Critical loads and H+ budgets of forest soils affected by air pollution from oil sands mining in Alberta, Canada

Atmospheric Environment 69 (2013) 56e64

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Critical loads and Hþ budgets of forest soils affected by air pollution from oil sands mining in Alberta, Canada Kangho Jung a, b, Scott X. Chang a, *, Yong Sik Ok c, M.A. Arshad a a

Department of Renewable Resources, 442 Earth Sciences Building, University of Alberta, Edmonton, Alberta, Canada T6G 2E3 Department of Agricultural Environment, National Academy of Agricultural Science, 150 Suinro, Kweonseonku, Suwon 441-707, Republic of Korea c Department of Biological Environment, Kangwon National University, Chuncheon 200-701, Republic of Korea b

h i g h l i g h t s < Proportion of SO4 2- was greater in interception than in bulk deposition. < Exceedance of S deposition was underestimated if based on bulk deposition only. < Sulfur deposition was lower than critical loads in the studied watersheds. < The studied forest soils were recovering from previous acidification.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 7 September 2012 Received in revised form 4 December 2012 Accepted 11 December 2012

We investigated the critical load (CL) and exceedance (EX) of sulfur (S) deposition, temporal changes in soil chemistry, and Hþ budget of soils in plots dominated by Pinus banksiana (jack pine) or Populus tremuloides (trembling aspen, aspen) in two acid-sensitive watersheds to assess the risk of soil acidification by S emissions from oil sands mining in the Athabasca oil sands region (AOSR), Canada. The CLs and EXs were determined by two methods: one was based on bulk deposition and the other based on total deposition (as a sum of bulk deposition and interception deposition). The CLs ranged from 223 to 711 molc ha1 yr1 based on bulk deposition. Those values were similar to that obtained based on total deposition. However, EXs based on bulk deposition were significantly lower (p < 0.001) than those based on total deposition due to the relative increase of SO4 2 concentrations in interception deposition, indicating that EXs based on bulk deposition only could underestimate the risk of soil acidification in the AOSR. The S deposition did not exceed CLs in the long-term for both methods. The pH in the forest floor increased and available SO4 2 (as the sum of soluble and adsorbed SO4 2 ) in the forest floor and surface mineral soils increased in both jack pine and aspen stands between 2005 and 2010. The Hþ budget ranged from 289 to 130 molc ha1 yr1 in jack pine stands and from 510 to 371 molc ha1 yr1 in aspen stands. Our results suggest that 1) soils in the studied forest stands have recovered from acidification based on the increasing soil pH over time and the negative Hþ budget, and 2) the risk of soil acidification should be assessed by CL and EX calculated based on total deposition. Ó 2012 Elsevier Ltd. All rights reserved.

Keywords: Athabasca oil sands Critical load Hþ budget Interception deposition S deposition Soil acidification

1. Introduction Atmospheric emission and subsequent deposition of acid materials such as SO2 and NOx have caused changes in elemental biogeochemical cycles and soil acidification in forest ecosystems (Aber et al., 1989). Critical load (CL) has been used to estimate acceptable levels of acid deposition and to identify acid sensitive * Corresponding author. Tel.: þ1 780 492 6375; fax: þ1 780 492 1767. E-mail addresses: [email protected] (K. Jung), [email protected] (S.X. Chang), [email protected] (Y.S. Ok), [email protected] (M.A. Arshad). 1352-2310/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.atmosenv.2012.12.010

regions. The exceedance (EX) of CL allows us to determine whether the area is under acidification. However, in some studies CLs have been evaluated by a simple mass balance model (SMB) (UBA, 2004), which has a finite number of parameters for practical use. As such the calculated EX may have limited utility to indicate actual changes in soil acidity, because soil acidification involves a large number of processes where Hþ is either produced or consumed in the soil. The Hþ budget model has been used to quantify soil acidification or alkalinisation rates (e.g., Fujii et al., 2008) by evaluating various sources and sinks of Hþ. The Athabasca oil sands region (AOSR) is the largest area for open-pit oil sands mining in Alberta, Canada, and daily oil

K. Jung et al. / Atmospheric Environment 69 (2013) 56e64

production is approximately 90,000 m3. As a result, a large amount of air pollutants are released to the surrounding ecosystems and soil acidification is of concern due to chronic acid deposition (Aherne and Shaw, 2010). The emission of SO2 peaked at more than 400 Mg day1 between the 1980s and the early 1990s, and then decreased to approximately 300 Mg day1 in the mid-2000s, while NOx emissions increased gradually from 20 Mg day1 in 1970 to 300 Mg day1 in the mid-2000s (Hazewinkel et al., 2008). However, given that boreal forests are N-limited, contribution of NOx deposition to soil acidification may not be significant with N deposition similar to or lower than N uptake (Hari and Kulmala, 2008; Freer-Smith and Kennedy, 2003); N saturation was not found even after a 3-year simulated N application of 85 kg N ha1 yr1 in eastern Canada (Moore and Houle, 2009) and a 4-year simulated N application with 30 kg N ha1 yr1 (Jung and Chang, 2012) in the AOSR. Sulfur deposition, therefore, could be regarded as the main cause of soil acidification in the AOSR. Air pollutants return to the soil through two pathways: bulk deposition (BD) and interception deposition (ID). The BD occurs through gravity, while ID involves aerosols or particulate matters being intercepted by obstacles such as the tree canopy, especially through fogs, clouds, or dews, and the dissolution of them on wet surfaces. The type of tree species can influence ID, with conifer trees intercepting acid deposition more efficiently than deciduous trees due to the shape of needles and higher crown density (Augusto et al., 2002). Some studies included effects of intercepted deposition by canopy trees when assessing CLs (e.g., Craenen et al., 2000) while BD has been often used to estimate and map CLs in large areas as it is much more complicated to determine ID than BD (Draaijers and Erisman, 1995). However, ID can constitute a significant portion of the atmospheric deposition, and the chemistry of ID and BD can be very different, with the rate of SO4 2 deposition normally greater in ID than in BD (Jung et al., 2011a; Staelens et al., 2008). Therefore, using BD only can be misleading in the estimation of CLs and EXs in forest ecosystems. In addition to external inputs of Hþ and other cationic species, tree species affect soil chemistry through a number of other processes: organic acid exudation, nutrient uptake and turnover, litter fall (quality and quantity), and so on (Augusto et al., 2002; Knops et al., 2002). Such differences can cause CLs, EXs, and Hþ budgets of soils to be different between stands of different tree species under the same air quality. In this study, we assessed the risk of soil acidification by acid deposition in the AOSR based on CLs, EX, and Hþ budgets, and tested the following hypotheses: (1) EXs are underestimated using BD alone, as compared to using both BD and ID, (2) CLs are lower in coniferous stands than in deciduous stands, and (3) forest soils are being acidified by acid deposition, which is indicated by positive values of EXs and Hþ budgets of soils. 2. Materials and methods 2.1. Site description Two watersheds, NE7 and SM8, were selected for this research in the AOSR. Those watersheds are acid-sensitive due to soils that are coarse textured and have low sulfate adsorption capacity (Jung et al., 2011b). Watershed NE7 (57.15 N, 110.86 W) is located northeast of Fort McMurray, Alberta, Canada, while SM8 (56.21 N, 111.20 W) is located south of Fort McMurray. Mining areas are mostly located north of Fort McMurray, and NE7 has been exposed to more polluted air and greater acid deposition rates than SM8: BDs of SO4 2 in NE7 and SM8 were 4.1 and 3.2 kg S ha1 yr1, respectively, and those of NO3  were 2.1 and 1.8 kg N ha1 yr1, respectively (Jung et al., 2011a). Climate conditions are similar in both watersheds. The mean annual temperature was 0.7  C with

57

a mean relative humidity of about 67% between 1960 and 1990. The mean annual precipitation and evaporation were 456.4 and 486.3 mm, respectively, between 1960 and 1990 (Ok et al., 2007). Both watersheds were dominated by Pinus banksiana (jack pine) and Populus tremuloides (trembling aspen, aspen) in upland forests, and Picea mariana (black spruce) in low-lying areas and wetlands. The common soil types in the upland forests were Dystric Brunisolic soils and Gray Luvisolic soils in the Canadian system of soil classification (Soil Classification Working Group, 1998), belonging to Cryalf in US Soil Taxonomy (Soil Survey Staff, 1999). Five 20  20 m plots were established in each watershed in 2005, where three plots were jack pine dominated and the other two plots were aspen dominated. Most plots had coarse-textured sola except for aspen stands in SM8 that had fine-textured Bt horizons below sandy Ae horizons. 2.2. Sampling and analysis 2.2.1. Field sampling and measurement Soil samples were collected from 3 layers from each plot in July 2005 and then in May 2010: forest floor, 0e15 cm mineral soil (surface mineral soil), and 15e45 cm (subsurface) mineral soil. Soil samples were air-dried and crushed to pass through a 2-mm sieve. In water sampling, collectors for bulk precipitation and throughfall were installed in November 2005 to collect the first sample in May 2006, and were replaced every month during the growing season from May to October between 2006 and 2009, and in May, 2010; snow-melt water was included in samples in May from collectors set up in November (2005) or October (between 2006 and 2009) in the previous year. The collectors consisted of a 1 L bottle, a funnel (10 cm radius) with a screen (1  1 mm opening size), and a 30 cm long PVC tube covered by aluminum foil. The collectors were fixed to the soil making funnel rim height about 20 cm aboveground level. Three collectors were installed in open areas near experimental plots to collect BD in each watershed. Three throughfall collectors were placed below the canopy of dominant trees with different diameters. Two zero-tension lysimeters were installed at 45 cm soil depths at two randomly selected locations in each plot in May, 2008 to determine leaching loss; the water collection area of each lysimeter was 500 cm2. Soil solutions in zero-tension lysimeters were collected every month during the growing season from June to October in 2008, from May to October in 2009, and in May 2010. A soil moisture sensor (CS616, Campbell Scientific, U.S.) was installed at 20 cm depth in each plot in July 2005 and soil moisture content (v:v) was recorded every hour. Climate data were collected at the Muskeg station (57.13 N, 110.9 W) for NE7 and the Stony Mountain station (56.38 N, 111.23 W) for SM8 to evaluate water balance. For destructive plant sampling, four canopy trees of dominant species in a range of diameter were selected near each plot. Foliage, branch, bark, wood, and coarse roots were sampled from each selected tree. Foliar and branch samples were collected with a pole pruner, bark samples were collected at breast height (130 cm from the ground) using a chisel, and wood samples were obtained at breast height with an increment corer. In order to collect root samples, soils around the selected trees were dug out and roots were cut from the stump. Plant samples were rinsed quickly with distilled water to remove surface contamination. All plant samples were placed in the oven and dried for 72 h at 70  C. To obtain homogenous samples, they were ground to fine powder with a MM200 ball grinder. The diameter at breast height (DBH) of each tree in each plot was measured each summer from 2005 to 2009. 2.2.2. Analytical methods Soil pH was measured using 10 g of sample in 40 mL (forest floor) or 20 mL (mineral soils) of water. Available ammonium and nitrate

58

K. Jung et al. / Atmospheric Environment 69 (2013) 56e64

concentrations were determined using the indophenol blue method and the colorimetric method with vanadium, sulfanilamide, and N(1-naphthyl) ethylenediamine, respectively, after extracting soil samples with 2 mol L1 KCl at the 1:10 (w:v) ratio. Exchangeable cations including Ca2þ, Mg2þ, Kþ, and Al3þ were extracted with 1 mol L1 NH4Cl at the 1:20 (w:v) ratio. After 1 h shaking and filtration, cation concentrations in filtrates were analyzed using ICPMS (Elan 6000 quadrupole, PerkineElmer, Inc., CT). Available SO4 2 and Cl as the sum of water soluble and adsorbed forms, were extracted from 5 g of soil with 50 mL 500 mg P L1 solution made from Ca(H2PO4)2 and determined using ion chromatography (IC) (DX 600, Dionex Corp., Sunnyvale, CA). For water samples, volume, pH, and concentrations of cations nþ nþ nþ (Ca2þ, Mg2þ, Kþ, Naþ, NHþ 4 , Al , Fe , and Mn ) and anions ) were determined. Each cation concentration (SO4 2 , Cl, and NO 3 and each anion concentration were determined using ICP-MS and IC, respectively. The amount of drainage was determined with water volume collected by lysimeters and a correction factor for collection efficiency, as zero tension lysimeters underestimate soil drainage (Titus and Mahendrappa, 1996). Estimated drainage ranged from 10 to 15% of precipitation similar to those reported in other studies in western Canadian boreal forests (Blanken, 1997). Collection efficiency was calculated with a ratio of collected water to drainage by water balance between June and September:

Precipitation ¼ AET þ DS þ Drainage where AET is actual evapotranspiration and DS is a change in soil water storage. Water balance was calculated with daily climate data. Potential evapotranspiration (PET) was evaluated with the Hargreaves model (Hargreaves and Samani, 1985) and 0.32 and 0.27 of AET to PET ratios were applied for jack pine and aspen, respectively (Strickland et al., 2001; Rao et al., 2011). For plant samples, each ground sample was digested using concentrated HNO3 at 125  C for 4 h and 30% H2O2 was added to remove organic residuals for the analysis of Ca, Mg, K, Na, Al, Fe, Mn, Cl, and P on an ICP-MS. Concentrations of Cl and P in digested-plant solutions were determined with AgNO3 precipitation method and vanado-molybdo-phosphoric yellow color method, respectively. The S concentration in each ground plant sample was analyzed with an element analyzer (4010 CHNSO analyzer, Costech analytical technologies, Inc., Switzerland). 2.3. Calculation of Hþ budget, CLs, and EXs The Hþ budget was calculated considering all sources and sinks of Hþ (Marcos and Lancho, 2002):

Hþ budget ¼

X

ðSourcesÞ 

X

ðSinksÞ

þ þ þ ¼ Hþ in þ HNT þ HCat up þ HAn w   þ þ þ  Hþ loss þ HAn up þ HCat w þ HWA

where Hþin is Hþ input in throughfall deposition, HþNT is net Hþ production by N transformation, HþCat_up and HþAn_up are net Hþ consumption by uptake of cations and anions, respectively, HþCat_w, and HþAn_w are net Hþ production by weathering, adsorption, and desorption of cations and anions, respectively, Hþloss is Hþ loss through drainage, and HþWA is net Hþ consumption through protonation by weak acid anions. Annual nutrient uptake was calculated using the annual increment of tree biomass and nutrient concentration. Aboveground tree biomass was calculated with a set of DBH-based allometric equations and belowground biomass was estimated with an allometric equation based on aboveground biomass (Lambert et al., 2005; Kurz et al., 1996).

The CL of S deposition was calculated with a simple mass balance model (SMB) (UBA, 2004):

CL ¼ BCdep  Cldep þ BCw  BCup  Alkle;crit where BC is base cations as the sum of Ca2þ, Mg2þ, Kþ, and Naþ, BCdep is the atmospheric deposition of BC, Cldep is the atmospheric Cl deposition, BCw is the weathering rate of BC, BCup is net base cation uptake, and Alkle, crit is critical leaching rate of alkalinity; as N uptake was similar or greater than N deposition in the studied watersheds, we excluded terms related to N cycle to avoid overestimating CL (Freer-Smith and Kennedy, 2003). For the long-term (CL_L) and the short term (CL_S) assessments, the CL was calculated with two different methods: BD basis and total deposition (the sum of BD and ID) basis, as CL_BD and CL_BDþID, respectively. As base cations taken up by plants can return to the soil through litter fall and through the tree itself at the end of its life, BCup was regarded as minimal for CL_L. The ID was calculated using the canopy budget model, with BD and throughfall deposition (Jung et al., 2011a). The precipitation surplus (Q) was leaching water below 45 cm. The (BC:Al)crit used was 10 and BCw was based on 45 cm soil depth and was determined using the following equation (Ouimet and Duchesne, 2005):

  BCw ¼ 0:56 clay  3:72 clay2  365  Expð3600=281  3600=TÞ where T is soil temperature. Exceedance of CL (EX) was calculated as atmospheric S deposition minus CLs. 2.4. Statistical analysis Analysis of variances (ANOVA) was performed to determine the effects of watershed and tree species on measured variables, and differences in CL and EX between different methods and between time scales. Correlation analysis was performed among parameters for CLs and Hþ budgets. An a value of 0.1 was chosen to indicate statistical significance due to the high natural variability of the measured variables under field conditions. All statistical analyses were performed using version 9.01 of SAS (SAS Institute Inc, Cary, NC). 3. Results 3.1. Soil water flux Soil water content started to increase in early April and peaked between late April and early May due to water supply from melting snow (Fig. 1). On the other hand, soil water content changed sharply during torrential rains in summer season. Response of soil water content to rainfall was clear in jack pine stands but it was relatively small in aspen stands, especially in SM8. Based on the water balance model, drainage accounted for 9.8% of precipitation in jack pine stands and 15.9% in aspen stands between June and September (Table 1). The collection coefficient of zero tension lysimeters was estimated at 13.4%. 3.2. Changes in soil properties between 2005 and 2010 Most chemical properties including pH and exchangeable cations were affected by tree species and/or the watershed, while pH and available SO4 2 changed over time (Fig. 2). The pH increased with time in the forest floor (p < 0.01) but not in the surface or subsurface mineral soils. The pH of the forest floor ranged from 3.31 to 3.87 in jack pine stands, and from 3.91 to 4.89 in aspen stands in

K. Jung et al. / Atmospheric Environment 69 (2013) 56e64

59

Fig. 1. Summer precipitation and soil water content at 20 cm soil depth in jack pine (JP) and trembling aspen (TA) stands in watersheds NE7 and SM8 in Alberta, Canada.

2005, while it ranged from 3.79 to 4.04 in jack pine stands and from 4.58 to 5.18 in aspen stands in 2010. The pH in jack pine stands was lower (p < 0.001) than that in aspen stands in the forest floor but was not different in the surface and subsurface mineral soils. Available SO4 2 increased in the forest floor (p < 0.1) and surface mineral soil (p < 0.05) over time in both watersheds. However, available SO4 2 in the subsurface mineral soil significantly increased in NE7 (p < 0.05), but not in SM8. Exchangeable cations did not change over time except for Al which showed an increasing trend in the surface and subsurface mineral soils (p < 0.05). 3.3. Sources and sinks of Hþ 3.3.1. Atmospheric deposition, throughfall, and leaching loss The annual BD of SO4 2 and base cations were greater (p < 0.05 for both) in NE7 than in SM8 (Fig. 3b). The annual ID for SO4 2 and base cations were greater (p < 0.05) in NE7 than in SM8 in jack pine stands, whereas no difference was found between watersheds in aspen stands (Fig. 3b). In addition, ID of SO4 2 and base cations were greater (p < 0.05 and p < 0.1, respectively) in jack pine than in aspen stands in NE7 but not in SM8. The Hþ input by throughfall in jack pine and aspen stands were 152 and 51 molc ha1 yr1, respectively, in NE7, and 203 and 35 molc ha1 yr1, respectively, in SM8 (Table 2). The leaching loss of Hþ was not different between watersheds or dominant tree species while it accounted for 17 and 120% of throughfall deposition in jack pine and aspen stands, respectively (Table 2). 3.3.2. Nutrient uptake Tree biomass increment was greater (p < 0.01) in SM8 than in NE7 (Table 3). Uptake of Ca, Mg, K, and S were significantly

influenced by tree species (p < 0.05) as well as watershed (p < 0.05). Net Hþ production by fluxes of cation uptake by plants was positive in all plots and was greater (p < 0.05) in SM8 than in NE7, and greater (p < 0.01) in aspen than in jack pine stands (Fig. 4). Net Hþ production by assimilation had a positive correlation with annual biomass increment (r ¼ 0.89 and p < 0.01 in aspen stands and r ¼ 0.94 and p < 0.01 in jack pine stands). 3.3.3. Weathering and adsorption The base cation weathering rate was smaller (p < 0.05) in NE7 than in SM8 but was not different between dominant tree species (Fig. 3b). The greater supply of base cations through weathering in SM8 implied greater Hþ consumption by cation weathering and adsorption in SM8 (p < 0.01) than in NE7 (Fig. 4). Net Hþ consumption by cation weathering and adsorption was also affected by tree species (p < 0.01). Net Hþ production by anion weathering and adsorption also differed between watersheds and dominant tree species (Fig. 4). It was more negative (p < 0.01) in jack pine than in aspen stands and more negative (p < 0.01) in NE7 than in SM8 (Fig. 4). 3.3.4. Nitrogen transformation Throughfall depositions of NO3  and NH4 þ did not differ between watersheds and dominant tree species (Table 2). The leaching loss of NO3  and NH4 þ was minimal and was not influenced by watershed or stand type. Net Hþ production by N transformation was positive in both watersheds and dominant tree species. 3.3.5. Protonation of weak acid anions Throughfall deposition of weak acid anions was greater (p < 0.001) in aspen than in jack pine stands, and greater

0 0 23.6 0 e 4.5 24.9 0 0 e

5.7 0.3 0.9 e e 1.4

Dr_WB

DS

41.3 4.8 36.5 10.3 e 3.4 14.2 1.6 5.4 e

AET

0 0 26.1 0 e 0 5.4 0 0 e 57.9 10.4 22.4 3.9 e 6 9 14.1 12.5 e

e e 3.7 e 1.9 e 0.1 e e 0.3

84.4 80 60.9 33.3 e 73.1 75.1 65.9 37.3 e

3.3.6. Hþ budget In all plots, the estimated Hþ budgets were negative, indicating that soils in the two studied watersheds were being alkalinized rather than acidified (Fig. 4). The Hþ budget was more negative (p < 0.001) in the aspen stands than in jack pine stands, while no significant difference was found between watersheds. The Hþ budget was positively related to Hþ input (r ¼ 0.82 and p < 0.01), and was negatively related to protonation by weak acid anion (r ¼ 0.73 and p < 0.01). However, net Hþ production by uptake showed a negative relationship with Hþ budget (r ¼ 0.64 and p < 0.05). 3.4. Critical loads and exceedances

1.9

PP, AET, and DS mean precipitation, actual evapotranspiration, and a change in soil water storage, respectively. 4,5 Dr_WB and Dr_Lys mean drainage estimated with water balance and drainage collected with lysimetry, respectively.

2010

2009

June July August September May June July August September May 2008

1,2,3

8.2

0.3 5.1

43.1 84.8 121 43.6 e 81 85.8 64.3 31.9 e e e 5.5

0 0 50.8 0 e 32.3 0 38.2 0 e 44.2 31.2 12.9 12.4 e 17.7 48.6 16.2 35.2 e 91.8 89.3 68.7 41 e 86.8 90.6 67.9 46.1 e e 0.2 2.2 e 3.9 5.5 1.8 7.4 e 1.1 0 0 26.1 0 e 20.8 0 28.7 0 e 57.9 17.9 27.4 18.5 e 19.2 62.2 16.9 42.1 e 105.5 102.6 78.9 47.1 e 99.8 104.2 78.1 53 e

TA

(p < 0.001) in SM8 than in NE7 (Table 2). However, the leaching loss of weak acid anions was not influenced by watershed or the dominant tree species. As a result, reduction of Hþ by protonation of weak acid anions was greater (p < 0.05) in aspen than in jack pine stands, and greater (p < 0.05) in SM8 than in NE7 (Fig. 4). Protonation of weak acid anions in jack pine and aspen stands was 376 and 440 molc ha1 yr1, respectively, in NE7, and 405 and 543 molc ha1 yr1, respectively, in SM8.

100.5 95.2 72.6 39.7 e 87 89.4 78.4 44.4 e

Dr_WB

DS

47.6 120.5 132.4 28.6 e 101.4 42 89.9 10.9 e

JP

AET

PP Dr_4WB AET2

DS3

Dr_5Lys

AET

DS

Dr_WB

Dr_Lys

SM8

JP PP

1

NE7 Month Year

Table 1 Water balance in jack pine (JP) and trembling aspen (TA) stands in watersheds NE7 and SM8 in Alberta, Canada. The unit is mm month1.

Dr_Lys

TA

Dr_Lys

K. Jung et al. / Atmospheric Environment 69 (2013) 56e64

e e 4.4

60

In the long-term, CLs were not affected by watershed or tree species for both models (Fig. 3a). The CL_L_BD ranged from 223 to 711 molc ha1 yr1 and CL_L_BDþID showed similar values with CL_L_BD. The EX_L did not occur in most plots, indicating that S deposition was less than CL_L during the study period (Fig. 3a). However, EX_L_BDþID was less negative (p < 0.001) than EX_L_BD, due to a relatively high proportion of SO4 2 in ID. EX_L_BDþID was less negative (p < 0.05) in NE7 than in SM8 while no watershed effect was found on EX_L_BD. Tree species did not affect EX_L. On average, EX_L_BD was 222 molc ha1 yr1 in NE7 and 334 molc ha1 yr1 in SM8, and EX_BDþID was 81 molc ha1 yr1 in NE7 and 264 molc ha1 yr1 in SM8. The CLs were lower in the short-term than in the long-term scale due to the influence of BCup (Fig. 3a). The CL_S were influenced by tree species (p < 0.1) and were lower in aspen than in jack pine stands due to greater BCup in the former. The watershed did not have any influence on CL_S. The CL_S_BD were, on average, 260 molc ha1 yr1 in jack pine and 59 molc ha1 yr1 in aspen stands. The CL_S_BDþID were 256 molc ha1 yr1 in jack pine and 45 molc ha1 yr1 in aspen stands. In both watersheds, the average EX_S_BD was negative in jack pine stands but positive in aspen stands (Fig. 3a). The EX_S_BDþID was more positive or less negative than EX_S_BD. The EX_S_BDþID in jack pine and aspen stands were 65 and 205 molc ha1 yr1, respectively, in NE7 and 22 and 99 molc ha1 yr1, respectively, in SM8. 4. Discussion 4.1. Interception deposition and critical loads Differences between CL_BD and CL_BDþID ranged from 2 to 25 molc ha1 yr1 in this study as the proportions of base cations and Cl were similar between BD and ID (Fig. 3). However, EX_BDþID were much greater than EX_BD (Fig. 3) due to increasing proportions of SO4 2 in ID, indicating that the risk of acidification by S deposition would be underestimated in forest ecosystems with the conventional method using BD only. The ID of tree canopies has been often excluded in estimations of CL in large-scale studies (e.g., Sullivan et al., 2011), even though ID accounts for a significant portion of atmospheric deposition in forest ecosystems. Sulfate deposition has been found to be similar between the forest edge and the forest interior due to SO2 being transported as aerosol,

K. Jung et al. / Atmospheric Environment 69 (2013) 56e64

61

Fig. 2. Soil chemistry of forest floor (FF), surface (SS, 0e15 cm) and subsurface (SSS, 15e45 cm) mineral soils in jack pine (JP) and trembling aspen (TA) stands in watersheds NE7 and SM8 in Alberta, Canada. Error bars are standard errors of the mean.

Fig. 3. Critical loads and exceedances (a) and parameters of critical loads (b) in jack pine (JP) and trembling aspen (TA) stands in watersheds NE7 and SM8 in Alberta, Canada. BD, ID, BC_w, and BC_up represent bulk deposition, interception deposition, base cation weathering, and base cation uptake, respectively. Error bars are standard errors of the mean.

62

Table 2 Throughfall deposition (TF) and leaching loss (LL) of elements in jack pine (JP) and trembling aspen (TA) stands in watersheds NE7 and SM8 in Alberta, Canada. Numbers in parentheses are standard error of the mean. Water type

Water-shed

Tree species

Hþ (molc ha1 yr1)

NH4 þ (molc ha1 yr1)

Ca2þ (molc ha1 yr1)

Mg2þ (molc ha1 yr1)

Kþ (molc ha1 yr1)

Naþ (molc ha1 yr1)

Alnþ (molc ha1 yr1)

Fenþ (molc ha1 yr1)

Mn4þ (molc ha1 yr1)

SO4 2 (molc ha1 yr1)

NO3  (molc ha1 yr1)

Cl (molc ha1 yr1)

WAa (molc ha1 yr1)

TF

NE7

JP TA JP TA JP TA JP TA

151.5 51.5 202.9 35.3 19.9 56.3 42.8 46.5

89.3 68.1 59.4 74.8 0.8 0.8 0.3 0.9

225.2 246.5 144.1 193.9 3.7 4.1 3.2 5.2

96.9 112.0 74.2 124.4 1.8 2.0 1.5 2.8

173.7 283.1 117.6 329.2 5.1 3.5 2.7 4.4

55.0 45.0 44.3 50.3 8.9 10.0 3.8 5.5

13.8 9.2 16.7 6.3 2.0 3.1 2.1 3.2

4.6 3.2 3.5 2.5 0.5 0.8 0.5 0.8

4.6 3.8 10.9 13.6 0.0 0.0 0.0 0.1

298.0 237.1 170.8 157.5 3.2 3.5 1.0 3.2

78.3 85.5 57.1 71.5 0.3 0.3 0.1 0.4

54.4 42.1 32.0 45.5 2.0 1.9 4.9 15.0

383.8 457.7 413.6 555.9 16.5 18.0 5.3 3.0

SM8 LL

NE7 SM8

(10.8) (7.5) (16.0) (9.8) (1.1) (0.8) (0.2) (0.5)

(21.2) (14.7) (31.7) (17.0) (4.4) (1.0) (0.1) (1.3)

(10.8) (7.5) (13.8) (6.8) (1.8) (0.7) (0.1) (0.5)

(45.2) (23.8) (31.4) (10.7) (4.1) (1.4) (0.2) (1.7)

(4.5) (6.1) (6.7) (3.4) (10.4) (10.5) (4.1) (3.1)

(1.9) (1.1) (0.9) (2.3) (2.0) (0.6) (0.5) (1.5)

(1.0) (0.6) (0.9) (0.4) (0.5) (0.2) (0.1) (0.4)

(0.7) (0.9) (1.4) (0.7) (0.0) (0.0) (0.0) (0.0)

(24.5) (24.7) (10.3) (11.7) (4.8) (0.2) (0.5) (1.5)

(15.1) (9.5) (6.9) (11.8) (0.5) (0.4) (0.0) (0.3)

(4.8) (5.3) (6.3) (12.1) (1.9) (0.5) (2.5) (16.7)

(52.9) (41.5) (48.5) (38.2) (14.5) (14.6) (4.9) (13.8) K. Jung et al. / Atmospheric Environment 69 (2013) 56e64

a

(21.2) (14.7) (9.2) (41.0) (29.3) (13.9) (57.0) (62.6)

WA means weak acid anions.

Table 3 Annual biomass increment and nutrient uptake of jack pine (JP) and trembling aspen (TA) stands in watersheds NE7 and SM8 in Alberta, Canada. Numbers in parentheses are standard error of the mean. Nutrient uptakea

Water-shed Tree species Biomass increment Total Above-ground Root (kg ha1) (kg ha1) (kg ha1) NE7 SM8

JP TA JP TA

466 383 919 1622

(27.1) (116) (288) (168)

124 108 228 259

(6.4) (5) (52) (15)

590 491 1147 1881

Ca (molc ha1 yr1)

(30.3) 49.1 (7.2) (121) 162.8 (70.1) (339) 73.4 (12.7) (153) 341.2 (106.6)

Mg (molc ha1 yr1)

K Na Al Fe Mn S (molc (molc (molc (molc (molc (molc 1 1 1 1 1 1 1 1 1 1 ha yr ) ha yr ) ha yr ) ha yr ) ha yr ) ha1 yr1)

13.8 32.0 28.0 80.2

12.9 24.5 26.4 70.2

(2.0) (13.4) (6.4) (10.6)

(0.4) (5.6) (7.7) (9.9)

3.5 2.6 10.7 19.8

(0.9) (0.4) (5.8) (4.8)

5.7 2.5 14.7 9.8

(2.3) (0.8) (3.7) (1.2)

2.9 3.3 10.6 9.5

(0.5) (1.4) (2.1) (1.4)

2.1 0.6 5.8 4.1

(0.5) (0.2) (1.5) (1.5)

7.5 18.2 13.4 40.3

1

Cl P N kg ha (molc (molc 1 1 1 1 ha yr ) ha yr )

(0.8) 4.8 (0.6) (6.8) 7.7 (0.8) (2.7) 13.5 (7.8) (10.8) 20.1 (1.1)

6.2 9.7 15.2 24.8

(0.8) (2.7) (6.4) (0.2)

2.6 2.0 5.4 8.0

(0.6) (0.3) (1.2) (0.9)

Net Hþ production (molc ha1)

71.5 193 128 450

(8.7) (80.8) (20.7) (123)

a Nutrient uptake was presented as the charge equivalent unit to evaluate net Hþ production by assimilation except for N: the charges used were 2 for Ca and Mg, 1 for K and Na, 3 for Al and Fe, 4 for Mn, 2 for S as SO4 2 , 1 for Cl, and 3 for P as PO4 3 .

K. Jung et al. / Atmospheric Environment 69 (2013) 56e64

63

Fig. 4. Budgets, sinks, and sources of Hþ of soils in jack pine (JP) and trembling aspen (TA) stands in watersheds NE7 and SM8 in Alberta, Canada. NT, Cat_up, An_up, Cat_w, An_w, and WA represent net Hþ production by N transformation, uptake of cations and anions, weathering and adsorptionedesorption of cations and anions, and protonation of weak acid anions. Error bars are standard errors of the mean.

while base cations and Cl moving as particulate matters are significantly intercepted in the open field/forest border, causing the so called forest edge effect (Devlaeminck et al., 2005). Reduced particulate matters with base cations and Cl can increase the proportion of SO4 2 in ID in the forest interior. The ID was similar to BD for base cations, and was more than twice that of BD for SO4 2 in Pseudotsuga menziesii stands in the Netherlands (Draaijers and Erisman, 1995) and similar trends were found in Fagus sylvatica L. stands in Belgium (Staelens et al., 2008). The IDs of SO4 2 in this study showed similar trends. Intercepted SO4 2 accounted for 62 and 58% of total deposition in jack pine and aspen stands, respectively, while that of base cations was responsible for approximately 32% of total deposition in both stand types. As NOx is also transported as an aerosol like SO2, N deposition is also increased by canopy interception (Malek, 2010). Therefore, we conclude that ID should be included at assessing CL in the AOSR, even in studies for a large area, even though obtaining data on the spatial variation of ID can be complex. 4.2. Assessment of tree species effects on soil acidification Trees contribute to soil acidification through a number of processes such as interception of acid materials (Jung et al., 2011a) and organic acid exudation (Tuason and Arocena, 2009). Excess uptake of cationic compared to anionic nutrients has also been suggested to increase soil acidity (Fujii et al., 2008) and can be a major source of Hþ in unpolluted or less polluted areas (Marcos and Lancho, 2002). In this study, BCup was greater in aspen than in jack pine stands, which led to lower CL_S and greater EX_S in aspen stands (Fig. 3). Due to the greater concentration of base cations in deciduous trees than in conifers (Frelich et al., 1989), CL with harvest removal of base cations has been estimated to be lower in deciduous than in coniferous stands with similar stand biomass (Freer-Smith and Kennedy, 2003). Therefore, deciduous stands in the AOSR, based on the CL data, could be more sensitive to acidification caused by acid deposition than conifer stands if harvest would happen. On the other hand, the Hþ budget of the soil was less negative in jack pine than in aspen stands, even though assimilation provided greater net Hþ production in aspen than in jack pine stands (Fig. 4). This result was caused by greater Hþ input from throughfall due to canopy leaching of organic acids and lower protonation by weak acid anions in jack pine stands (Fig. 4). The Hþ budget of jack pine stands was about 200 molc ha1 yr1 higher

than that of aspen stands with similar acid deposition, which was as much as 3.2 kg S ha1 yr1 of S deposition; BDs of S were 4.1 and 3.2 kg S ha1 yr1 in NE7 and SM8, respectively (Jung et al., 2011a). This implies that Hþ budget could explain the effect of trees for which the simple CL concept does not properly deal with. 4.3. Risk of soil acidification in AOSR Atmospheric deposition of SO4 2 and NO3  in NE7 and SM8 were moderately low compared with those greater than 10 kg ha1 yr1 each for SO4 2 and NO3  in areas affected by air pollution in eastern North America (Vet et al., 2004), the western and central parts of Europe (Lorenz et al., 2008), and eastern Asia (Fujii et al., 2008). The CLs and EXs of forests have been mapped using long-term data using BD only in Alberta, in which most forest ecosystems have been exposed to S and N deposition lower than CLs (Aherne, 2008), suggesting that forest soils are not being acidified in the AOSR under the current level of acid deposition. Furthermore, soil pH in the forest floor increased during the study period, which is consistent with the negative Hþ budget calculated in this study, implying significantly reduced Hþ supply and/or increased supply of base cations in the soil; the forest floor is relatively sensitive to environmental changes such as acid deposition, as compared with mineral soils (Jung and Chang, 2012). However, we could not conclude that forest soils in the AOSR have never been affected by acid deposition. Two scenarios can be suggested. One is that forest ecosystems in the AOSR have never experienced soil acidification due to rates of acid deposition that were lower than CLs, and the other is that the forest ecosystems are recovering from previous acidification. The emission of SO2, the dominant air pollutant in the AOSR, reached its zenith between the early 1980s and mid-1990s, and then decreased due to installation of flue gas desulfurisation in spite of the gradual increase of fuel consumption that would have increased the emission of NOx and particulate matter containing high base cations concentrations in the same periods (Hazewinkel et al., 2008). This implies that the negative Hþ budget in this study could have resulted from decreased Hþ input due to decreased S deposition and increased particulate matter deposition, supporting the latter scenario. Increasing pH in the forest floor have been also reported to be an early indicator of recovery with decreased acid deposition in North America (Lawrence et al., 2012) and Europe (Karlsson et al., 2011). Meanwhile, based on expectation that synthetic oil production and

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subsequently acid emissions will increase in the AOSR, soil acidification in the AOSR is still of concern, although no sign of soil acidification was found in this study. 5. Conclusions The exceedance of S deposition was underestimated based on the calculation of BD only compared to that based on total deposition, because of a greater proportion of SO4 2 in ID than in BD. Therefore, the conventional method of using EX_BD that excludes ID might underestimate the risk of soil acidification by S deposition in the AOSR. The CL_L was not affected by tree species, while CL_S was influenced by tree species showing lower CL_S in aspen stands caused by greater net assimilation rates of base cations in aspen stands. Due to greater Hþ input by canopy leaching of organic acids and lower net Hþ consumption by protonation by weak acid anions, jack pine stands had a less negative Hþ budget than aspen stands, even though net Hþ production by assimilation was greater in aspen stands. Based on our results of increased soil pH, negative EX and negative Hþ budget, we showed that soils had been recovering from previous acidification in the AOSR associated with the decreasing S emission in the late 1990s. However, further research should be conducted to evaluate the effect of acid deposition on forest soils, due to the expected increase in synthetic oil production and subsequent acid emission and deposition in the future. Acknowledgments This study was carried out under the framework and financial support of the Cumulative Environmental Management Association, and received support from Alberta Environment and the Natural Sciences and Engineering Research Council of Canada. References Aber, J.D., Nadelhoffer, K.J., Steudler, P., Melillo, T.M., 1989. Nitrogen saturation in northern forest ecosystems. Bioscience 39, 378e386. Aherne, J., Shaw, D.P., 2010. Impacts of sulphur and nitrogen deposition in western Canada. Journal of Limnology 69, 1e3. Aherne, J., 2008. Calculating Critical Loads of Acid Deposition for Forest Soils in Alberta: Critical Load, Exceedance and Limitations. Canadian Council of Ministers of the Environment. Augusto, L., Ranger, J., Binkley, D., Rothe, A., 2002. Impact of several common tree species of European temperate forests on soil fertility. Annals of Forest Science 59, 233e253. Blanken, P.D., 1997. Evaporation Within and Above a Boreal Aspen Forest. Ph.D. thesis, The University of British Columbia, Vancouver. Craenen, H., Ranst, E.V., Tack, F.M.G., Verloo, M.G., 2000. Calculation and mapping of critical loads of sulfur and nitrogen in Flanders, Belgium. Science of the Total Environment 254, 55e64. Devlaeminck, R., De Schrijver, A., Hermy, M., 2005. Variation in throughfall deposition across a deciduous beech (Fagus sylvatica L.) forest edge in Flanders. Science of the Total Environment 337, 241e252. Draaijers, G.P.J., Erisman, J.W., 1995. A canopy budget model to assess atmospheric deposition from throughfall measurements. Water, Air, & Soil Pollution 85, 2253e2258. Freer-Smith, P.H., Kennedy, F., 2003. Base cation removal in harvesting and biological limit terms for use in the simple mass balance equation to calculate critical loads for forest soils. Water, Air, & Soil Pollution 145, 409e427. Frelich, L.E., Bockheim, J.G., Leide, J.E., 1989. Historical trends in tree-ring growth and chemistry across an air-quality gradient in Wisconsin. Canadian Journal of Forest Research 19, 113e121. Fujii, K., Funakawa, S., Hayakawa, C., Kosaki, T., 2008. Contribution of different proton sources to pedogenetic soil acidification in forested ecosystems in Japan. Geoderma 144, 478e490.

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