
1.22
-0.7
-0.37
0.83
-0.01
-0.01
6
Northwestern Forested Mountains
28
0.64
0.39
-0.26
-0.4
0.36
0.00
0.00
7
Marine West Coast Forest
3
0.45
0.69
0.24
0.54
0.16
0.00
0.01
8
Eastern Temperate Forests
72
2.13
1.58
-0.55
-0.26
0.66
0.00
0.00
9
Great Plains
24
2.03
0.91
-1.12
-0.55
0.86
0.03
0.01
10
North American Deserts
17
0.58
0.19
-0.38
-0.66
0.62
0.00
0.00
11
Mediterranean California
4
1.01
0.64
-0.38
-0.37
0.82
-0.02
0.00
12
Southern Semi-arid Highlands
1
0.42
0.13
-0.29
-0.69
0.76
0.00
0.00
13
Temperate Sierras
2
0.63
0.26
-0.37
-0.59
0.75
0.00
0.00
15
Tropical Wet Forests
1
1.14
0.33
-0.81
-0.71
0.75
0.04
0.01
Compared with Appel et al. (2011), our model results indicate larger bias for
WDEP for both the eastern and western US (Table S4 in the Supplement). The
NMB increases for all three species in our results from 2002 to 2006 after
applying the precipitation adjustment, which was also seen in Appel et
al. (2011), except for TS, which Appel et al. (2011) reported decreased bias
after the precipitation adjustment. The discrepancies for the model
performances between our study and Appel et al. (2011) could be caused by the
grid resolutions, in which coarse-resolution models (e.g. 36 km in our
study) have more challenges to simulate various chemical and physical
processes compared with fine resolution (e.g. 12 km used in Appel et al.,
2011). There are numerous differences between the model configuration and
versions used in this analysis and those previously used by Appel et
al. (2011). Specific model process representation differences between
CMAQv5.0 used here and CMAQv4.7 used in Appel et al. (2011) can be found at
https://www.epa.gov/cmaq/cmaq-models-0 (last access: 21 June 2018).
Comparison of the WDEP trend for each valid site between the
precipitation-adjusted model values and observations for total oxidized
nitrogen (TNO3, a), reduced nitrogen (NHx, b), and total
sulfate (TS, c). Each NADP site is assumed to be valid for our analysis only
if at least 18 years of observation data are available at that site and the
data coverage is at least 75 % for each year. The green color is for the
eastern US, and the red color is for the western US, with the dashed line
for the 1 : 2 and 2 : 1 ratio and the solid line for the 1 : 1 ratio.
To evaluate the model's performance in simulating the DDEP, we compare the
model simulated concentration with the observations from CASTNET. Comparisons
of annual average simulated concentrations with corresponding measurements at
the CASTNET sites show strong correlation for SO2 (R of 0.88),
SO4 (0.95), TNO3 (0.94), and NH4 (0.94). Some
underestimation for SO4 and overestimation in other species
ambient concentrations is noted (Fig. S4 in the Supplement). The model also
captures the trends for these species with very high R, but the magnitude
of the decreasing trends is underestimated by the model (Fig. S5 in the
Supplement).
The same as Table 2 but for TS.
ID
Region name
No. of sites
Mean
MB
NMB
R
Trends
Obs
Mod
Obs
Mod
5
Northern Forests
18
7.76
7.33
-0.42
-0.06
0.95
-0.29
-0.23
6
Northwestern Forested Mountains
28
2.15
1.88
-0.27
-0.13
0.70
-0.05
-0.01
7
Marine West Coast Forest
3
3.35
6.08
2.73
0.82
0.46
-0.02
0.04
8
Eastern Temperate Forests
72
11.78
11.04
-0.70
-0.06
0.97
-0.34
-0.29
9
Great Plains
24
4.16
2.95
-1.21
-0.29
0.91
-0.07
-0.04
10
North American Deserts
17
1.38
0.81
-0.58
-0.41
0.79
-0.04
-0.01
11
Mediterranean California
4
1.40
3.15
1.75
1.25
0.67
-0.03
0.01
12
Southern Semi-arid Highlands
1
1.45
0.89
-0.56
-0.39
0.91
-0.07
-0.04
13
Temperate Sierras
2
2.30
1.05
-1.25
-0.54
0.76
-0.08
-0.01
15
Tropical Wet Forests
1
7.41
2.94
-4.47
-0.60
0.73
0.09
0.04
Spatial patterns of modeled total deposition of nitrogen and
sulfur
Table 5 shows that modeled TDEP of TIN, i.e., the
sum of TNO3 and NHx, is much higher in the Eastern
Temperate Forests than any other ecoregion (regional average of 10.08 and
7.95 kg N ha-1 in 1990 and 2010, respectively), followed by the
Northern Forests and Mediterranean California regions. The hotspot for TIN
TDEP has shifted from the eastern US in 1990 to the northern central US in
2010, with relative higher values in North Carolina (NC) and Pennsylvania
(PA) (Fig. 4). During the period from 1990 to 2010, TIN TDEP has
significantly decreased (with p < 0.05 for the standard
two-tailed Student's t test) over several ecoregions, including Eastern
Temperate Forests, Northern Forests, Mediterranean California, and Marine West
Coast Forest (decreasing trend of 0.12, 0.071, 0.038, and
0.017 kg N ha-1 yr-1, respectively) as a result of significant
reductions in anthropogenic NOx emissions (Xing et al.,
2013). Slightly increasing but not statistically significant trends are
estimated in TIN TDEP for the Great Plains and the Tropical Wet Forests while
the remaining regions show statistically insignificant decreasing trends
(Table 6). We see statistically significant increasing trends of TIN TDEP in
eastern NC (larger than 0.2 kg N ha-1 yr-1), which is mainly
caused by the increase in NHx TDEP (Fig. 5) arising from
increased NH3 emission from hog farming (Xing et al., 2013; Paulot
et al., 2014). There are also significant increasing trends of TIN TDEP over
Iowa, Minnesota, and South Dakota (larger than
0.04 kg N ha-1 yr-1) because of the increased
NHx TDEP related to animal foster and corn plantation
(Figs. 4 and 5). In Fig. 5 we see that the TIN TDEP decreasing trends
predominantly result from the TNO3 TDEP decreases across the US,
with larger decreasing rates in the east than the west. The increasing TIN
TDEP trends over the east and central states (such as NC, PA, and Virginia)
were caused by the NHx TDEP increases, which in turn arise from
increases in NH3 emissions (Paulot et al., 2013).
Spatial distribution of annual TDEP of total inorganic nitrogen
(TIN, kg N ha-1, a–c) and sulfur (kg S ha-1,
d–f) in 1990 (a, d), 2010 (b, e), and
the simulated trends of the TIN (c, kg N ha-1 yr-1) and
total sulfur (f, kg S ha-1 yr-1) TDEP changes over the
2 decades. Grey areas on the right plots show p value for the standard
two-tailed Student t test greater than 0.05 (i.e., areas where trend
estimates were not significant at the 95 % confidence level).
TDEP (WDEP + DDEP; units of kg N ha-1 for nitrogen deposition
including TNO3, NHx, and TIN and kg S ha-1 for TS) in
1990 and 2010 for the 10 ecoregions.
ID
Region name
TNO3
NHx
TIN
TS
1990
2010
1990
2010
1990
2010
1990
2010
5
Northern Forests
4.21
2.19
2.35
2.56
6.56
4.74
9.86
3.56
6
Northwestern Forested Mountains
1.36
1.12
0.91
1.26
2.27
2.38
1.75
1.47
7
Marine West Coast Forest
1.07
1.35
2.00
2.43
3.7
3.78
5.03
3.95
8
Eastern Temperate Forests
6.12
3.27
3.96
4.68
10.08
7.94
17.54
6.66
9
Great Plains
2.45
1.84
2.77
3.97
5.22
5.81
3.36
2.16
10
North American Deserts
1.49
1.12
0.83
1.01
2.32
2.13
1.34
1.05
11
Mediterranean California
3.15
2.08
2.68
3.36
5.84
5.44
1.68
1.74
12
Southern Semi-arid Highlands
1.68
1.10
1.18
0.93
2.86
2.03
2.87
0.92
13
Temperate Sierras
2.00
1.48
0.91
1.02
2.91
2.5
2.33
1.2
15
Tropical Wet Forests
4.11
3.35
1.27
2.05
5.38
5.41
5.15
3.77
Similar to TIN TDEP, TDEP of total sulfur (TS), i.e., the sum of SO2
and SO42-, shows a distinct spatial gradient from the east
(usually larger than 9 kg S ha-1) compared to the west (lower than
3 kg S ha-1) (Fig. 4). In 1990, the TS was even higher than
30 kg S ha-1 in some states of the central US, such as Indiana,
Ohio, PA, and West Virginia. In 2010, TS TDEP is still higher in the east
than the west, but TS TDEP in the east has decreased by half (to lower than
15 kg S ha-1) for most regions. From 1990 to 2010, the estimated TS
TDEP exhibits significant trends across the US, with decreasing trends
generally larger in the east (larger than 0.4 kg S ha-1 yr-1)
and lower in the west (less than 0.2 kg S ha-1 yr-1) as a
result of SO2 decreases from the passage of the Clean Air Act
Amendments of 1990. All the ecoregions experienced statistically significant
decreases of TS TDEP over the past 2 decades, which were dominated by the
decreases in SO42-, except for the Mediterranean California
ecoregion, which showed an insignificant decreasing trend (Table 6). The
largest decreasing trend was seen in the Eastern Temperate Forests region
(-0.51 kg S ha-1 yr-1), followed by the Northern Forests
(-0.23 kg S ha-1 yr-1) and the Great Plains
(-0.082 kg S ha-1 yr-1).
Spatial distribution of the trends for the TDEP of total oxidized
nitrogen deposition (TNO3, a), and reduced nitrogen
(NHX, b) from 1990 to 2010. Grey areas on the both plots show
p value great than 0.05 for the standard two-tailed Student t test (i.e.,
areas where trend estimates were not significant at the 95 % confidence
level).
Trends for total deposition (WDEP + DDEP, units of
kg N ha-1 yr-1 for nitrogen deposition including TNO3,
NHx and TIN, and kg S ha-1 yr-1 for TS) over the
10
ecoregions. The bolded values indicate trends that are statistically
significant with the P value less than 0.05 for the Student's t test.
ID
Region name
TNO3
NHx
TIN
TS
5
Northern Forests
-0.087
0.016
-0.071
-0.23
6
Northwestern Forested Mountains
-0.013
0.011
-0.002
-0.021
7
Marine West Coast Forest
-0.018
0.002
-0.017
-0.053
8
Eastern Temperate Forests
-0.15
0.034
-0.12
-0.51
9
Great Plains
-0.041
0.044
0.003
-0.082
10
North American Deserts
-0.016
0.008
-0.008
-0.023
11
Mediterranean California
-0.051
0.013
-0.038
-0.013
12
Southern Semi-arid Highlands
-0.014
0.002
-0.012
-0.074
13
Temperate Sierras
-0.016
0.009
-0.006
-0.054
15
Tropical Wet Forests
-0.026
0.041
0.015
-0.055
Wet versus dry nitrogen and sulfur deposition trends in the US
Figure 6 shows that the TIN WDEP is higher in the east than the west due to
both greater precipitation (Fig. 2d) and higher atmospheric burden of
airborne reactive nitrogen in the east (Xing et al., 2013). In addition,
estimated TIN WDEP shows widespread significant decreasing trends in the
eastern US while trends in the western US generally have smaller magnitudes
and often are not statistically significant. The most significant decreasing
region is the Eastern Temperate Forests, with an annual decrease of
-0.070 kg N ha-1 yr-1, followed by the Northern Forests
(-0.037 kg N ha-1 yr-1) and the Great Plains
(-0.023 kg N ha-1 yr-1) (Table S5 in the Supplement). The
decreasing trends of TIN WDEP are
mainly caused by the WDEP of TNO3 (Fig. S6a and Table S5 in the
Supplement). There are no significant changes for WDEP of
NHx in the majority of the US except for the region Tropical
Wet Forests (Fig. S6b), consistent with previous findings (Lajtha and Jones,
2013). TIN DDEP is higher in the eastern US and lower in the northwestern and
central US. Significant decreasing trends for the TIN DDEP
are seen over the Eastern
Temperate Forests (-0.049 kg N ha-1 yr-1), Northern Forests
(-0.033 kg N ha-1 yr-1), Mediterranean California
(-0.032 kg N ha-1 yr-1), and Marine West Coast Forest regions
(-0.022 kg N ha-1 yr-1) (Table S6 in the Supplement). The
decreases of TIN DDEP over these regions are dominated by the DDEP of TNO3 (Fig. S6c and Table S6 in
the Supplement). In contrast, there are significant increasing trends of TIN
DDEP over the Tropical Wet Forests (0.027 kg N ha-1 yr-1),
Great Plains (0.026 kg N ha-1 yr-1), and Southern Semi-arid
Highlands (0.009 kg N ha-1 yr-1). These increases are caused by
the DDEP of NHx (Fig. S6d and Table S6 in the Supplement).
Figure 7 shows a distinct spatial distribution for both the WDEP and DDEP of
sulfur, with much higher values in the eastern US in the vicinity and
downwind of major sources. Significant decreasing trends are noted for both
the wet and dry TS deposition for all the ecoregions except the Marine West
Coast Forest and Mediterranean California, where TS WDEP
are estimated to increase, though
the trend is not statistically
significant (Tables S5 and S6 in the Supplement). TS DDEP trends
are larger or comparable to TS
WDEP trends for the majority of the regions, except for Southern Semi-arid
Highlands, Temperate Sierras, and Tropical Wet Forests, where the magnitude
of the decreasing trends for DDEP are lower than those for WDEP.
Spatial distribution of WDEP (a–c) and DDEP (d–f) of
TIN (kg N ha-1) in 1990 (a, d), 2010 (b, e), and the simulated trends
(c, f, kg N ha-1 yr-1) over the 2 decades. Grey areas on the right
plot show p value great than 0.05 for the standard two-tailed Student t test
(i.e., areas where trend estimates were not significant at the 95 %
confidence level).
As in Fig. 6 but for sulfur. The units are kg S ha-1 for (a, b, d, e) and kg S ha-1 yr-1 for (c, f).
Deposition budget in the US
Interannual variability of the TDEP for inorganic nitrogen (a)
and sulfur (b) in the US from 1990 to 2010, including their fractions
labeled as percent contributions for WDEP of oxidized nitrogen (NO3),
WDEP of reduced nitrogen (NHx), DDEP of oxidized nitrogen (NO3)
and DDEP of reduced nitrogen (NHx) deposition for the nitrogen, and
WDEP versus DDEP for sulfur.
Figure 8a shows that the US domain average TDEP of TIN generally
decrease over the past 2 decades,
from 5.55 kg N ha yr-1 in 1990 to 5.00 kg N ha yr-1 in
2010. The decrease in TIN TDEP is mainly caused by reductions in
TNO3. The TNO3 WDEP is estimated to decrease from 1.26 to 0.76 kg N ha yr-1 and
TNO3 DDEP decrease from 1.98 to 1.35 kg N ha yr-1 during
the same period. DDEP accounts for large fractions of TDEP for TIN over the
entire 1990 to 2010 time period, 58–65 % of TDEP over the US (Fig. S7 in
the Supplement). The relative proportions of TNO3 over the TDEP
have also changed over the past 2 decades in response to changes in precursor
emissions. TNO3 deposition dominates TIN TDEP until the early
2000s. After 2003, however, NHx dominates the TIN TDEP over
the US (Fig. S7 in the Supplement). This is consistent with Li et al. (2016),
who showed that the US TIN deposition has transitioned from being dominated
by TNO3 to NHx as a result of NOx
emission reductions and increases of unregulated NH3 emissions. The
increasing contributions of NHx to the TIN TDEP can also be
seen in Fig. 9, which shows increasing proportions of NHx
contributions across larger regions of the CONUS during the 1990 to 2010
period (significant increasing trend (p < 0.05) for the
NHx fraction of the total TIN across the US). This has
resulted from the significant NOx reduction due to
regulations and growth in NH3 emissions (Warner et al., 2017).
The ratio of TDEP of NHx over the TDEP of TIN in 1990 (a),
2010 (b), and the trend (c). The blue color in panels (a, b) indicates a NHx ratio
less than 0.5, which means TNO3 dominates the total nitrogen
deposition, while the red color indicates a ratio larger than 0.5 and
NHx dominates the total nitrogen deposition.
Similar to TIN TDEP, the TS TDEP has also decreased, from
6.85 kg S ha-1 yr-1 in 1990 to
3.26 kg S ha-1 yr-1 in 2010 (Fig. 8b), as a result of the
decreasing anthropogenic SO2 emissions (Smith et al., 2011; Xing et
al., 2013). The TS DDEP dominates the TS TDEP during the first decade, but TS
WDEP becomes dominant after the year 2004. The dry sulfur deposition has
decreased by 58 % from 1990 to 2010, from 3.65 to
1.55 kg S ha-1 yr-1, while the wet sulfur deposition has
decreased by 47 %, from 3.20 to 1.70 kg S ha-1 yr-1, during
the same period.
Conclusions
In this study, we use model simulations spanning a 21-year period from
1990 to 2010 to investigate the spatial distribution and temporal trends in the
total inorganic nitrogen (TIN) and total sulfur (TS) deposition across the
US, including changes in chemical composition of the deposition as well as
relative importance of the wet (WDEP) and dry deposition (DDEP) components.
By evaluating the model's performance against observations from the NADP
network, we find that the model generally underestimated the WDEP for both
the oxidized nitrogen (TNO3) deposition and reduced nitrogen
(NHx) deposition across the US. The model underestimates TS
WDEP in the eastern US, but overestimates it in the western US. The model
exhibits better performance in simulating the WDEP in the eastern US than
in the western US. The 21-year model simulations capture the spatial pattern
of decreasing trends for the WDEP of TNO3 and TS very well, with a
correlation coefficient typically larger than 0.9. However, the model
generally underestimates the decreasing trends of the TNO3 and TS
WDEP. The model performance is worse in simulating the spatial distribution
and trends of the NHx deposition compared with
TNO3 and TS, which may be caused by uncertainties in the
representation of NH3 emissions in the model. The underestimation
of the NHx deposition could also be caused by uncertainties
in temporal and spatial representation of emissions associated with
fertilizer applications and bi-directional exchange of NH3 between
the air and underlying soil and vegetation surfaces. Applying the
bi-directional NH3 exchange mechanism in the coupled model could
improve the model's ability in simulating NHx deposition
(Appel et al., 2011; Bash et al., 2013).
The modeled total deposition (TDEP) of TIN and TS is higher in the eastern
US and lower in the western US. For TIN, it is highest in the Eastern
Temperate Forests and lowest in the Northwestern Forested Mountains. For TS
it is also highest in the Eastern Temperate Forests but lowest in the North
American Deserts. The TDEP of TIN has seen significant decreasing trends over
the Eastern Temperate Forests, Northern Forests, Mediterranean California, and
Marine West Coast Forest and results from decreases in both wet and dry
deposition of TNO3. Modeled TDEP of TS was found to be decreasing
over the entire US, with larger decreasing trends for the dry deposition
compared with the wet deposition.
The TDEP of TIN over the entire US domain is dominated by DDEP, accounting
from 58 to 65 % of the total from 1990 to 2010. TDEP of oxidized nitrogen
dominates TIN deposition in the US in the first decade but a shift occurred
in 2003 when TDEP of reduced nitrogen becomes the dominant factor. The DDEP
of TS dominates the TS deposition in the first decade while WDEP
becomes the dominant factor after the year 2004.
Our analysis, as well as others (Li et al., 2016; Kharol et al., 2017), shows
that reduced nitrogen has dominated the total nitrogen deposition budget in
the US in recent years. Additionally, model calculations show strong
increasing trends in dry deposition amounts of NHx across
the US which arise from both increasing NH3 emissions and reduced transport distances. Reductions in SO2 and
NOx emissions (and consequently their oxidation products)
have decreased the amounts of NHx partitioning to the
aerosol phase where scavenging by rain is the primary sink. Consequently,
more NHx remains in the gas phase and dry deposits closer to
the source regions. The study highlights the growing importance of
NHx deposition as emissions of NOx and
SO2 have been reduced substantially over the years. We conclude
that it is urgent to acquire accurate NH3 emissions inventories and
maintain additional measurements of NHx, not only for
improving the air quality model's performance but also for controlling the
nitrogen deposition in the US. In addition, dry deposition of TNO3
and TS is a large fraction of the total deposition in the US, demonstrating
the need for accurate dry deposition measurements as well as more robust
characterization of dry deposition in air quality models.