Download Atmospheric Ammonia: Detecting emission changes and environmental impacts PDF

TitleAtmospheric Ammonia: Detecting emission changes and environmental impacts
Author
LanguageEnglish
File Size18.8 MB
Total Pages468
Table of Contents
                            Sutton_FM.pdf
Sutton_Ch01.pdf
Sutton_Ch02.pdf
Sutton_Ch03.pdf
Sutton_Ch04.pdf
Sutton_Ch05.pdf
Sutton_Ch06.pdf
Sutton_Ch07.pdf
Sutton_Ch08.pdf
Sutton_Ch09.pdf
Sutton_Ch10.pdf
Sutton_Ch11.pdf
Sutton_Ch12.pdf
Sutton_Ch13.pdf
Sutton_Ch14.pdf
Sutton_Ch15.pdf
Sutton_Ch16.pdf
Sutton_Ch17.pdf
Sutton_Ch18.pdf
Sutton_Ch19.pdf
Sutton_Ch20.pdf
Sutton_Ch21.pdf
Sutton_Ch22.pdf
Sutton_Ch23.pdf
Sutton_Ch24.pdf
Sutton_Ch25.pdf
Sutton_Ch26.pdf
Sutton_Ch27.pdf
Sutton_Ch28.pdf
Sutton_Author Index.pdf
Sutton_Subject Index.pdf
                        
Document Text Contents
Page 2

Atmospheric Ammonia

Page 234

15 Ammonia Deposition Near Hot Spots 221

where R
wmin

ranges between 2 and 20 and b
Rw

is of the order of 6–12. It should be
noted however, that cuticular deposition to “wet surfaces” may also occur without
apparent dew (Duyzer et al. 1992; Sutton et al. 1992; Wyers and Erisman 1998),
which might be due to the presence of wet films at the leaf surface created by
the conjunction of stomatal evaporation and the presence of hygroscopic aero-
sols deposited preferentially near the stomates (Burkhardt and Eiden 1994). The
empirical parametrization of Eq. [15.6] incorporates the effect of hygroscopy, but
does not distinguish any dependence of R

w
on R

s
. Smith R.I. et al. (2000) gives

an alternative empirical expression of both temperature and relative humidity.
Nemitz et al. (2001) included the dependence of R

w
on the SO

2
/NH

3
concentra-

tion ratio.
It should be recognized that the parametrization of R

w
is, however, a steady state

simplification of a dynamic bi-directional exchange of NH
3
with leaf cuticles. An

initial dynamic model of this effect was provided by Sutton et al. (1995a, 1998a).
A simplification of that model was that the leaf surface pH needed to be speci-
fied. Fléchard et al. (1999) advanced this substantially, by developing a model that
simulated leaf surface pH in response to wet and dry deposition processes and
derived bi-directional cuticular exchange using a dynamical model that takes into
account the uptake of different soluble pollutants their chemistry in the water layer
on the leaf. In these models, the steady state value of R

w
is effectively replaced by a

capacitance of the leaf surface, a capacitance charge, with exchange limited by an
adsorption/desorption resistance (R

d
).

Near sources, cuticular deposition is likely to be very high in humid climate
due to large NH

3
concentrations. Throughfall measurements near intensive source

which are reported in the literature may be indicative of cuticular deposition,
although they might be subject to uncertainties due to dry deposition onto collectors,
flooding under high rain events, or biochemical transformations of NH

x
deposited

onto leaves (Theobald et al. 2001; Dämmgen et al. 2005; Erisman et al. 2005).
Theobald et al. (2001) report throughfall ranging 3% and 4% of the NH

3
emitted

by a source releasing between 500 and 2,800 kg N-NH
3
year−1. It should be noted

that at very high concentrations the value of R
w
tends to increase, due to a partial

saturation of the leaf surface sink. The presence of SO
2
will increase the dry depo-

sition of NH
3
. For that reason, R

w
is sometimes modeled as a function of the ratio

NH
3
/SO

2
(Nemitz et al. 2001), or by empirical approaches based on observational

data (Pitcairn et al. 2004).

15.5.2.4 Two Layer Exchange Model

A two-layer resistance scheme (Fig. 15.4d, Nemitz et al. 2001, see Appendix 2 for
detailed equations) takes into account the ground level source which can either be
an emission from a fertilizer or from decomposing leaf litter (Denmead et al. 1976;
Sutton et al. 1993c; Nemitz et al. 2000a). Moreover, the two-layer model allows
reproducing the absorption by leaves of a fraction emitted from the ground (Nemitz
et al. 2001). The soil or litter compensation point may be very large, especially in

Page 235

222 B. Loubet et al.

nitrogen rich litter (Husted et al. 2000; Nemitz et al. 2001; Sutton et al. 2001a),
where G can reach more than 100,000 (Sutton et al. 2006). The two-layer models
have shown to be very useful in modelling the effect of the canopy structure one
NH

3
exchange with the atmosphere (Personne et al. 2008).

15.6 Deposition of Particulate Ammonium

The dry deposition of particles to the ground can be represented by the scheme of
Fig. 15.4a, but with R

c
= 0, and with a parallel pathway correspond to a resistance

inverse to the settling velocity of the particle V
s
. The computed deposition velocity

for particles becomes simply (Slinn 1982; Zhang et al. 2001):


d

a ref bpart

V V
R z R

1

( )
s= + +

(15.7)

where R
bpart

is the boundary layer resistance for particle, which depends on
Brownian diffusion. V

d
depends strongly on the particle size, the characteristics

of the surface (roughness) and u*. The dry deposition velocity V
d
of NH

4
+ contain-

ing particles for neutral atmospheric conditions was estimated by Erisman et al.
(1994b) as:


d

u
V

A
*= (15.8)

where V
d
and u* are in m s−1, A = 500 (dimensionless) for low vegetation and

A = 100 for forests. Measurements show that the dry deposition velocity of NH
4

+
containing particles to moorland or grass is of the order of 0.2 cm s−1, with a
large uncertainty justifying the rough parameterisation of Eq. [15.8] (Sutton et
al. 1993c; Duyzer 1994). The dry deposition velocity to forests is higher than to
moorland.

The dry deposition velocity of NH
3
is potentially relatively high and is about a

factor of 10 higher than that of particulate NH
4
+. This means that NH

x
after conver-

sion from NH
3
to NH

4
+ is not dry deposited very well and is transported over long

distances. The only efficient removal process for particulate NH
4

+ is wet deposition
(Asman and Janssen 1987).

15.6.1 Measured Dry Deposition Velocities of NH
3
to (semi-)

Natural Vegetation

Measurement of NH
3
deposition velocity to semi-natural vegetation is reported in

many studies (Table 15.1). Table 15.1 shows higher V
d
for forest than for moorland

and grassland, which reflects the higher u
*
over forest.

Page 467

Subject Index 463

Livestock, 3, 42, 46, 49, 50, 52, 59, 62, 63, 77,
87, 88, 97, 109, 110, 115, 124, 195,
206, 277, 294, 394, 425, 431, 435

Local recapture, 205, 232, 239, 246, 392,
407, 453

M
Macrolichens, 103, 104
Manure

application, 88, 115, 250, 294, 304, 396,
397, 424, 427–429, 452

spreading, 24, 35, 137, 193, 380
storage, 88, 206, 208, 294, 396, 399, 429, 430

Mapping, 7, 9, 45, 87, 88, 113, 231, 331,
381, 445

Measurements, 1–3, 7, 17, 19, 23, 26, 31, 32,
38, 39, 53, 55, 66, 71, 75, 77, 79,
82–84, 87, 94, 95, 97, 98, 109–111,
117, 124, 130, 131, 133, 135–138,
140–142, 144, 147, 149, 156, 157, 159,
161–163, 166–168, 171–177, 183,
188–190, 195, 197, 198, 220–223, 232

Mire(s), 30
Mitigation, 4, 9, 109, 123, 124, 206, 384, 385,

387, 423–426, 429, 435, 440
MODDAAS, 224, 230, 231, 238, 239, 243–246
MODDAS-2D, 207
Model(s)

mesoscale, 2, 6, 7, 251, 334, 346, 446
regional, 7, 336, 339, 392–395, 407, 410,

411, 416, 449, 452, 453
Monin-obukhov length, 218
Monitoring, networks, 3, 7, 124, 131, 147,

171, 176, 385, 386, 433, 436, 441
Moorland, 19, 21, 29, 58, 60, 222, 223, 271,

284, 306, 312, 398

N
National ammonia monitoring network

(NAMN), 73, 83, 141, 142, 144,
187–193, 312, 316, 317

National emissions ceilings, 195
National trends network, 161
Network(s), 3, 7, 51, 73, 83, 124, 131,

134–136, 138, 139, 141, 142, 144
Nitric acid (HNO

3
), 42, 166, 167, 309, 330

Nitrogen
oxides (NO

x
), 9, 42, 205, 349

reduced (NH
x
), 2, 42, 90, 131, 133, 141,

161, 163, 166, 167, 169, 171, 174, 177,
182, 205, 312, 314, 331, 345, 346, 359,
360, 363, 365, 368, 383, 385, 386

Nitrophile, 32, 60, 63, 66–68, 377
Nitrophobe, 32, 60, 63, 66–68, 377
Nitrophyte, 43, 60, 71–74, 79, 101, 102, 104,

106, 377
Nitrous oxide (N

2
O), 9, 212, 403, 424, 427,

450, 453
No observable effect concentration

(NOEC), 16

O
OML-DEP, 224, 226, 231, 329, 331, 336
Open-slot injection (OSI), 196–201
Operational priority substance (OPS), 130,

134–138, 172, 211, 226, 249, 308, 317,
318, 320, 411, 414

Orographic enhancement, 7, 312, 361

P
Parameterisations, 176, 177, 231, 302, 303, 331
Particles, 19, 182, 212, 215, 216, 222, 224,

225, 234, 240–243, 265, 302, 306, 309,
310, 319, 338, 343

Particulate matter, 1, 6, 343, 392, 411, 435
Passive sampler(s), 53, 134–137, 174, 191,

208, 249, 320, 321, 389, 403
pH, 5, 20, 45, 51, 59, 71, 74–77, 79, 81,

101, 102, 104–106, 117, 162, 208,
209, 213, 219, 221, 307, 309, 324,
344, 396, 430, 431

Pig(s), 128, 144–146, 161, 162, 190, 191, 195,
197–199, 210, 212, 248, 312, 318, 396,
429, 435

Policy, 3, 5, 6, 8, 9, 19, 27, 41, 47, 123, 124,
131, 174, 175, 192, 383–385, 389, 391,
393, 417, 418, 433–442, 446, 448, 451,
452, 454

Poultry, 23, 59–65, 67, 68, 73, 145, 146, 190,
191, 195, 212, 248, 270, 271, 273–278,
281, 282, 284, 294, 312, 318, 396, 429,
430, 435

Precipitation, 19, 110, 111, 126–128,
138–140, 147, 150–152, 154, 159

Protocols, 23, 52, 205, 381, 388, 447, 451

R
Rain, 19, 123, 130, 131, 138, 169, 172, 200,

221, 224, 225, 251, 307, 308, 319, 343,
369, 384, 401, 448

Rapid incorporation, 196, 198, 429
Reactive nitrogen, 9, 71, 346, 367, 437, 439,

441, 446

Page 468

464 Subject Index

Reduced emission techniques, 195
Resistances, cuticular, 239, 246, 263, 417

S
Sampling, 26, 47, 55, 59, 72, 73, 76, 79, 83,

97, 101–104, 110–113, 115, 131, 140,
142, 145, 172, 189–191, 234, 235, 270,
273, 312, 381, 404, 414

Scale farm, 73, 74, 77–79, 82
Scavenging, 130, 224, 225, 229, 266, 307,

308, 312, 319, 324, 329, 331, 338, 343,
360, 361

Seasonal variation / variability, 160, 161,
209–211, 213, 229, 234, 338, 339, 345

Sites of special scientific interest (SSSI), 46,
60, 271, 276, 278

Slurry, 15, 195–201, 250, 396, 428–433
Stomata, 22, 52, 55, 56, 216, 217, 263–265,

306, 307, 319, 398
Source height, 205, 239–243, 245, 250, 302
Southern Europe(an), 380, 381
Spatial

planning, 293–296, 394, 404–405
variability, 3, 124, 175, 233, 291, 316, 349,

367, 368, 392, 395, 398, 404, 406, 449
Special area(s) of conservation (SAC), 46
Sphagnum, 20, 49, 56
Stomatal

compensation point, 219–220, 239, 241,
243, 251, 263, 307, 407

resistances, 239, 342
Sulphur, 126, 160, 169, 183, 184, 205, 251,

312, 322, 349, 370, 388
Sulphur dioxide (SO

2
), 71, 101, 183, 185, 212,

231, 331, 349, 368
Survey, 26, 28, 32, 36, 45, 61, 63, 73, 74,

76, 77, 79, 82–84, 102, 112,
376–378, 447

T
Target, 5, 37, 41, 46, 50, 98, 123, 138, 175,

195, 292, 391, 393, 404, 418, 426, 429,
433–436, 438–441, 446, 454

Task Force on Measurement and Modelling
(TFMM), 6, 177, 392

Task Force on Reactive Nitrogen (TFRN) 9
Temperature, 22, 28, 49, 51, 52, 55, 59, 110,

111, 117, 207, 208
Temporal trends, 144

Throughfall, 19, 31, 175, 176, 207, 221, 235, 236
TIA (Total inorganic ammonium), 166, 168, 235
TIN (Total inorganic nitrate), 166, 167
Tissue nitrogen, 282
Trailing hose (TH), 196, 197, 199–201, 429
Trailing shoe (TS), 196, 197, 199–201, 429
Transect(s), 26, 49, 51–53, 54, 56, 57, 59–62,

68, 269–271, 273, 275, 276, 284, 285,
293, 296

Transport, transboundary, 1, 5, 6, 177, 195,
391–395, 435, 445, 446

Trend, 63, 123–134, 140, 141, 143–147,
150–152, 154, 156, 162, 165, 166,
172, 175, 176, 181–183, 187, 190,
191, 211, 226, 246, 247, 267, 317,
336, 359, 385, 386, 388, 426, 431,
448, 452

Twigs, 72–84, 101–107

U
Uncertainties, 2, 6, 7, 9, 16, 38, 44, 45, 82,

124, 125, 131, 136, 171, 173, 205, 211,
221, 236, 249, 251, 321, 344, 377, 380,
393, 395, 397, 399–401, 406, 409, 415,
417, 418, 420, 425, 440, 446, 448,
449, 452

UNECE expert workshop
Aspenaas Herrgaard, 2
Bad Harzburg, 2
Bern, 2–4, 123, 124, 131, 143
Egham, 2, 4, 41, 47, 93–98, 447

United Nations Economic Comission for
Europe (UNECE), 1–3, 5, 6, 8, 9, 29,
30, 41–47

V
Vegetation, 4, 15, 16, 18, 22, 23, 25, 27–31,

33, 35–38, 42, 45, 46
Verification, 9, 131, 177, 237, 365, 489, 403,

433, 436, 441, 450, 453, 454

W
Whim, 22, 23, 31, 35, 49, 51–53, 56, 284–286,

378, 381

X
Xanthoria, 79, 81, 91

Similer Documents