Long-term trends of wet deposition of inorganic ions are
affected by multiple factors, among which emission changes and climate
conditions are dominant ones. To assess the effectiveness of emission
reductions on the wet deposition of pollutants of interest, contributions
from these factors to the long-term trends of wet deposition must be
isolated. For this purpose, a two-step approach for preprocessing wet
deposition data is presented herein. This new approach aims to reduce the
impact of climate anomalies on the trend analysis so that the impact of
emission reductions on the wet deposition can be revealed. This approach is
applied to a 2-decade wet deposition dataset of sulfate (SO42-),
nitrate (NO3-), and ammonium (NH4+) at rural Canadian
sites. Analysis results show that the approach allows for statistically
identifying inflection points on decreasing trends in the wet deposition
fluxes of SO42- and NO3- in northern Ontario and
Quebec. The inflection points match well with the three-phase mitigation
of SO2 emissions and two-phase mitigation of NOx emissions in Ontario.
Improved correlations between the wet deposition of ions and their
precursors' emissions were obtained after reducing the impact from climate
anomalies. Furthermore, decadal climate anomalies were identified as
dominating the decreasing trends in the wet deposition fluxes of
SO42- and NO3- at a western coastal site. Long-term
variations in NH4+ wet deposition showed no clear trends due to
the compensating effects between NH3 emissions, climate anomalies, and
chemistry associated with the emission changes of sulfur and nitrogen.
Introduction
To assess the long-term impacts of acidifying pollutants on the environment,
the wet deposition of sulfate (SO42-), nitrate (NO3-),
and ammonium (NH4+), among other inorganic ions, has been measured
for several decades through monitoring networks such as the European
Monitoring and Evaluation Programme (EMEP) (Fowler et al., 2005, 2007;
Rogora et al., 2004, 2016), the National Atmospheric Deposition
Program/National Trends Network in the US (Baumgardner et al., 2002;
Lehmann et al., 2007; Sickles II and Shadwick, 2015), and the Canadian Air and
Precipitation Monitoring Network (CAPMoN) (Vet et al., 2014; Zbieranowski
and Aherne, 2011). The high-quality data collected from these networks have
been widely used to quantify the atmospheric deposition of acidifying
pollutants (Lajtha and Jones, 2013; Lynch et al., 2000; Pihl Karlsson et
al., 2011; Strock et al., 2014; Vet et al., 2014). The data have also been
utilized to identify trends in the atmospheric deposition of reactive
nitrogen (Fagerli and Aas, 2008; Fowler et al., 2007; Lehmann et al., 2007;
Zbieranowski and Aherne, 2011) and to examine the impacts of acid rain and
the perturbation of the natural nitrogen cycle on sensitive ecosystems
(Wright et al., 2018). The long-term data can also be used for assessing the
effectiveness of environmental policies (Butler et al., 2005; Li et al.,
2016; Lloret and Valiela, 2016).
The wet deposition of SO42-, NO3-, and NH4+ is
affected by not only their gaseous precursors' emissions (Butler et al.,
2005; Fowler et al., 2007; Li et al., 2016) but also complex atmospheric
processes such as long-range transport, chemical transformation, and dry and
wet removal (Cheng and Zhang, 2017; Yao and Zhang, 2012; Zhang et al.,
2012). These processes can be largely affected by climate anomalies. For
example, climate anomalies can sometimes bring extreme precipitation amounts
in a particular month and subsequently lead to extremely high wet deposition
fluxes of ions through enhanced wet removal of air pollutants. Furthermore,
climate anomalies can alter the relative contributions of local sources
versus long-range transport to the total wet deposition amounts at reception
sites, thereby complicating the relationships between wet deposition and the
emission of air pollutants of interest (Lloret and Valiela, 2016; Monteith
et al., 2016; Wetherbee and Mast, 2016). The
emissions of SO2 and NOx have been decreasing substantially in Europe
and North America (Butler et al., 2005; Li et al., 2016; Pihl Karlsson et
al., 2011); coincidently, climate anomalies have also occurred more
frequently in the recent decades (Burakowski et al., 2008; Lloret and Valiela, 2016; Wijngaard et al., 2003), thereby leading to more complicated
linkages between wet deposition and emission trends on decadal scales.
Many trend analysis studies in the literature simply examined annual or
seasonal values as the data inputs for two popular trend analysis tools,
i.e., the Mann–Kendall (M–K) and linear regression (LR) methods (Marchetto
et al., 2013; Waldner et al., 2014, and references therein). These studies
focused on the detection of statistically significant trends; for example,
Waldner et al. (2014) conducted a comprehensive analysis on the
applicability of the techniques to different choices of length and temporal
resolutions of a data series. Regarding the resolved trend results, these
approaches are not well suited to separating the impact of air pollutants'
mitigation from the perturbation by climate anomalies. Large uncertainties
thus existed in the studies interpreting the major driving forces
determining the extracted trends in the wet deposition of SO42-,
NO3-, and NH4+. Regarding the fact that air pollutant emission
mitigation targets often vary in different phases of the entire study
period, inflection points may exist in the trends in the wet deposition of
ions. The inflection points were rarely studied, despite their importance
for assessing the effectiveness of environmental policies. An alternative
would be to use high-time-resolution data in the ensemble empirical mode
decomposition (EEMD) method (Wu and Huang, 2009); however, this method
still suffers from the end effect in certain scenarios, whereby the
extracted trends cannot be explained (Yao and Zhang, 2016).
A new approach is presented herein that aims to reduce the perturbations
from climate anomalies of data inputs so that robust trends can be
elucidated for evaluating the effectiveness of emission control policies. In
this approach, raw data are preprocessed to generate a new variable, which
is then applied to the M–K and LR methods. A piecewise linear regression (PLR)
is also used to extract trends for cases in the presence of inflection points.
The extracted trends in the wet deposition data on a decadal scale are then
properly linked to major driving forces such as emission reductions and
climate anomalies. This new approach is first applied to the wet deposition
data of SO42-, NO3-, and NH4+ in Canada, as an
example to demonstrate its capability and advantages over the traditional
approaches. The extracted trends in the wet deposition of ions are further
studied through correlation analysis with known emission trends of their
respective gaseous precursors (SO2, NOx, and NH3) in Canada and the
US. Major driving forces for the trends of ion wet deposition and how the
wet deposition ions responded to their precursors' emissions
in Canada are then revealed.
MethodologyData sources
Wet deposition flux (Fwet) data were obtained from CAPMoN
(https://www.canada.ca/en/environment-climate-change/services/air-pollution/monitoring-networks-data/canadian-air-precipitation.html, last access: 11 January 2020).
Data from four sites have been collected for over 20 years and were
chosen herein to illustrate the novel trend analysis method (Table S1 in the Supplement). Site
1 is an inland forest site at Chapais in Quebec. Site 2 is situated in a
coastal forest area at Saturna in British Columbia. Sites 3 and 4 are two
inland forest sites at the Chalk River and at Algoma, respectively, in
northern Ontario. Details on data sampling, chemical analysis, and quality
control can be found in previous studies (Cheng and Zhang, 2017; Vet and Ro, 2008; Vet et al., 2014).
The emissions data of gaseous precursors were downloaded from the Air
Pollutant Emission Inventory (APEI,
https://pollution-waste.canada.ca/air-emission-inventory/,last access: 11 January 2020) in Canada and
from the US EPA National Emissions Inventory (NEI, https://www.epa.gov/air-emissions-inventories/air-emissions-sources, last access: 11 January 2020) in
the US. These data were demarcated at a provincial level in Canada and at a
state level in the US. Data for the years of 1990 to 2011, which correspond
to the period of selected Fwet data, were used in this study.
Statistical methods
The M–K method is a popular nonparametric statistical procedure that can
yield qualitative trend results, such as “an increasing/decreasing trend
with a P value of <0.05,” “a probable increasing/decreasing trend
with a P value of 0.05–0.1,” “a stable trend with a P value of
>0.1 as well as a ratio of <0.1 between the standard
deviation and the mean of the dataset,” and “no trend for P>0.1 with all other conditions” (Kampata et al., 2008; Marchetto et al.,
2013). The LR method has also been widely used to extract trends (Marchetto
et al., 2013; Waldner et al., 2014). Zbieranowski and Aherne (2011) used LR
to extract trends by separating different phases because of the presence of
inflection points in the entire study period, and the approach is the same as
PLR (Vieth, 1989). In this study, the three methods were employed to compute
the trends of ion wet deposition using software downloaded from https://www.gsi-net.com/en/software/free-software/gsi-mann-kendall-toolkit.html (last access: 11 January 2020)
and Excel 2016, first using the annual Fwet directly as input data and
then using a modified input dataset, as described in Sect. 2.3.
The annual Fwet is widely used for trend analysis, and the trend results
are thereby used to compare with those derived from the approach proposed in
this study. Note that R2 is conventionally used in LR and PLR. However,
r instead of R2 is used in correlation analysis. Thus, R2 and r
are used for the two types of analyses in this study. Moreover,
several methods can be used to do PLR in classical statistics literature.
The simplest one is to manually conduct piecewise regression where
inflection points are visible to be recognized, and this approach is used in
this study. More complex algorithms are also available in literature to
conduct PLR for datasets with hundreds of points (Ryan and Porth, 2007, and
references therein). The complex algorithms have seldom been used to
identify trends in annual wet deposition of ions because of the short data
record.
Filtering climate anomalies
The modified input dataset was produced in two steps. The first step was an
effort to reduce the perturbation from the monthly climate anomalies to the
input data. This was done by creating a new variable that was defined as the
slopes of the regression equations of a series of study years against a
climatology (base) year using monthly Fwet data. Note that the monthly
Fwet data were aggregated from daily raw data before the regression
analysis. To ensure the presence of enough data points in each regression
equation, the data corresponding to 2-year periods (or 24 monthly
Fwet values) were grouped together, as detailed below. At a selected
site and for a given chemical component, monthly Fwet data were
generated for the first 2 years and were grouped together and rearranged
from the smallest to the largest values to form an array of data with 24
data points, i.e., A(i) with i=1 to 24. Repeating the above procedure for
the subsequent years using a 2-year interval to eventually obtain a series
of data arrays, A(i) now becomes A(i,j) with i=1 to 24 and j=1 to N,
where N is the total number of data arrays. The climatology data array
(CA(i)) was then defined as the average of all of the arrays as follows:
CA(i)=1N∑j=1NAi,j,i=1to24.
LR with zero interception was applied for each individual data array against
the climatology data array. In cases where the maximum monthly deposition
flux deviated greatly from the general regression curve, the slopes
(m values) were calculated after excluding the maximum monthly deposition
flux, which is an approach that reduced the perturbation to the m values
from the monthly-scale climate anomalies. The second step was to screen out
the outliers in m values, which reduced the perturbation to the m values
from the annual-scale climate anomalies.
Fitting monthly Fwet of SO42- against the
climatology values from every 2 years using LR with zero interception at
Site 1 according to the new approach described in Sect. 2. Fitted lines
represent the LR function with zero interception using 24 elements. x, y, and
R2 in the legend represent climatology monthly Fwet, monthly
Fwet in every 2 years, and the coefficient of determination in LR
analysis, respectively. The asterisk reflects the maximum value (cycled markers)
excluded for LR analysis and all P values <0.01.
Example case for data filtering
An analysis of Site 1 is used to illustrate the new approach and demonstrate
its advantages against the existing common approaches used in the
literature. Twelve 2-year periods of data (1988–1989, 1990–1991, etc.) are
available from this site. The regression of each dataset against the
climatology dataset was first performed using all of the monthly values to
obtain an m value (the slope) (Fig. 1a–d). For eight out of the 12 datasets, the m values were recalculated after excluding the maximum monthly
value of Fwet, which appeared to be an apparent outlier of the linear
regression. Three out of the 12 datasets showed the maximum Fwet being
positively deviated from the general trend, five negatively deviated from
the general trend, and four consistent with the general trend. The R2
values were then significantly increased for the eight sets, e.g., from the
original values of 0.79–0.94 to the improved values of 0.92–0.98. To
demonstrate that the excluded maximum value was an outlier, the case of the
1990–1991 dataset was taken as an example. The new regression equation
(y=1.47x, R2=0.98, Fig. 1a) predicted a maximum value in the range
of 330–368 mg m-2 month-1 using 3 times the standard
deviation (±3 SD, 0.08) at a 99 % confidence level. The actual
observed maximum value of 532 mg m-2 month-1 was much larger than
the upper range of the predicted value and was thus believed to be caused by
monthly-scale climate anomalies, i.e., the occurrence of an extreme amount of
precipitation. The maximum monthly deposition flux in 1990–1991 occurred in
September 1990 when the monthly precipitation depth reached 294 mm, which
was much higher than that in the same month of other years, e.g., 169, 68,
95, and 127 mm in 1988, 1989, 1991, and 1992, respectively. The maximum daily
precipitation depth in September was also higher in 1990 (91 mm) than in
other years (43.6, 12.2, 13.6, and 26.8 mm in 1988, 1989, 1991, and 1992,
respectively). However, the monthly geometric average concentration of
SO42- in precipitation (1.8 mg L-1) in September 1990 was
close to the mean value (1.7±0.3 mg L-1) in September 1988–1992
and was even smaller than that (2.9 mg L-1) in August 1990. The maximum
value was treated as an outlier and excluded for analysis.
Using the similar procedure, all outliers in this study were identified. The
exclusion of the observed maximum value greatly reduced the perturbation of
the short-term climate anomalies to the calculated m value in this 2-year
period; i.e., the m value decreased from 1.67 to 1.47, which in turn
increased the relative contribution of the air pollutants' emissions to the
calculated m value. Note that monthly changes in emissions may not impact
the Fwet as much as a large monthly change in precipitation depth
or concentration in precipitation does. For example, the monthly average
concentrations of SO2 were almost the same in May, September, and
October of 1990 (∼0.7µg m-3) while the monthly
Fwet of SO42- varied significantly, e.g., 113, 179, and 532 mg m-2 month-1 , respectively, in the same months. The monthly average
concentration of SO2 in February (4.8 µg m-3) was the
largest among the 12 months of 1990, but the corresponding monthly
Fwet of SO42- was the smallest (34 mg m-2 month-1).
Even through comprehensive analysis, any single climate factor alone,
including monthly precipitation depth, was apparently unable to explain the
negative deviation of the maximum monthly value of Fwet from the
general trend. The causes of such a negative deviation are yet to be
identified. In summary, the new approach proposed above by applying the
criteria of being outside the boundaries of ±3 times the standard
deviation of the general trend meets the objective of identifying outlier
data points.
The revised m values were further scrutinized by eliminating the outliers
caused by the annual-scale climate anomalies. For example, the m value of
1.31 in 1998–1999 greatly deviated from other m values, narrowly oscillating
approximately 0.96±0.07 (average ±1 SD) during the period of
1994–2005, even with the ±3 SD being considered (Fig. 1a–d). Using
the value of 0.96 as the reference, climate anomalies likely increased the
Fwet of SO42- by 37 % in 1998–1999. The m values were then
calculated by shifting 1 year in time to 1997–1998 (1.07) and to 1999–2000
(1.24). The Fwet in 1998 was less affected by climate anomalies than
that in 1999. Thus, the m value in 1997–1998 was within 0.96±0.21
(average ±3 SD) and used to replace the m value in 1998–1999 for the
trend analysis. Similar to the first step discussed above, this approach
meets the objective of identifying outlier m values by applying the criteria
of being outside the range of ±3 SD plus the average m value during a
decade or a longer period. The abnormally increased Fwet of
SO42- in 1999 was mainly because of the increased precipitation
depth (1312 mm), which was the largest during 1998–2011 (the annual average
precipitation depth excluding 1999 was 1067±86 mm). However, the
geometric average concentration of SO42- in precipitation in 1999
(1.0 mg L-1) was close to those in the other years, e.g., 0.9 mg L-1 in 1997 and 1998 and 1.0 mg L-1 in 2000.
Justification for the new approach
More justification of the new approach can be found in the Supplement, including Figs. S1–S6, wherein the statistical comparison
between this and other approaches was presented. Theoretically, the
extracted trend using the data preprocessed with the new approach is
determined by the local emissions of air pollutants, the regional transport
of air pollutants, and climate anomalies that are unable to be removed by
the new approach. It is assumed that the extracted trend is less affected by
microphysical/chemical processes, since 2-year data were used together to
calculate the m value.
In theory, if the data from different sites in the same region are grouped
together for trend analysis, the results may be better linked to the trends
of the regional emissions of related air pollutants. In the following
sections, trend analysis results from individual sites as well as those from
grouped sites are discussed. Sites 1, 3, and 4 showed similar trends in the
wet deposition of SO42- and NO3-, and these three sites
were grouped together.
The m values and annual Fwet of SO42-,
NO3- and NH4+ in 1988–2011 at Site 1, and the annual
emissions of SO2 and NOx in 1990–2011 in Quebec and Ontario,
Canada. Full and empty markers in blue in (a), (d) and (g) represent the
calculation of m values without and with the outlier, respectively. Empty
markers in red represent the outliers in m values and are excluded for trend
analysis, as detailed in Sect. 2. R2 reflects the coefficient of
determination of a variable against the calendar year from LR analysis, and
the fitted lines represent the LR function. M–K results are shown in (a–b),
(d–e) and (g–h). Phases 1, 2 and 3 in (a) and (c), Phases 1 and 2 in (d) and
(f) were gained from PLR presented in Sect. 3.1.
Results and discussionTrends at Site 1 after reducing perturbations from climate anomalies
Trends in the m values shown in Fig. 2 represent the trends after removing
the perturbations from climate anomalies at Site 1 in northern
Quebec from 1988 to 2011. SO42- and NO3- showed
decreasing trends from a LR analysis, with R2 values of 0.81 and 0.71,
respectively, and P values <0.01 (Fig. 2a and d). The decreasing
trends were also confirmed by the M–K method analysis. NH4+exhibited
a stable trend from M–K analysis (Fig. 2g), as well as no significant trend
with P value >0.05 from LR analysis. The annual Fwet values of
these ions are also shown in Fig. 2b, e, and f, and annual emissions of
SO2, NOx, and NH3 are shown in Fig. 2c, f, and i, respectively. These
data were used to compare and facilitate analysis in terms of identifying
inflection points and the advantage of using the m value over the annual
Fwet, as presented below.
The m values of SO42- and NO3- also allowed for
statistical identification of trends in different phases supported by annual
variations in emissions of SO2 and NOx (Fig. 2c and f) to some
extent. The inflection point for each phase is critical to (a) link the
annual Fwet of ions and the emissions of the corresponding precursors
and (b) assess the effectiveness of environmental policies. For example, the
trends in the m values of SO42- can be clearly classified into
three phases (Fig. 2a). Therefore, PLR should be applied separately for the
different phases in the presence of the inflection points, rather than LR
for the entire period, and the result is presented as
mvalue=1.38,1988≤x<1994mvalue=1.02,1994≤x≤2005mvalue=-0.185×x2-1001+1.15,2005<x≤2010,
where x represents the calendar year from 1988 to 2010.
The m values oscillated approximately 1.38±0.08 during Phase 1 (1988
to 1993) and approximately 1.02±0.08 during Phase 2 (1994 to 2005),
with a significant difference between the two phases under the t test (P value <0.01), thereby implying an abrupt decrease of approximately
30 % at the inflection point between the two phases. The m values linearly
decreased by approximately 20 % every 2 years, starting from the end of
Phase 2 to Phase 3 (2006–2011). Again, a significant difference existed
between Phase 2 and Phase 3 under the t test (P value <0.01). The
three phases generally aligned with the three-phase regulated SO2
emissions in Ontario. It should be stated that Phase 1 and Phase 3 each
covered only 6 years (N=6). Cautions should be taken to explain the
trend result in each phase in relation to precursors' emissions.
The PLR result of NO3- is expressed as
mvalue=1.09,1988≤x<2004mvalue=-0.128×x2-1001+1.08,2004≤x≤2010.
The trend in the m values of NO3- can be classified into two
phases with the inflection point at 2003, which was confirmed by the t test
result; i.e., the values oscillated approximately 1.09±0.09 during
the period from 1988 to 2003 and then exhibited a significant decrease of
approximately 50 % overall afterwards, with P value <0.01.
The m value of NO3- in 1998–1999 was approximately 30 % larger
than the mean value in 1988–2003 and exceeded the mean value plus 3 SD in
1998–2003 and thus was not included in the trend analysis. The sharp
increase in Fwet of NO3- occurred mainly in 1999, which was
probably due to largely increased annual precipitation depth as mentioned in
Sect. 2.4. The analysis was also supported by the geometric average
concentration of NO3- in precipitation, which was 1.1 mg L-1
in 1999, 5 % lower than that in 1988 and only 5 %–10 % higher than those
in 1990–1991, 1993, and 2002. Moreover, the monthly Fwet values of
NO3- in March, April, July, and August 1999 were actually lower
than the corresponding long-term averages in 1988–2003 (excluding 1999)
(Fig. S6a). This outcome indicates that the large increase in annual
Fwet of NO3- in 1999 was unlikely to have been determined
by the emissions of its gaseous precursors. The same can be said for the
large increase in Fwet of SO42- in 1999 (Figs. 2a, S6b).
To demonstrate the advantage of using the m values in trend analysis,
m values were correlated to the reported emissions of concerned air
pollutants. The trends in the m value of SO42- at Site 1 (Fig. 2a) were clearly different from those of the SO2 emissions in
Quebec (Fig. 2c) but matched well to those in Ontario (Fig. 2c), which
is also supported by their Pearson correlation coefficients, e.g., no
significant correlation (r=0.46 and P value >0.05) for the
former case and a good correlation (r=0.96 and P value <0.01)
for the latter case. Zhang et al. (2008) reported that this remote area can
receive the long-range transport of air pollutants from Ontario but that
transport is less likely from the intensive emission sources in Quebec.
In addition, LR analysis of the annual Fwet of SO42- revealed a decreasing trend (second row in Fig. 2b). The M–K method
analysis also confirmed the decreasing trend with annual Fwet as input.
However, the three-phase trend in Fwet of SO42- and related
inflection points, identified using the m values discussed above, were not
identified by the t test when simply using annual Fwet data as input.
The correlation between annual Fwet and
emission was 0.89 for SO42- vs. SO2 in Ontario (P values
<0.01), while the corresponding r value was as high as 0.96 between
m value and emission. After reducing the perturbations from climatic factors
to the annual Fwet, a stronger correlation was obtained between
Fwet and emission. The increased r further solidified the dominant
contribution of the long-range transport of air pollutants from Ontario
rather than Quebec to the wet deposition of SO42- at Site 1.
The trends in NOx emissions during 1990–2003 had similar bell-shaped patterns
in Quebec and Ontario, although with different magnitudes of emissions
(Fig. 2f). A different trend pattern was seen for the m value of
NO3- at Site 1 than for the abovementioned provincial emissions
during the same period (Fig. 2d), and there was no significant correlation
(r<0.41, with P value >0.05) between the m value of
NO3- and the emissions of NOx in Quebec or Ontario. Different
results were found for the period of 2002–2011 than those of 1990–2003
discussed above. In 2002–2011, the m value of NO3- decreased by
∼50 % and the NOx emissions decreased by ∼40 % in Quebec and Ontario; also, good correlations (r=0.94–0.95
with P values <0.01) were observed between m values and emissions.
The contrasting correlation results between the two different periods
discussed above implied the complex link between wet deposition of
NO3- and emissions of NOx. One might assume that the
perturbation from climate anomalies might not be fully removed by the new
approach for the period of 1990–2003, which overwhelmed the effects of NOx
emissions on the trends in m values of NO3-. Such a possibility is
practically very low since the approach works well for the period of
2002–2011. The contrasting results between these two periods are yet to be
explained. Fwet of NO3- and precipitation depth exhibited
only a weakly significant correlation, with r=0.58 and P<0.05
in 1988–2003 (the values in 1999 were excluded). Annual precipitation varied
by only ∼20 % during the 15 years, and this factor
alone was unlikely to explain the ∼100 % interannual
variation in Fwet of NO3- during that period.
LR analysis of the annual Fwet of NO3- revealed a decreasing
trend (second row in Fig. 2e), confirmed by the M–K method analysis.
However, the two-phase trend in Fwet of NO3- and related
inflection point were not identified by the t test when simply using annual
Fwet data as input. The correlations between annual Fwet and
emission were 0.74–0.76 for NO3- vs. NOx in Quebec and
Ontario (P values <0.01), while the corresponding r values
increased to 0.84–0.85 between m value and emission. Both the identified
inflection point and the stronger correlation between m value and emission
demonstrated the advantage of using the m value over annual Fwet of
NO3- in trend analysis.
The m value of NH4+ at Site 1 had no significant correlation (r=0.21 and P value >0.05) with the emission of NH3 in
Quebec but exhibited a weakly significant correlation (r=0.60 and P value <0.05) with the emission of NH3 in Ontario. Nearly all
of the NH4+ was associated with SO42- and
NO3- in the atmosphere (Cheng and Zhang, 2017; Teng et al., 2017; Zhang et al., 2012), and the trends in the m value of
NH4+ could be affected by many other factors besides NH3
emissions and climate anomalies, e.g., gas–aerosol partitioning and
different dry and wet removal efficiencies between NH3 and
NH4+ as well as pH value of wet deposition.
The stable trend in annual Fwet of NH4+ and the decreasing
trend in annual Fwet of NO3- gradually increased the relative
contributions of reduced nitrogen in the total nitrogen wet deposition
budget, e.g., from 40 % in 1998–1999 to 52 % in 2010–2011. A similar
trend has also been recently reported in the US (Li et al., 2016). Such a
trend was mostly due to the mitigation of NOx rather than climate anomalies.
Same as in Fig. 2 except for Site 2, and the
annual precipitation and annual emissions in British Columbia, Canada.
Horizontal dashes in (b) represent precipitation, and the fitted lines
represent the LR function.
Decadal climate anomalies drove trends at Site 2Trends in m value of SO42-
Figure 3 shows the trend analysis results at Site 2. An obvious shift in the
m values and annual Fwet occurred during 2001–2002, as detected by the
t test; i.e., the m values of SO42- oscillated approximately
1.15±0.11 in 1990–2001 and 0.76±0.02 in 2002–2011 (or
0.83±0.12 if the value in 2006–2007 was included), but with a
significant difference between the two periods with a P value <0.01.
The annual Fwet of SO42- oscillated approximately 632±63 mg m-2 in 1990–2001 and 452±74 mg m-2 in 2002–2011,
and the values between the two periods showed significant differences. The
shift led to the m values and annual Fwet of SO42- exhibiting a consistent decreasing trend by ∼40 % overall
from 1990 to 2011 using the LR and the M–K methods.
The emissions of SO2 oscillated approximately 1.13±0.07 in
1990–2001 and 1.06±0.03 in 2002–2011 in British Columbia, which did
not support the large decrease of approximately 40 % in wet deposition of
SO42- in 2002–2011. Statistically, no correlation existed between
annual Fwet of SO42- and the emissions of SO2 in
British Columbia, with r=0.52 and a P value >0.05. Although
the transboundary transport of air pollutants from the US cannot be
excluded, the almost constant m values from 2002 to 2011 (excluding
2006–2007) at Site 2 were inconsistent with the approximately 70 %
decrease in emissions of SO2 in the state of Washington in the
US during that period (not shown). Precipitation cannot explain the jump
in wet deposition either, because there was no corresponding jump in
precipitation during 2001–2002 (Fig. 3b).
The mean wind vector and speed (shading area) during
1990–2011 (a) and the anomalies of wind vector and wind speed (shading area)
during 1990–2001 (b), 2002–2011 (c), and 2007 (d) at 925 hPa over western
coastal Canada and the US (the anomalies in b, c, and d were conducted relative
to the 20-year period of 1990–2009 and the wind vector and wind speed were
from the North American Regional Reanalysis (NARR) with a spatial resolution
of 32 km by 32 km).
Van Donkelaar et al. (2008) analyzed aircraft and satellite measurements
from the Intercontinental Chemical Transport Experiment and proposed the
long-range transport of sulfur from East Asia to the west coast of Canada.
The wind vector and wind speed from the North American Regional Reanalysis
(NARR), with a spatial resolution of 32 km by 32 km (Mesinger et al., 2006),
were thereby analyzed to study the decadal changes in wind fields and
associated potential impacts on the long-range transport of air pollutants
over western coastal Canada and the US. The average wind fields including
mean wind vector and speed (shading in Fig. 4a–d) in 1990–2011 at 925 hPa
showed air masses over western coastal Canada and the US primarily
originated from the Pacific Ocean (Fig. 4a). However, the anomalies of wind
fields in 1990–2001 relative to 1990–2009 clearly showed a counterclockwise
pattern in the corresponding coastal area, including Site 2, while a
clockwise pattern existed in 2002–2011 relative to 1990–2009 (Fig. 4b, c).
The anomalies shown in Fig. 4c indicated the northwesterly wind being
enhanced in 2002–2011 over western coastal Canada and the US, possibly
reducing air pollutants being transported from the continent to Site 2. In
contrast, the anomalies in Fig. 4b indicated that the northwesterly wind was
reduced in 1990–2001. Consequently, more air pollutants might have been
transported from the continent to Site 2, resulting in a distinct
demarcation in 2002. This hypothesis was also supported by a large rebound
of the m value in 2006–2007, due to the increase in Fwet of
SO42- in 2007. The climate anomalies of wind fields in 2007
relative to 1990–2009 showed a counterclockwise pattern in the north, while
the clockwise pattern was pushed to the south (Fig. 4d). With the
northwesterly wind being reduced, a greater contribution of air pollutants
from the coast of Canada and US to Site 2 might have led to the large
increase in Fwet of SO42- during a few month-long periods in
2007.
The present study is the first one identifying the decreasing trend in the
annual Fwet of SO42- as being very likely caused by decadal
climate anomalies, i.e., wind fields, rather than by the emission reductions
of SO2. The decadal anomalies of wind fields may substantially alter
the long-range transport of air pollutants to the reception site. Note that
the causes for the decadal anomalies of wind fields in this region are
beyond the scope of the present study, but some information can be found in
the literature (Bond et al., 2003; Coopersmith et al., 2014; Deng et al.,
2014).
Trends in m values of NO3- and NH4+
For the wet deposition of NO3-, the m values also showed a clear
shift; i.e., the m values oscillated approximately 1.09±0.14 in
1990–2001 and 0.88±0.06 in 2002–2011, with a significant difference
between the two periods under the t test with a P value <0.01. The
annual Fwet of NO3- varied substantially, and the shift could
not be identified statistically. However, the annual Fwet of
NO3- exhibited a decreasing trend with M–K method analysis.
Similar to the case of SO42-, no significant correlation (r=0.49, P value >0.05) existed between the annual Fwet of
NO3- and the emissions of NOx in British Columbia.
In addition to decadal anomalies of wind fields, the interannual climate
variability such as precipitation depth, annual anomalies of wind fields in
2007, etc., (Fig. 3b) also affected the trends in m values and annual
Fwet of NO3-. The annual precipitation depth largely varied
from 601 mm to 1054 mm in the 2 decades. The perturbations from
interannual variability of precipitation depth cannot be completely removed
by the new approach. For example, the calculated m values in 1992–1993 and
1994–1995 were evidently lower than the m values in 1990–2001. However, the
annual geometric average concentrations of NO3- in 1992–1995
varied around 0.77±0.11 mg L-1 and were even larger than the
values of 0.66±0.08 mg L-1 in 1990–2001 (excluding 1992–1995).
The lower m values were mainly attributed to the lower precipitation depth
in 1992–1994 (Fig. 3b) rather than lower emissions of NOx. Interannual
climate variability including precipitation depth and annual anomalies of
wind fields may complicate the relationship between the Fwet of
NO3- and the emissions of NOx in British Columbia. For
example, the m values in 1990–1991, 1996–1997, 1998–1999, and 2000–2001 were
nearly constant at 1.17±0.03; however, the NOx emissions in British
Columbia in 1998–1999 were 26 % greater than those in 1990–1991. Moreover,
there was a sharp decrease in the NOx emissions (by ∼30 %)
from 2002 to 2011 in British Columbia. However, the m values oscillated
approximately 0.88±0.06 and showed no clear trend based on either the
M–K method or LR analysis. The interannual climate variability apparently
negated the impact of reduced emissions during these periods.
The m values and the annual Fwet of NH4+ oscillated
approximately 0.99±0.13 and 81±16 mg m-3, respectively,
in the period of 1990–2011 and showed no trend (Fig. 3). Neither the
m values nor annual Fwet of NH4+ showed the two-period
distribution pattern or had any significant correlation with the emissions
of NH3 in British Columbia at a 95 % confidence level. Similarly to
Site 1, the annual variation in Fwet of NH4+ at Site 2 cannot be simply explained by known emission trends.
In summary, decadal anomalies of wind fields overwhelmingly determined the
long-term trends in the wet deposition of SO42- and
NO3-, with the perturbation from monthly and annual climate
anomalies removed at Site 2. The interannual climate variability including
precipitation depth, annual anomalies of wind fields, etc. further
complicated the trends, resulting in undetectable influences of the emission
trends on the deposition trends. Since the decrease in Fwet of
NO3- appeared to be primarily caused by decadal climate anomalies
of wind fields, the relative contributions of NH4+ and
NO3- in the total N wet deposition varied little, i.e., 33 %
versus 67 % in 2010–2011 and 31 % versus 69 % in 1990–1991.
Regional m values at Sites 1, 3, and 4: (a)SO42-, (b)NO3-, and (c)NH4+. R2
reflects the coefficient of determination of a variable against the calendar
year from LR analysis, and the fitted lines represent the LR function. M–K
results are shown in (a–c). Phases 1, 2, and 3 shown in (a) and Phases 1 and 2 shown in (b) were gained from PLR presented in Sect. 3.3.
Regional trends in wet deposition in northern Ontario and Quebec
Trends in the m values or annual Fwet of ions at Sites 3 and 4 in the
northern regions of Ontario were generally similar to those found at Site 1
(Figs. S7 and S8). The three-phase trend in m values of SO42- and
the two-phase trend in m values of NO3- were also obtained at
Sites 3 and 4 after excluding a few m values that were caused by large
perturbations from climate anomalies. For example, the annual precipitation
depths of 1044 mm in 1987 and 905 mm in 1997 at Site 4 were evidently lower
than the average value of 1299±124 mm (excluding 1987 and 1997) in
1985–1997 (Table S2). However, the geometric average concentration of
SO42- of 1.5 mg L-1 in 1997 was the same as the mean value
of 1.5±0.2 mg L-1 in 1995–1999 (excluding 1997). The value of
1.6 mg L-1 in 1987 was also the same as that in 1989. The lower annual
precipitation depths in 1987 and 1997 than in the other years were very
likely the dominant factor causing the abnormally lower m values in
1986–1987 and 1996–1997. Thus, Sites 1, 3, and 4 were combined together to
study regional trends in the northern areas of Ontario and Quebec (Fig. 5a–c). Similar to those found at the individual sites, the temporal profile
of regional m values of SO42- can be clearly classified into
three phases (Fig. 5a) as follows: Phase 1 from 1988 to 1993 with m values
oscillating approximately 1.31±0.08, Phase 2 from 1994 to 2003 with
near-constant m values of 1.05±0.04, and Phase 3 for 2004 onward with
a decreasing trend by overall ∼50 %. Significant
differences of m values existed between any two of the three phases, based
on the t test results (P value <0.01). The PLR result is expressed
as below:
mvalue=1.31,1988≤x<1994mvalue=1.05,1994≤x<2004mvalue=-0.129×x2-1001+1.03,2004≤x≤2010.
The three-phase pattern of m values matched well with the three-phase
emission profile of SO2 in Ontario. Statistically, an ∼70 % decrease in m value and an ∼70 % decrease in
emissions were found from 1990 to 2011, with a correlation of r=0.95 (P value <0.01).
The profile of the regional m values of NO3- also clearly
exhibited two phases, according to the following t test results: Phase 1
from 1988 to 2003, with m values narrowly varying approximately 1.11±0.05, and Phase 2 from 2004 to 2011 with a decreasing trend by an overall
∼40 % against that in 2002–2003 (Fig. 5b). The PLR result
is expressed as below:
mvalue=1.11,1988≤x<2004mvalue=-0.11×x2-1001+1.03,2004≤x≤2010.
From 2002 to 2011, the m value had a moderately good correlation with the
NOx emission in Ontario (r=0.91, P<0.01), and the two variables
decreased by 30 %–40 % in this period. From 1990 to 2003, the near-constant
m value was, however, inconsistent with the bell-shaped profile of the NOx
emissions mainly caused by annual variations in NOx emission from the sector
of transportation and mobile equipment in Ontario and Quebec, which
could be due to either the perturbation from climate anomalies or an
unrealistic emissions inventory from (APEI) in Canada. Considering that the
first possibility was minimal over a large regional scale, especially when
the consistency was determined in a different time frame (2002–2011) in the
same region, it is thus doubtful that the bell-shaped profile of the NOx
emissions in 1990–2003 was realistic.
The regional m values of NH4+ largely oscillated from 1988 to 2003
(Fig. 5c). The m values of NH4+, however, decreased by
∼30 % from 2002 to 2011, leading to a probable decreasing
trend in the m value from 1988 to 2011. No correlation was found between the
m values of NH4+ and the emissions of NH3 in Ontario, which
is consistent with the findings at the individual sites discussed above.
Since the decrease in Fwet values of NO3- at Sites 3 and 4
was very likely due to the mitigation of NOx in Ontario, the decrease also
changed the relative contributions between NH4+ and NO3-in the total N wet deposition budget. For example, NH4+ and
NO3- contributed 52 % and 48 %, respectively, to the total
budget in 2010–2011 and 34 % and 66 %, respectively, in 1984–1985 at
Site 3. The corresponding numbers at Site 4 were 58 % and 42 % in
2010–2011 and 47 % and 53 % in 1985–1986.
Conclusions
Climate anomalies during the 2-decade period resulted in annual Fwet
of SO42- and/or NO3- deviating from the normal value by
up to ∼40 % at the rural Canadian sites. The new approach
of rearranging and screening Fwet data can largely reduce the impact of
climate anomalies when used for generating the decadal trends of Fwet.
With the climate perturbation being reduced, Fwet of SO42-
exhibited a three-phase decreasing trend at every individual site, as well
as on a regional scale in northern Ontario and Quebec. The three-phase
pattern of the decreasing trend in Fwet of SO42- matches well
with the emission trends of SO2 in Ontario, as supported by the good
correlation between wet deposition and emission, with r≥0.95 and
P<0.01. Fwet of NO3- exhibited a two-phase
decreasing trend, but only during the second phase Fwet of
NO3-, and the emissions of NOx in Ontario and Quebec matched
well, with a good correlation of r≥0.91 and P<0.01. Compared
to the results obtained without applying the new approach, it is concluded
that, after reducing the perturbation from climate anomalies, (1) better
correlation was obtained between Fwet of ions and the emission of the
corresponding gaseous precursors in northern Ontario and Quebec, and (2) the inflection points in the decreasing trends of Fwet of
SO42- and NO3- were visibly and statistically
identified.
However, the new approach cannot completely remove the perturbations from
climate anomalies, especially when this is the dominant factor and/or on
long timescales, as was the case at a coastal site of Saturna in British
Columbia. At this location, the decreasing trends in Fwet of
SO42- and NO3- were caused by the decadal anomalies of
wind fields, as well as being affected by interannual climate variability
including precipitation depth and annual anomalies of wind fields,
which overwhelmed the impact of the emission changes of the gaseous
precursors in this province. This is the first study that has identified
that decadal anomalies of wind fields can dominate trends in Fwet of
SO42- and NO3-. The new findings will stimulate more
studies on the impacts of decadal climate anomalies on atmospheric
deposition of concerned air pollutants. The long-term variations in
Fwet of NH4+ generally showed no clear long-term trends.
Moreover, no apparent cause–effect relationships were found between the wet
deposition of NH4+ and the emission of NH3. It can be
reasonably inferred that additional key factors besides those discussed in
this study also impact the trends of Fwet of NH4+. Thus,
cautions should be taken to use wet deposition fluxes of NH4+ to
extrapolate emissions of NH3.
Data availability
Data used in this study are available from the corresponding authors.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-20-721-2020-supplement.
Author contributions
XY and LZ designed the study, analyzed the data and prepared the
paper.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
We greatly appreciate the reviewers for their constructive comments which have helped us improve the paper quality.
Financial support
This research has been supported by the National Key Research and Development Program in China (grant no. 2016YFC0200500) and the Climate Change and Air Pollutants program of Environment and Climate Change Canada (grant no. N/A).
Review statement
This paper was edited by Aijun Ding and reviewed by G. M. Beachley and one anonymous referee.
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