Nitrogendeposition pathway

The magnitude of terrestrial N deposition largely depends on the height of vegetation, for example forests may receive a two- to three-fold higher N

deposition than shorter vegetation types such as grasslands (Fowler et al, 2004) and the proximity of the ecosystem to the pollutant source, for example being in the vicinity of a poultry farm (Skiba et al, 2006). In regions with intensive agriculture, reduced N compounds dominate N deposition, whereas in areas unaffected by agricultural activities oxidized N compounds, originating mainly from combustion processes (industry, vehicles; see Chapter 9), are the most important. An example is the Hoglwald Forest in southern Bavaria, situated in a landscape with intermixed forest and agricultural areas, where the NH3-to-NO3- ratio in the throughfall is 2:1, while N deposition, depending on forest type, is in the range of 20-35kg N ha-1 yr-1 (Kreutzer and Weis, 1998). N input of such a magnitude significantly exceeds the N demand of a growing forest, which is approximately 5-10kg N ha-1 yr-1 (Scarascia-Mugnozza et al, 2000). Thus N deposition leads to increased N availability in the soil-plant system, reflected by, for example, a narrowing of the C:N ratio of the litter, forest floor or mineral soil and increased concentrations of nitrate and ammonium in the soil solution (Kristensen et al, 2004; Mannig et al, 2008). Several studies show that N deposition and N2O, as well as NO emissions, from forest soils are positively correlated (for example Brumme and Beese, 1992; Brumme et al, 1999; Papen and Butterbach-Bahl, 1999; van Dijk and Duyzer, 1999; Butterbach-Bahl et al, 2002a, 2002b; Pilegaard et al, 2006; Skiba et al, 2006) and that the observed stimulation of fluxes may mainly be attributed to the increased availability of N (as NH4+ and NO3-) for the microbial processes of nitrification and denitrification (Rennenberg et al, 1998; Corre et al, 1999), i.e. the key microbial processes responsible for N trace-gas production in soils (see Chapter 2). In a study involving microbial process studies along an N-enrichment gradient, Corre et al (2007) demonstrated that gross N mineralization, NH4+ immobilization, gross nitrification and NO3- immobilization rates increased up to intermediate N-enrichment levels and somewhat decreased in highly N-enriched conditions. With regard to N trace-gas emissions the authors concluded that decreasing turnover rates of the NO3- pool, due to a slowdown of microbial nitrate immobilization, may be the reason for increased gaseous emissions as well as increased nitrate leaching.

A possible further explanation for increased N2O emissions due to ecosystem N enrichment was recently provided by Conen and Neftel (2007). They speculated that increased N availability may have reduced N2O reduction in soils via denitrification, i.e. that the ratio of N2O to N2 increases with increasing N availability. Since increased N deposition also affects nitrate N leaching and runoff (Dise et al, 1998; Borken and Matzner, 2004), one also needs to consider indirect N2O emissions from water bodies due to N deposition to natural systems. However, a thorough evaluation and quantification of N-deposition effects on soil N trace-gas emissions also remains difficult, since environmental conditions such as meteorology or soil and plant properties do significantly affect the magnitude, temporal course and composition of the emitted N gases (NO/N2O/N2) (for example Figures 8.3 and 8.4).

Figure 8.3 Soil N2O and NO fluxes (±standard error (SE)) at two directly adjacent beech and spruce sites of the Höglwald Forest in the years 2002 and 2003

Note: Fluxes are daily mean values of sub-daily observations for five different chambers per site and trace gas as measured with automated measuring systems. The lower panel shows simultaneous observed temporal variations in forest floor temperature and moisture at the spruce site. Noteworthy are the pronounced differences in N2O and NO emissions between both sites, i.e. with NO emissions dominating at the spruce site and with N2O and NO emissions being balanced at the beech site. These differences in N trace-gas emissions are mainly due to differences in atmospheric N deposition and effects of tree species on soil hydrological and chemical properties. For further details see Papen and Butterbach-Bahl (1999) and Pilegaard et al (2006). Source: Butterbach-Bahl et al (1997)

Having these difficulties in mind, there have been several attempts to estimate the stimulating effect of N deposition on N2O emissions from forest soils. Skiba et al (2006) used a gradient approach, with measuring sites being located at increasing distances from a poultry farm, i.e. a strong NH3 source. They estimated that >3 per cent of the N deposited to the woodland sites was released as N2O. Butterbach-Bahl et al (1998) used a regression-type approach, time

Figure 8.4 Effect of changes in soil moisture on the ratio of N2O to NO

Note:The figure is based on daily mean N2O and NO fluxes at the spruce site in the Höglwald Forest (see Plate 8.1) and time domain reflectometry (TDR) measurements of volumetric moisture in the forest floor. At all water contents NO is the dominant N trace gas emitted. However, at volumetric water contents >30 per cent (approximately >65 per cent WFPS), N2O emissions increase exponentially at the cost of NO. Source: Butterbach-Bahl et al (1997)

Forest floor moisture [Vol%]

Figure 8.4 Effect of changes in soil moisture on the ratio of N2O to NO

Note:The figure is based on daily mean N2O and NO fluxes at the spruce site in the Höglwald Forest (see Plate 8.1) and time domain reflectometry (TDR) measurements of volumetric moisture in the forest floor. At all water contents NO is the dominant N trace gas emitted. However, at volumetric water contents >30 per cent (approximately >65 per cent WFPS), N2O emissions increase exponentially at the cost of NO. Source: Butterbach-Bahl et al (1997)

series of nitrogen deposition throughfall data, and continuous N2O and NO emission measurements (Figure 8.3; Plate 8.1) at the long-term monitoring site at Höglwald Forest for estimating N-deposition-driven N2O losses. Their estimate is comparable to that in the study by Skiba et al (2006), i.e. 1.4 per cent for coniferous forests and 5.4 per cent for deciduous forest. Also, a literature review by Denier van der Gon and Bleeker (2005) showed that N deposition to forests stimulates N2O emissions within the same range; they concluded that the stimulating effect was higher for deciduous forests (5.7 per cent of deposited N being lost as N2O) than for coniferous forests (3.7 per cent).

This marked forest-type effect (Figure 8.3 and Table 8.3) may be due to differences in canopy structure and resulting effects on soil moisture, and in acidity of the forest floor, as well as differences in soil C storage and distribution, which favour nitrification rather than denitrification activity in the soils of coniferous forests as compared to soils of deciduous forests (Butterbach-Bahl et al, 2002a; Pilegaard et al, 2006; de Vries et al, 2007). In a scenario-type study at the European Union scale, Kesik et al (2005) estimated N deposition effects on forest soil N2O emissions by running the biogeochemical model Forest-DNDC either with actual values of atmospheric N deposition or by assuming that N deposition was zero. The results showed that across Europe 1.8 per cent of atmospheric N deposition was returned to the atmosphere as N2O. All published estimates, therefore, show that the default N2O EF of 1 per cent used by IPCC for indirect emissions from soils following N deposition (Mosier et al, 1998; IPCC, 2006) is most likely too low by at least a factor of two.

Table 8.3 Summary of published N2O emission data for deciduous forests and coniferous forests and derived emission factor as a function of N input

Number of

N2O emission

Emission

observationsa

(kg N ha-1 yr1)

factor1

Reference(s)

Deciduous forest

3

0.49

0.023

Ambus et al (2001); Beier et al (2001)

1

0.23

0.023

Bowden et al (2000)

8

1.67

0.053

Brumme etal (1999)

2

2.98

0.111

Butterbach-Bahl etal (2002b)

1

1.45

0.072

Butterbach-Bahl etal (1997)

2

0.02

0.001

Corre et al (1999)

2

2.65

0.044

Mogge etal (1998)

1

0.20

0.013

Oura etal (2001)

2

4.44

0.222

Papen and Butterbach-Bahl (1999)

6

0.65

0.035

Skiba etal (1998)

3

4.03

0.115

Zechmeister-Boltenstern et al (2002)

Indicative averagec

0.065

Coniferous forest

3

0.31

0.016

Borken et al (2002)

4

0.58

0.034

Brumme etal (1999)

2

0.70

0.020

Butterbach-Bahl etal (2002b)

4

1.59

0.073

Butterbach-Bahl etal (1997)

6

0.11

0.005

4

0.36

0.005

2

0.39

0.013

2

3.20

0.032

6

0.85

0.028

Papen and Butterbach-Bahl (1999)

14

0.37

0.016

Skiba etal (1998,1999)

Indicative averagec

0.024

Note:a 'Number of observations' (n) counts separately the different years of each study and the various plots with different N treatments and/or tree species within the class 'deciduous forest' or 'coniferous forest'; thus for example for an experiment in which a beech plot and an alder plot were each monitored for two consecutive years, n = 4. bThe EF (i.e. the fraction of N input that is emitted as N2O) is calculated for individual plots on the original data for N2O emission and N input, and then averaged. cThe average EF presented here is only indicative, as it is not corrected for the number of observations or N input levels, and weights each location and/or study equally. Source: Based on Denier van der Gon and Bleeker (2005)

Note:a 'Number of observations' (n) counts separately the different years of each study and the various plots with different N treatments and/or tree species within the class 'deciduous forest' or 'coniferous forest'; thus for example for an experiment in which a beech plot and an alder plot were each monitored for two consecutive years, n = 4. bThe EF (i.e. the fraction of N input that is emitted as N2O) is calculated for individual plots on the original data for N2O emission and N input, and then averaged. cThe average EF presented here is only indicative, as it is not corrected for the number of observations or N input levels, and weights each location and/or study equally. Source: Based on Denier van der Gon and Bleeker (2005)

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