boundary-layer isotope dilution/mass balance methods for measurement of nocturnal methane emissions...

Atmospheric Environment 36 (2002) 4663–4678

Boundary-layer isotope dilution/mass balance methods formeasurement of nocturnal methane emissions from grazing

sheep

M.J. Harveya,*, G.W. Brailsforda, A.M. Bromleya, K.R. Lasseya, Z. Meia,I.S. Kristamenta, A.R. Reisingerb, C.F. Walkerc, F.M. Kelliherd

aNational Institute of Water and Atmospheric Research, P.O. Box 14-901, Kilbirnie, Wellington, New ZealandbMinistry for the Environment, P.O. Box 10-362, Wellington, New Zealand

cSOC, University of Southampton, European Way, Southampton SO14 3ZH, UKdManaaki Whenua—Landcare Research, P.O. Box 69, Lincoln, Canterbury, New Zealand

Received 20 July 2001; received in revised form 21 May 2002; accepted 12 June 2002

Abstract

Following advances with methods for 13C/12C isotopic analysis of methane in small (p4L) air samples, new isotope

dilution techniques are proposed for measurement of methane emissions at the paddock scale from grazing ruminant

animals. These techniques combine measurement of the isotopic d13CH4 composition of air samples with a non-

intrusive mass balance method applied in the nocturnal boundary layer. Flux estimates from trials using the isotope

dilution techniques are compared with estimates based on scaling up individual animal emission measurements using a

rumen gas tracer technique. The methane flux assessed by the latter technique ranged from 35 to 70mg (CH4) m�2 d�1

with a stocking density between 10 and 20 sheep ha�1. The isotope dilution based nocturnal boundary-layer estimates

generally agreed to better than a factor of 2 and usually to within 20% of the average of individual animal emission rate

per unit area of paddock. Both static and advecting mass balance methods are developed. In the advecting case, the

upwind/downwind contrast in d13C was typically 0.2–0.5%. Care was necessary with air sampling to avoid error in this

small contrast contributing to error in the flux. Agreement between concentration- and isotope-based nocturnal

boundary layer methods and the sheep breath measurements indicated that sample representativeness was generally

good. Factors which affect the accuracy of the method are examined and include variability in nocturnal mixing height,

the assumed d13CH4 composition of the source sheep breath and diurnal patterns in sheep emission. This paper

establishes new techniques useful in the paddock to landscape scale although widespread application awaits further

development of technology for rapid and repeatable field analysis of d13CH4 in small samples.

r 2002 Elsevier Science Ltd. All rights reserved.

Keywords: Ruminant methane; Micrometeorology; Agricultural greenhouse gas; Methane isotopes; New Zealand

1. Introduction

Globally, ruminant methane accounts for about 15%

of the total methane flux to the atmosphere; more than

50% of this total flux is anthropogenic (Houghton et al.,

2001). However, in New Zealand, ruminant livestock is

thought to account for nearly 90% of anthropogenic

methane emission based on national inventory data for

2000 supplied under the United Nations Framework

Convention on Climate Change (New Zealand Climate

Change Project, 2002). On the basis of 100 year global

warming potentials (Houghton et al., 2001) methane is

New Zealand’s single most important greenhouse gas*Corresponding author. Fax: +64-4-386-2153.

E-mail address: [email protected] (M.J. Harvey).

1352-2310/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved.

PII: S 1 3 5 2 - 2 3 1 0 ( 0 2 ) 0 0 4 1 0 - 7

emission accounting for about half of the CO2-

equivalent anthropogenic greenhouse gas emissions

(Ministry for the Environment, 1997). However, there

is significant uncertainty in these estimates. As part of

the process of improving the accuracy of the national

greenhouse gas emissions inventory, ruminant emissions

and their variability are being quantified under a range

of typical farming situations. The current study is one of

a number in New Zealand assessing methane emissions

over a range of measurement scales from individual

animal to region.

These studies include measurements at the individual

animal scale using a sulfur hexafluoride (SF6) tracer

technique developed for cattle by Johnson et al. (1994).

Based on a calibrated permeation source of SF6 inserted

in the animal rumen this technique measures, over a

period of hours to days, the average concentrations of

both SF6 and methane in exhaled air that is slowly

drawn into an evacuated container mounted on the

animal. Methane emission rates are estimated from

the ratio of methane to SF6 in the sampled breath and

the calibrated release rate of SF6. This technique has

been applied in New Zealand and Australia to both

cattle and sheep (Lassey et al., 1997; Leuning et al.,

1999). Emission variations between animals can limit the

certainty in scaled-up breath measurements. This

limitation has, in part, led to measurements that exploit

the atmosphere itself as a natural spatial integrator. At

the paddock scale (0.5–1 km), the micrometeorological

flux-gradient technique has been applied to sheep flocks

(Judd et al., 1999) using point profile gas sampling. For

improved spatial integration, a development of the flux-

gradient technique using long-path measurements with

Fourier transform infrared (FTIR) spectroscopy has

been suggested by Andreas et al. (1992) and applied in

New Zealand by Kelliher et al. (2002). At the regional

scale (20–40 km) convective boundary layer (CBL)

budget measurements have been made by measuring

vertical profile differences up- and downwind of a source

region using a light aircraft (Wratt et al., 2001). In this

paper, we focus on the paddock scale, where the flux-

gradient technique is attractive because it is relatively

easy to apply and non-intrusive. However, a number of

requirements need to be met. Firstly, the method

requires a homogeneous source region (fetch) upwind

and this is not possible to achieve without artificial

constraints on sheep that naturally wander and tend to

flock. Ideally, the landscape should be flat without

aerodynamic barriers (shelter-belts) upwind and suitable

sites are difficult to find in the New Zealand landscape.

Secondly, the technique is often applied close to the

lower limit of flux quantification as determined by the

signal-to-noise ratio, i.e. the magnitude of the concen-

tration gradient can be similar to the precision with

which methane can be measured. Thirdly, the technique

cannot be applied under conditions of light wind and

strong stability at night, when turbulent transfer

relationships break down.

As an alternative at night, sheep emission fluxes can

be quantified from the methane gas budget within the

nocturnal boundary layer (NBL), in either a static or an

advecting situation. The low-level inversion and stable

surface layer that forms, most strongly on still clear

nights, through loss of long-wave radiation to space

significantly inhibits the vertical mixing of trace gases

emitted at the surface. Nocturnal mixing heights are

typically less than 100m compared to daytime con-

vective boundary layers of 1000m, giving more than an

order of magnitude advantage in rate of concentration

increase for emissions within that layer. However,

because of poor mixing within the stable surface layer,

and the likelihood of intermittent entrainment of air

flowing above the inversion (Mahrt, 1999), inhomogene-

ities in methane concentration are highly likely. Never-

theless, nocturnal box and profile measurements have

been used to estimate methane emissions from wetlands

by Gallagher et al. (1994), Choularton et al. (1995) and

Beswick et al. (1998) and from extensive sheep grazing

by Denmead et al. (2000).

In this paper, we describe the development of

techniques for the measurement of d13CH4 in small air

samples. We then develop and assess an extension to

NBL techniques using the isotopic methane measure-

ments. Sheep methane emission is quantified through

dilution of its distinctive isotope signal in the nocturnal

boundary layer and the method is applied to estimate

emission fluxes on five nights at two sites. The results are

compared with other techniques applied concurrently

and to predictions of a plume dispersion model.

Limitations and potential difficulties of the NBL

technique are discussed.

2. Methods

2.1. Methane analysis methods

Methane mixing ratio was measured by gas chroma-

tograph (GC-Hewlett Packard 5890 Series II) with flame

ionisation detection. Measurement precision was typi-

cally better than 1 ppbv. During 1998, high-precision

analysis techniques were developed for methane carbon

isotope ratio determination in small (4 L) air samples

through miniaturization of traps in the vacuum extrac-

tion line. Offline isotope ratio mass spectrometry

(IRMS) was done using the dual inlet technique on a

Finnigan-MAT 252. The GC and IRMS methods

including calibration are outlined by Lowe et al. (1999).

In 1999, the dual inlet technique was superseded by a

continuous-flow (GC-IRMS) technique which intro-

duced a nanomolar sample directly into the mass

spectrometer. The method described by Ferretti et al.

M.J. Harvey et al. / Atmospheric Environment 36 (2002) 4663–46784664

(2000) for CO2 was modified for CH4. Interfering gases

were removed: CO through oxidation with iodine

pentoxide followed by removal of CO2, N2O, non-

methane hydrocarbons and water by cryogenic trapping.

The purified sample was then combusted to CO2 in a

furnace with puratronic grade platinum wire as the

catalyst. At 150ml of air per determination, three

determinations were made on small air samples to

0.06% precision. The total processing time by GC-

IRMS was about 30min compared with 2 h for

extraction and analysis by dual inlet. Accuracy of all

the mass spectrometer measurements was maintained

with regular working gas standard measurements

calibrated against IAEA-NBS19 standard.

For the atmospheric measurement, there is potentially

good signal to noise for both concentration and isotope

measurements. For example with an emission flux F of

2.5mmol(CH4) m�2 d�1 from a sheep flock and a mixing

height z of 100m, the predicted rate of concentration

change determined using Eq. (1) is 25 ppb h�1 which is

16 h�1 of the measurement precision of 1.5 ppb. From

NBL-IDT method 1 the predicted rate of d13C change is

�0.26% h�1 which is 4 h�1 of the measurement precision

of 0.06%.

2.2. NBL and mass balance techniques

If the NBL is considered as a well-mixed box, capped

by a mixing height z; in which the methane concentra-

tion, C; grows with time due to entrainment, the

methane surface source flux, F ; may be calculated as

F ¼ zðdC=dtÞ: ð1Þ

This simple zeroth-order relationship as applied by

Gallagher et al. (1994) to methane flux estimation asserts

mass balance in such a box, neglecting both horizontal

advection and diffusion through the box ceiling. More-

over, during light winds, a weakness in this technique is

the assumption that air within the box is well mixed. To

account for horizontal inhomogeneity, sufficient mea-

surements need to be made within the box to quantify a

‘‘representative’’ concentration. When vertical profiles

of methane concentration are available to characterise

the incomplete vertical mixing in the box, these lead to a

more accurate flux assessment given by

F ¼Z z

0

ðdC=dtÞ dz: ð2Þ

This method Eq. (2), denoted here NBL method 1, is

also limited to still conditions because it ignores

horizontal advection. In practice, this means nights with

windspeed at 2m of less than 2m s�1.

If there is significant advecting wind, (windspeed at

2m greater than 2m s�1) horizontal concentration

gradients will occur across the source region, and mass

balance then requires NBL method 2 Eq. (3) (e.g.

Denmead, 1995; Denmead et al., 1998; Leuning et al.,

1999):

F ¼1

X

Z z

0

uðCd � CuÞ dz: ð3Þ

Application requires that vertical profiles of gas

concentration be measured upwind, CuðzÞ; and down-

wind, CdðzÞ; of the source region. The overbar in Eq. (3)

denotes the time-averaged product of this profile

difference with the advecting windspeed, uðzÞ; across

the experimental plot with distance X between the

upwind and downwind measurement points. This mean

product will differ from the product of the mean profile

difference and mean wind speed because the latter

ignores correlations in the form of turbulent diffusive

fluxes. Denmead (1995) has examined these effects, and

showed that, as has been done in this study, ignoring

such correlations (i.e., replacing the mean of the product

by the product of the mean in Eq. (3)) incurs errors of

around 10–20%.

2.3. Isotope dilution mass balance techniques

As an extension to the NBL methods above, sheep

methane emissions are estimated by following the time

dependent increase in both mixing ratio and d13Cisotopic ratio of the ambient methane. We use the

standard delta notation, d13C, which relates the stable

isotope ratio of sample Rsa to that in the Vienna Peedee

belemnite (VPDB) isotope standard:

d13C ¼ ðRsa=RVPDB � 1Þ � 1000ð%Þ; ð4Þ

where the ratio RVPDB ¼13 CVPDB=12

CVPDB of around

0.0112 (Craig, 1957). The isotope dilution technique

(IDT) exploits the contrast between the d13C in methane

of background or upwind air, du; which is close to

�47%, and that of the agricultural source, ds: For sheepconsuming rye grass/clover pasture, the ‘‘enterically

fermented’’ methane has a d13C value which we have

measured at around �62%, consistent with values

reported by Rust (1981). Source isotopic composition

is discussed further in Section 4.2.

From mass balance considerations, the entrainment of

a surface flux of methane from grazing sheep (d13C value

ds) into upwind air (concentration Cu; d13C value du) to

produce downwind air (well-mixed concentration Cd;d13C value dd) is described by

Cddd ¼ Cudu þ Csds; ð5Þ

where Cs ¼ Cd � Cu is the concentration of sheep

methane in the downwind air. Rearrangement of

Eq. (5) produces an ‘‘isotope mixing line’’:

dd ¼ ds þ ðdu � dsÞCu=Cd ð6Þ

A plot of dd against 1=Cd is a straight line with

intercept at 1=Cd-0 that estimates ds; i.e. d13C of the

M.J. Harvey et al. / Atmospheric Environment 36 (2002) 4663–4678 4665

source (e.g. Stevens and Engelkemeir, 1988; Berga-

maschi et al., 1998).

The IDT utilises the rate of change of d13C due to

entrainment of sheep methane within the boundary

layer, by analogy with the rate of change of concentra-

tion in NBL method 1. Taking the analogue of Eq. (1)

Fds ¼ zðdðCdÞ=dtÞ; ð7Þ

where dðtÞ is the changing value for d13C in the

accumulating atmospheric methane, and combining

with Eq. (1) itself gives

F ¼zCðdd=dtÞds � d

: ð8Þ

For a steady flux, C and d are evaluated at t ¼ 0: Theanalogue of NBL method 1, denoted NBL-IDT method

1, can be similarly derived as

F ¼Z z

0

Cð0Þdd=dt

ds � dð0Þdz: ð9Þ

The NBL-IDT method 1 requires measurement of an

initial concentration and time series of d13C in a well-

mixed box. A similar derivation based on NBL method

2 produces NBL-IDT method 2

F ¼1

X ðdu � dsÞ

Z z

0

uCdðdu � ddÞ dz; ð10Þ

where du is the mean upwind or background methane

d13C. If the background boundary-layer air is well mixed

and the isotope ratios of source and background are

quantified, then NBL-IDT method 2 enables a flux

estimation based on a single vertical profile of wind and

of methane isotope and mixing ratio downwind of the

source.

2.4. New Zealand field measurements

Isotope measurements were made on five nights

subsequently referred to as N1–N5, at two sites

(Table 1 and Fig. 1). The Aorangi Farm site (401210S,

1751290E) is in the fertile Manawatu lowlands of the

North Island, 9 km WNW of Palmerston North (and

21 km E of the Tasman sea). The site comprised three

contiguous flat and level paddocks of total length

B700m and width 150m. Westerly wind predominated

through all three measurement periods over a 1 km

upwind fetch of sheep with a stocking density of

approximately 20 ha�1. Comparisons are made with

the collocated flux-gradient measurements reported by

Judd et al. (1999) and CBL budget measurements by

Wratt et al. (2001) during Aorangi 1. The measurements

Table 1

Measurement periods at Aorangi and Springston Farms

Campaign Date and season Summary of measurementsa Nocturnal isotope dilution

experiment (Night number)

Aorangi 1 3–11 Apr 1997 (Autumn) SBb, NBL, FGb, CBLc 9–10 Apr (N1)

Aorangi 2 20–26 Sep 1997 (Early

Spring)

SB, NBL 20–21 Sep (N2)

25–26 Sep (N3)

Aorangi 3 21–27 Nov 1997 (Late

Spring)

FG

Springston 19 Mar–1 Apr 1999 (Early

Autumn)

SB, NBL, GR-FTIR 25–26 Mar (N4)

27–28 Mar (N5)

aSee Section 2.5, SB: sheep breath, NBL: nocturnal boundary layer, FG: gradient micrometeorological measurement, CBL: daytime

convective boundary layer budget, GR-FTIR: Gas ratio technique using open path Fourier transform infrared spectroscopy.b Judd et al. (1999).cWratt et al. (2001).

Fig. 1. New Zealand measurement sites.


at Springston (43138.80S, 172124.70E) were on a com-

mercial farm on the Canterbury plains of the South

Island. An area of approximately 10 ha (380m� 250m)

was populated by 92 pregnant ewes maintained in sub-

paddocks to distribute the sheep at a more even paddock

density of around 10 sheep per hectare. In the summer

months before the experiment, the paddock was in

drought and stock were supported with supplemental

feed. Substantial grass regrowth occurred with rains

during the month before the measurements reported

here. Comparisons were made with other techniques as

summarised in Table 1.

The presence of a nocturnal surface inversion was

established from wind, temperature and humidity

profiles to 200m measured from kytoon (AIR Inc.

model TS-3A-SP tethered balloon) soundings through

each night. During periods when the winds were too

strong (>10m s�1) for using the kytoon, low-lift

airsondes (AIR Inc. model AS-1C-PTH) were used. At

Springston, a doppler acoustic sounder (Remtech PA2)

was also operated at 20m vertical resolution to give

20min average wind to 400m as well as estimated

mixing height. Gas samples were collected in 2L (or

1.5 L) glass flasks (Glass Expansion Pty, Australia)

which were flushed several times then filled with ambient

air over about 10min to approximately 200 kPa using

12V battery powered diaphragm pumps (Thomas

Industries Inc.). Glass flasks were used in preference to

Tedlar bags and allowed collection of pressurised

samples. Additionally, the samples had to be stored

for several months before isotope analysis and there is

evidence (Okada and Tezuka, 1989) of significant

isotope shifts over 1 month with samples in Tedlar bags

whereas glass has shown no such shift.

On N1, vertical gradients of methane mixing ratio

were measured at the downwind site and used in the

vertical flux integrations. On subsequent nights, the

vertical structure in the lowest 20m was examined by

kytoon temperature and humidity sounding. In the

absence of discontinuities, vertical profiles of methane

were estimated from measurement at a single 2m height

and the flux/profile relationship for the expected

magnitude of flux F :

F ¼ �k2 qu

qðz � dÞqC

qðz � dÞðfHfM Þ�1;

where k is the von Karman constant, d is zero plane

displacement and ðfHfM Þ�1 is a generalized stability

factor. Under stable conditions (�0.1oRio1) this

factor is equivalent to (1–5Ri)2 (Thom, 1975). In this

study, stability was determined by the bulk Richardson

number Ri ¼ ðg=%yÞð%y2 � %y1Þðz2 � z1Þ=ðu2 � u1Þ2 in the

lowest 20m of the atmosphere; %y2 and %y1 denote the

mean potential temperature measured along with mean

windspeeds u from mast or kytoon at heights z2 and z1; g

is acceleration due to gravity. In addition, 2 or 3

upwind/background gas samples were collected during

the night.

2.5. Comparison with other methods

In comparing different methods (Table 1), measure-

ments of the breath emissions of individual animals

using the SF6 tracer technique (Lassey et al., 1997), in

conjunction with stocking density, were considered as

the standard reference ‘‘bottom-up’’ flux. These sheep

breath measurements were made during all NBL

measurement periods. In order to compare nocturnal

measurements with daytime or 24 h measurements, any

systematic diurnality in flux needs to be accounted for.

Our results contrast those of Judd et al. (1999) and show

that diurnality in the methane emission of pasture-

grazing sheep is complex and not predictable (Section

4.3). We therefore have not made corrections to our

NBL data on the basis of diurnality. At Aorangi,

comparisons with average flux-gradient and aircraft

CBL profile measurements were made. At Springston,

NBL measurements of gas concentration over a 100m

open-path, were made by FTIR spectrometer (Kelliher

et al., 2002). From these measurements, fluxes were

estimated through both mixing ratio increase (NBL

method 1) and an atmospheric gas ratio technique (GR-

FTIR) (Kuhlmann et al., 1998). The latter technique

uses the multi-gas capability of the FTIR spectrometer,

to calculate an indirect estimate of the methane flux

from the ratio of CO2 and CH4 mixing ratios and an

independent measurement of CO2 respiration flux at

night. An assumption is made that the sheep methane

emission and CO2 respiration flux are both homoge-

neously distributed surface sources. The nocturnal

surface emission of CO2 from soil and plant respiration

was measured at sample points around the paddock

using a portable chamber, covering an area of 0.008m2,

and infrared gas analyser system (coupled SRC-1 and

EGM-3, PP Systems, Ltd., Hitchin, Hertfordshire,

England).

2.6. Modelling methane sheep breath dispersion

For each night, the Ausplume Gaussian plume

dispersion model (VEPA, 1986) was used to simulate

sheep breath dispersion and predict the methane vertical

profile immediately downwind of the paddock. Sheep in

the immediate paddocks were modelled as a uniform

grid of point sources. At Aorangi, sheep in distant

paddocks upwind were modelled as area sources.

Meteorological input data were generated from the

measured hourly sonde and kytoon vertical profiles and

output concentration fields were produced at hourly

resolution.


3. Analyses and results

3.1. Methane isotope mixing lines

Fig. 2 shows the isotopic mixing lines for each night.

The correlation between d13C and inverse concentration

is weakest for the Springston measurements where the

local sheep methane was a less dominant source than at

Aorangi for two reasons. Firstly, both the paddock

sheep density and the regional sheep density was lower

than Aorangi. Secondly, nearby local agricultural burn-

offs were observed during the time of the experiment

with the possible introduction of an additional methane

source. The lighter intercept value for N4 (Table 2) is

evidence of the latter. However, the absence of elevated

CO in samples indicated that major contamination from

agricultural burning was unlikely. The average intercept

value of d13C (excluding N4 having low r2) was about

�64%, and close to our expected value for sheep

methane of �62% based on some individual measure-

ments of eructated gases (see Section 4.2). The

uncertainty in this estimate as calculated from the

standard error of the regression intercept was around

1% for nights with the greatest methane build up.

Table 2 summarises the mixing lines and makes a

comparison with regional baseline measurements made

at Baring Head (BHD 41124.60S, 174152.20E) baseline

monitoring station (Lowe et al., 1994). BHD provides

methane data sampled in an unpolluted marine bound-

ary layer and can be regarded as characterising

the background methane arriving at New Zealand.

The comparison (in the last column) is made between

the d13C predicted by the mixing line at the baseline

(BHD) mixing ratio at the time of these measurements

(Column 6: BHD mixing ratio) with the actual baseline

d13C measured at Baring Head (Column 7: d13C(BHD))

at the same time. Assuming a homogeneous back-

ground, a significant difference between d13C(fitted) andd13C(BHD) indicates that there has been some degree of

contamination of the methane upwind of the sample

4.00e-4 4.50e-4 5.00e-4 5.50e-4 6.00e-4

1/[CH4] (ppbv-1)

-53

-51

-49

-47

δ13

C(‰

)

N1 (Aorangi 9-10 Apr 1997 downwind)N1 (Aorangi 9-10 Apr 1997 upwind)N2 (Aorangi 20-21 Sep 1998)N3 (Aorangi 25-26 Sep 1998)N4 (Springston 25-26 Mar 1999)N5 (Springston 27-28 Mar 1999)

(2500 ppbv) (1670 ppbv)(1818 ppbv)

Fig. 2. Mixing lines of d13C methane. Each line represents the relationship between isotope ratio and mixing ratio for one night.

Table 2

Isotope mixing line summary and concurrent baseline methane at Baring Head (BHD)

Night

no.

d13C (source)

(%)

Std. Error

d13C (source)

(%)

Gradient

(% ppbv)

Correlation

(r2)

BHD CH4

mixing ratio

(ppbv)

d13C (BHD)

(%)

d13C (fitted)–

d13C (BHD)

(%)

N1 �63.4 2.2 26440 0.72 1705 �47.1 �0.8

N2 �66.1 0.9 33290 0.97 1740 �47.1 0.1

N3 �63.9 1.2 29000 0.95 1740 �47.1 �0.2

N4 �52.6 1.3 9220 0.38 1720 �47.03 �0.2

N5 �61.3 4.1 24710 0.59 1720 �47.03 0.1


site, or that upwind trajectories deliver different air

masses to the two sites. On most days d13C(fitted) is

within 0.2% of d13C(BHD). However, for N1 the

predicted value is 0.8% lighter (less enriched in 13C)

than d13C(BHD). There were several pieces of evidence

that on N1 at Aorangi there was a complex situation

with an airmass containing a significant mixing ratio of

isotopically lighter methane aloft. Firstly, the time series

of concentration and d13C showed a significant spike of

high concentration light methane around the time of the

break-up of the nocturnal inversion. Secondly, around

noon on 10 April 1997 an aircraft overflight at Aorangi

reported by Wratt et al. (2001) recorded methane mixing

ratios in the onshore winds at the site that were slightly

greater than those simultaneously recorded at heights

between 4 and 1m from ground-based measurement.

Finally, Wratt et al. (2001) also found significantly

greater methane concentrations at 1500m height off-

shore to the west than were present 20 km inland at

Aorangi at 1500m in westerly winds. In this case the

source of the methane aloft is uncertain although Wratt

et al. (2001) did find other instances of methane

draining off the west coast at night to be advected back

in again in a developing daytime westerly breeze. This

example and others in the general discussion below

indicate that spatial variability and complexities of

additional sources can be an important factor limiting

the ease of application of all boundary-layer mass

balance methods.

3.2. Nocturnal trials and flux estimation

The largest methane build-up was observed on N2

with light winds and strong stability. Table 3 sum-

marizes the meteorological conditions during periods of

gas build-up suitable for nocturnal flux determination.

Conditions on the very stable N2 are illustrated in

Fig. 3 which shows the potential temperature y differ-

ence between 100, 20 and 4m and the surface and the

bulk Richardson number calculated between 20 and 4m

and the surface. Fig. 4 shows the time series of methane

mixing ratio and d13C for this night. Periods with the

greatest atmospheric stability showed the greatest

increase in concentration and reduction in d13C. The

most dramatic instance was around 22:00 when con-

centration was approximately 1.5 times background.

Periods of rapid mixing ratio growth in the early part of

the evening in the most stable periods of the NBL were

used to give flux estimates by NBL method 1 and NBL-

IDT method 1. Table 4 gives the flux estimates

compared with those of other techniques. The sheep

breath measurements are based on a sub-flock sample of

12 sheep with results given on a per unit area and per

head basis. In the light winds of N2, NBL estimates were

in good agreement with the scaled sheep-breath esti-

mates. In contrast, significant advective loss on N3 has

reduced the NBL estimate to about half that from the

sheep breath.

On more windy nights (N1, N4 and N5), flux

estimates by NBL method 2 and NBL-IDT method 2

were made. Figs. 5 and 6 show times lines of mixing

ratio and d13C for N4 and N5, respectively. With

simultaneous measurement at four sites, large nocturnal

variability is apparent. On N4, the general trend in

mixing ratio increase is similar at three of the four sites

at around 2.5–3 ppbv h�1 over the whole period. The

most dramatic build up was at the downwind (S) site

through to the break up of the nocturnal inversion. On

N5, a similar mixing ratio increase was observed at all

four sites in the first part of the night from 17:30 to

01:00. In the second half of the night, mixing ratio

dropped; this drop is likely to have been caused by

the wind backing slightly in the middle of the night

from around 501 to 301 so that the downwind sample

site was displaced from the centre of the sheep methane

plumes.

On these two nights at Springston (Figs. 5 and 6),

downstream concentrations were not always largest and

upstream concentrations were not always smallest. d13Cshowed consistent anomalies with upstream data some-

times being more depleted in 13C compared to values

downstream. Although the winds were fairly steady on

these nights with a persistent north-easterly flow at

the surface, there was some sheep movement though the

night which could have accounted for much of the

variability. In general though, Table 4 shows the NBL

Table 3

Summary of nocturnal meteorology and maximum methane concentration

Night Average wind (10m)

(m s�1)

Potential

temperature gradient

(20–0m) (Km�1)

Bulk Richardson

number (4m)

Maximum nocturnal

[CH4] at 2m (ppbv)

N1 5 +0.04 0.03 (4–2m) 1809

N2 1.3 +0.09 1.02 2527

N3 2.0 +0.05 0.01 1975

N4 5.0 No data 0.02 1831

N5 4.3 +0.02 0.04 1875


methods gave good agreement to within 720% of the

‘‘bottom up’’ sheep breath assessments excluding N3

which underestimated flux due to unexpected advective

loss and N4 where estimates were likely to have been

affected by a biomass burning contamination.

4. Discussion

The NBL static techniques (NBL method 1 and NBL-

IDT method) 1 worked well with a well defined

nocturnal boundary layer, strong stability and light

18:00 21:00 00:00 03:00 06:00

Time of day

-2

-1

0

1

2

3

4

5P

oten

tial t

empe

ratu

re d

iffer

ence

(K

)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Bul

k R

icha

rdso

n nu

mbe

r

dθ (4m) dθ (20m) dθ (100m) Ri (4m) Ri (20m)

Fig. 3. Time course of atmospheric stability for N2 (20–21 September 1997).

18:00 21:00 00:00 03:00 06:00

Time of day

1700

1800

1900

2000

2100

2200

2300

2400

2500

2600

CH

4(p

pbv)

-54.0

-53.5

-53.0

-52.5

-52.0

-51.5

-51.0

-50.5

-50.0

-49.5

-49.0

-48.5

-48.0

-47.5

-47.0

δ13C

(%)

Measured CH4 mixing ratio downwind (ppbv) δ13C downwindInversion height (m)Ausplume CH

4 mixing ratio (ppbv, 2m height)

0102030405060708090

100

Inve

rsio

nhe

ight

(m)

Fig. 4. Time course of methane mixing ratio and d13C for N2 (20–21 September 1997).


winds below 2m s�1. The mass balance technique NBL-

IDT method 2 was applied to give acceptable estimates

under windier conditions. Table 4 also shows that

agreement between all the techniques is generally good

to within a factor of 2, and usually within B20%. We

have not expressed the magnitude of the error in

individual NBL trial assessments although we estimate

uncertainty in the flux estimate to be of the order of

720% from analysis of the propagation of error. The

contribution from the analytical error in the methane

mixing ratio and d13C measurements is insignificant

(typically 0.1% and 0.06%, respectively). The overall

error is dominated by the variability that is present due

to meteorological factors, such as poor mixing, which

causes horizontal variability in the concentration fields

from an inhomogeneous source and through difficulty in

measuring mixing height z: Some of the source

inhomogeneity is due to differences in emission rate of

individual animals. The coefficient of variation (1s s.d.)

of individual animal measurements is quite high at up to

25%. However, a far greater source of spatial inhomo-

geneity is caused by the tendency of the sheep to flock. A

careful sampling strategy is required to ensure that this

natural variability is captured and spatially averaged by

the NBL techniques. In order to collect upwind and

downwind air samples that are representative, we

analysed several samples of each collected along

horizontal crosswind transects to be confident that air

sampling uncertainties were minimal.

The IDT techniques are susceptible to error that could

arise through unrepresentative sampling. With upwind–

downwind contrasts in d13C as small as 0.2%, it is

important that errors in this contrast be minimised. For

example, an error of around 0.2% in the downwind d13Ccould give rise to a 50% or more error in the inferred

flux. The source-air contrast in d13C is much larger at

B15%, so that an inaccuracy of 2–3% in the value

adopted for the sheep source translates to around –20%

to +30% error in the inferred flux. Table 4 records good

agreement between the conventional NBL techniques

and the IDT methods, and their concurrence with

individual sheep measurements, on nights with favour-

able meteorology. This conformity suggests that the air

sampling did not unduly limit confidence in the inferred

fluxes. Nevertheless, for the benefit of future applica-

tions, we discuss specific sources of uncertainty in more

detail.

4.1. Uncertainties in mixing height and comparisons with

Ausplume model results

As with the measurements, modelled methane profiles

were highly sensitive to the stability class used in the

model. The effect is seen on N2 in the two peaks in the

Table 4

Comparison of flux estimates

Location Night

number

Flock

density

(ha�1)

Sheep breath

(mgm�2 d�1)

(g head�1 d�1

in brackets)

Mixing

height

(m)

NBL

method

NBL flux

(mgm�2 d�1)

Flux/gradient

(mgm�2 d�1)

Other

(mgm�2 d�1)

Aorangi N1 20 39.072.8 20 NBL 2 38 46a 73733b

(19.571.4) NBL-IDT 2 42

Aorangi N2 20 62.673.1c 20 NBL 1 56 NA NA

(31.371.6) NBL-IDT 1 59

Aorangi N3 20 62.673.1c 20 NBL 1 32 NA NA

(31.371.6) NBL-IDT 1 28

Aorangi

21–27 Nov

1997

— 20 68.473.1c — None NA 96766d NA

(34.271.6)

Springston N4 10 33.472.4c 2 NBL 2 79 NA NA

(35.272.5) NBL-IDT 2 29

Springston N5 10 33.472.4c 2 NBL 2 40 NA 20e

(35.272.5) NBL-IDT 2 38 39712f

Units (mg (CH4)m�2 d�1), NA: not available.

aFlux gradient (Judd et al., 1999).bDaytime aircraft CBL budget (Wratt et al., 2001).cAverage for week on both per area and per animal basis7standard error of mean (n=12).d22 half hour flux-gradient (between 4 and 2m) tedlar bag samples.eNBL method 1 by FTIR 29–30 March 1999 assuming 20m mixing height.fNBL gas ratio (GR-FTIR) CO2/CH4 29–30 March 1999.


Ausplume prediction (Fig. 4) which correspond to

periods when the windspeed was less than 1m s�1 in a

highly stable boundary layer. The general trends of

methane mixing ratio are similar in model and

measurement although details in the timing are

different; e.g. the dip around 22:00 was not seen at

19:00 22:00 01:00 04:00 07:00 10:00 13:00

Time of day

1700

1750

1800

1850

1900

[CH

4](p

pbv)

NE site (upstream) Centre paddockS site (downstream) SW site (downstream)

19:00 22:00 01:00 04:00 07:00 10:00 13:00

Time of day

-48.0

-47.8

-47.6

-47.4

-47.2

-47.0

-46.8

-46.6

δ13

C(‰

)

NE site (upstream) Centre paddock

S site (downstream) SW site (downstream)

Fig. 5. Time course of methane mixing ratio and d13C for N4 (25–26 March 1999).


the measurement frequency. In general, for all nights

(not shown) the modelled methane concentrations

were significantly less than the measured values. One

possible explanation may be the unrealistic model

assumption of a uniform flux that does not recognise

sheep flocking, a second could be poor performance of

the plume model under highly stable light wind

conditions.

With the strong vertical gradients in methane

that exist within the stable NBL, a depth-integrated

16:00 19:00 22:00 01:00 04:00 07:00 10:00 13:00

Time of day

1700

1750

1800

1850

1900

[CH

4]

(ppb

v)

NE site (upstream)

Centre paddock

S site (downstream)

SW site (downstream)

Ausplume SW prediction

19:00 22:00 01:00 04:00 07:00 10:00 13:00

Time of day

-48.0

-47.8

-47.6

-47.4

-47.2

-47.0

-46.8

-46.6

δ 13C

(‰)

NE site (upstream)

Centre paddock

S site (downstream)

SW site (downstream)

Fig. 6. Time course of methane mixing ratio and d13C for N5 (27–28 March 1999).


approach to all of the NBL methods provided the best

accuracy. Without its direct measurement, mixing height

is hard to obtain and introduces a major source of error.

Other scalars can be used to quantify mixing. We

estimated mixing height from discontinuities in vertical

soundings of potential temperature and water vapour

mixing ratio. As previously discussed, the best agree-

ment in NBL method 1 and NBL-IDT method 1 with

the sheep breath technique was found on N2. When

compared with modelled vertical profiles of methane on

N2, the extent of vertical diffusion predicted by

Ausplume (Fig. 7a) throughout the surface 20m layer

was similar to the mixing depth determined from kytoon

measurements. The kytoon showed a very stable layer to

20m in the first half of the night, containing a uniform

water vapour mixing ratio as an indicator of the well

mixed nature of this surface layer. A well defined mixing

height and strong near surface stability on this night led

to the best agreement between measurement and model.

In contrast, on nights N4 and N5, the mixing height

was less clearly defined and other sources of methane

were present above the NBL from daytime stubble

burning. On these nights, the Doppler sounder did not

prove useful. The predicted mixing height from acoustic

echo was typically of the order of 100m. However, from

methane vertical profiles, we found that an accurate flux

estimate, as compared with the sheep breath technique,

was achieved with vertical integration to 2m with the

restricted upwind extent of sheep at Springston of

B300m compared to B1 km extent at Aorangi. Fig. 7b

shows the modelled vertical profiles with concentrations

falling to background at around z ¼ 10m. This model,

using standard plume dispersion formula, broadly

agrees with the limited vertical dispersion observed

and predicts sz; the vertical dispersion parameter is

about 0.3 at 20m downwind from the Springston

paddock under the most stable conditions (Hanna

et al., 1982). In general, accurate information on mixing

height is important and this requirement is best met

through vertical profile measurement.

4.2. d13C signature of sheep breath

The range of d13C in eructed methane will be

dependent on d13C of the feed and fractionation

occurring in methanogenesis. Our NBL flux estimates

are sensitive to the d13C contrast between the source and

atmosphere. Uncertainties should be able to be kept

small compared to this contrast and it is therefore

important to measure the source signature for the

environment under study. Comparing feeds, the carbon

in C3 photosynthesis plants is relatively depleted in 13C

compared with C4 photosynthesis plants. Rust (1981)

found correspondingly that d13C of CH4 from ruminants

with a C3 diet ranged from �58.1% to �76.0%compared with those on a C4 diet of �45.4% to

�52.8%. However, there can be significant differences,

even within the C3 group. Bilek et al. (2001) show how

differing d13C in C3 hay/concentrate feeds leads to

corresponding differences in eructed d13CH4. Thus a

range of values appear in the literature. With the typical

C3 diet of temperate grasslands, Wahlen (1994) shows a

range between �67% and �72%, Gupta et al. (1996)

cite –62%, Hein et al. (1997) cite –6273% and Quay

et al. (1999) summarise data at –6075%. We have

measured for a typical New Zealand pasture diet of rye

grass (Lolium perenne) and white clover (Trifolium

repens), during Aorangi 2 and Aorangi 3 campaigns a

range of d13CH4 in 24 breath samples between �58.2%and �66.8% with a mean of �62.870.6 (s.e.m.). A

value of –62% has been used in our calculations.

4.3. Diurnality in sheep eructation

In using a nocturnal method we were concerned for

any bias that might occur due to diurnal patterns in

sheep emission. Judd et al. (1999) report on two

experiments where the daytime or afternoon emission

flux is 40% or 50% larger than the 24 h average flux.

These measurements were based on a small subset of the

flock at Aorangi assessed using the SF6 tracer method.

We repeated the small trial to test diurnal variability of

individual animals using the SF6 tracer technique at

Springston. Conversely, for six sheep over a period of 5

days, we found an average 1.2570.30 g head h�1 during

the working day (9:30–17:00) compared with

1.4470.35 g head h�1 (i.e. 15% more) for the period

(17:30–08:30). Fig. 8 shows that four of the six sheep

tested had significantly lower daytime emissions. During

the experiment, sheeps were observed eating and resting

during both day and night. Denmead et al. (2000)

summarised the results of other studies that show

methane emission is greatest during rumination and

rest and least when animals are actively grazing. In

general, the diurnal pattern of methane emissions is

linked closely to animal feeding patterns, which in turn

may be linked to times of availability of fresh feed. Our

trial results highlighted that there is the possibility of

significant differences between sites and flocks, such that

daytime emissions may not always be largest. For this

reason, we have not applied any correction in scaling to

a 24 h average from our nocturnally based estimates.

5. Conclusions

As with all the micrometeorological approaches, care

needs to be taken in sampling representative concentra-

tions and this will always be a difficulty when these

methods are applied to an inhomogeneous source

presented by free-roaming animals within a poorly

mixed nocturnal boundary layer. With the flocks we


12:00 18:00 00:00 06:00

Time of day

0

20

40

60

Hei

ght

(m)

174

2

1745

1750

1800 1800

1742 ppbv 1745 ppbv 1750 ppbv1800 ppbv 1850 ppbv 1900 ppbv

1950 ppbv 2000 ppbv 2050 ppbv

2100 ppbv 2150 ppbv 2200 ppbv

Sonde mixing height Bulk Ri

-0.2

0.3

0.8

1.3

1.8

2.3

Bul

k R

icha

rdso

n nu

mbe

r (4

m)

12:00 15:00 18:00 21:00 00:00 03:00 06:00 09:00 12:00

Time of day

0

20

40

60

Hei

ght (

m)

1721.0

1725.0

1730

.0

1730

.0

1721 ppbv1725 ppbv1730 ppbv1735 ppbv

Sonde mixing heightRi

-0.05

-0.01

0.03

0.07

Ric

hard

son

Num

ber

(3m

)

(a)

(b)

Fig. 7. (a) Modelled methane vertical profiles 10m downwind of the Aorangi paddock on N2. Background concentration 1740 ppbv.

(b) Modelled methane vertical profiles 10m downwind of the Springston paddock on N5. Background concentration 1720 ppbv.


have measured, the observed ‘between animal’ varia-

bility in emission was quite large (coefficient of variation

up to 25%). If high- and low-emitters are evenly

distributed within the flock, an advantage of the

proposed method is that it performs some spatial

averaging. In this assessment of the IDT for ruminant

methane emission measurement, the advantages of

providing a second somewhat independent and specific

assessment of sheep methane emission at the paddock

scale need to be considered against the added complica-

tion and expense of d13C determination. However, as the

technology develops for precise methane isotopic

analysis of small air samples, more widespread use of

this isotope dilution/mass balance approach is likely.

The IDT technique requires a careful strategy to ensure

representative samples are collected, especially with the

advecting technique where the upwind/downwind con-

trasts in d13C are small. In this study of nocturnal

boundary layer budget techniques, good agreement in

flux estimates to within a factor of 2 was achieved

compared with the ‘‘bottom-up’’ individual animal

measurements using the SF6 tracer technique. This

factor was closer to unity under ideal sampling

conditions and is considered to be excellent given the

many sources of uncertainty discussed above.

Acknowledgements

This research was funded by the New Zealand

Foundation for Research, Science and Technology

(FRST) contract CO9636 from the Landcare Research

programme ‘‘Greenhouse gas emissions from the terres-

trial biosphere’’. The FTIR measurements and develop-

ment of GC-IRMS techniques were made by the

National Institute of Water and Atmospheric Research

through ‘non-specific output’ funding.

Thanks are due to the many who made these

measurements possible including Ross Martin, Robert

Knobben, Andrew McMillan and Errol Lewthwaite at

NIWA and to Bill Ussler (currently University of North

Carolina), for initiating the work. Support was provided

at Aorangi Farm by AgResearch and thanks are due to

Alan Garrett and Brian Alison for accommodating our

research at Hollymount Farm, Springston. Finally we

thank the two anonymous reviewers for their useful

comments.

References

Andreas, E.L., Gosz, J.R., Dahm, C.N., 1992. Can long-path

FTIR spectroscopy yield gas flux measurements through a

variance technique. Atmospheric Environment 26A,

225–233.

Bergamaschi, P., Lubina, C., K .onigstedt, R., Fisher, H.,

Veltkamp, A.C., Zwaagstra, O., 1998. Stable isotope

signatures of methane from European landfill sites. Journal

of Geophysical Research 103, 8251–8265.

Beswick, K.M., Simpson, T.W., Fowler, D., Choularton, T.W.,

Gallagher, M.W., Hargreaves, K.J., Sutton, M.A., Kaye,

A., 1998. Methane emissions on large scales. Atmospheric

Environment 32, 3283–3291.

1 2 3 4 5 6

Sheep identification number

0.5

0.9

1.3

1.7

Ani

mal

em

issi

on (

g he

ad-1

h-1)

Day: 09:30 to 17:00 Night 17:30 to 08:30

Fig. 8. Hourly individual sheep methane emission for daytime and nighttime periods.


Bilek, R.S., Tyler, S.C., Kurihara, M., Tagi, K., 2001.

Investigation of cattle methane production and emission

over a 24-hour period using measurements of d13C and dDof emitted CH4 and rumen water. Journal of Geophysical

Research 106, 15405–15413.

Choularton, T.W., Gallagher, M.W., Bower, K.N., Fowler, D.,

Zahniser, M., Kaye, A., 1995. Trace gas flux measurements

at the landscape scale using boundary-layer budgets.

Philosophical transactions of the Royal Society of

London Series A: Physical Sciences and Engineering 351,

357–369.

Craig, H., 1957. Isotopic standards for carbon and oxygen

and correction factors for mass spectrometric analysis of

carbon dioxide. Geochimica et Cosmochimica Acta 12,

133–149.

Denmead, O.T., 1995. Novel meteorological methods for

measuring trace gas flux. Philosophical transactions of the

Royal Society of London Series A: Physical Sciences and

Engineering 351, 383–396.

Denmead, O.T., Harper, L.A., Freney, J.R., Griffith, D.W.T.,

Leuning, R., Sharpe, R.R., 1998. A mass balance method

for non-intrusive measurements of surface-air trace gas

exchange. Atmospheric Environment 32, 3679–3688.

Denmead, O.T., Leuning, R., Griffith, D.W.T., Jamie, I.M.,

Esler, M.B., Harper, L.A., Freney, J.R., 2000. Verifying

inventory predictions of animal methane emissions with

meteorological measurements. Boundary-Layer Meteorol-

ogy 96, 187–209.

Ferretti, D.F., Lowe, D.C., Martin, R.J., Brailsford, G.W.,

2000. A new gas chromatograph-isotope ratio mass spectro-

metry technique for high-precision, N2O-free analysis of

d13C and d18O in atmospheric CO2 from small air samples.

Journal of Geophysical Research 105, 6709–6718.

Gallagher, M.W., Choularton, T.W., Bower, K.N., Stromberg,

I.M., Beswick, K.M., Fowler, D., Hargreaves, K.J., 1994.

Measurements of methane fluxes on the landscape scale

from a wetland area in North Scotland. Atmospheric


Gupta, M., Tyler, S., Cicerone, R., 1996. Modeling atmospheric

d13CH4 and the causes of recent changes in atmospheric

CH4 amounts. Journal of Geophysical Research 101,

22923–22932.

Hanna, S.R., Briggs, G.A., Hosker, Jr., R.P., 1982. National

Technical Information Series: Handbook on Atmospheric

Diffusion, TIC-11223 ed. USDOE, Sprinfield, VA.

Hein, R., Crutzen, P.J., Heiman, M., 1997. An inverse modeling

approach to investigate the global atmospheric methane

cycle. Global Biogeochemical Cycles 11, 43–76.

Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der

Linden, P.J., Dai, X., Maskell, K., Johnson C.A. (Eds.),

2001. Climate Change 2001: The Scientific Basis.

Contribution of Working Group 1 to the Third Assessment

Report of the Intergovernmental Panel on Climate

Change. Cambridge University Press, Cambridge, United

Kingdom.

Johnson, K., Huyler, M., Westberg, H., Lamb, B., Zimmer-

man, P., 1994. Measurement of methane emission from

ruminant livestock using a SF6 tracer technique. Environ-

mental Science and Technology 28, 359–362.

Judd, M.J., Kelliher, F.M., Ulyatt, M.J., Lassey, K.R., Tate,

K.R., Shelton, D., Harvey, M.J., Walker, C.F., 1999. Net

methane emissions from grazing sheep. Global Change

Biology 5, 647–657.

Kelliher, F.M., Reisinger, A.R., Martin, R.J., Harvey, M.J.,

Price, S.J., Sherlock, R.R., 2002. Measuring nitrous oxide

emission rate from grazed pasture using Fourier-transform

infrared spectroscopy in the nocturnal boundary layer.

Agricultural and Forest Meteorology 111, 29–38.

Kuhlmann, A.J., Worthy, D.E.J., Trivett, N.B.A., Levin, I.,

1998. Methane emissions from a wetland region within the

Hudson Bay Lowland: an atmospheric approach. Journal of

Geophysical Research 103, 16009–16016.

Lassey, K.R., Ulyatt, M.J., Martin, R.J., Walker, C.F.,

Shelton, I.D., 1997. Methane emissions measured directly

from grazing livestock in New Zealand. Atmospheric


Leuning, R., Baker, S.K., Jamie, I.M., Hsu, C.H., Klein, L.,

Denmead, O.T., Griffith, D.W.T., 1999. Methane emission

from free-ranging sheep: a comparison of two measurement

methods. Atmospheric Environment 33, 1357–1365.

Lowe, D.C., Brenninkmeijer, C.A.M., Brailsford, G.W.,

Lassey, K.R., Gomez, A.J., 1994. Concentration and 13C

records of atmospheric methane in New Zealand and

Antarctica: Evidence for changes in methane sources.

Journal of Geophysical Resarch 99, 16913–16925.

Lowe, D.C., Allan, W., Manning, M.R., Bromley, T.,

Brailsford, G., Ferretti, D., Gomez, A., Knobben, R.,

Mei, Z., Moss, R., Koshy, K., Maata, M., 1999. Shipboard

determinations of the distribution of 13C in atmospheric

methane in the Pacific. Journal of Geophysical Research

104, 26125–26135.

Mahrt, L., 1999. Stratified atmospheric boundary layers.

Boundary-layer Meteorology 90, 375–396.

Ministry for the Environment, 1997. Climate change—the New

Zealand response II. New Zealand’s Second National

Communication under the Framework Convention on

Climate Change. Ministry for the Environment, Wellington,

New Zealand, 191p.

New Zealand Climate Change Project, 2002. National inven-

tory report—greenhouse gas inventory 1990–2000. New

Zealand Climate Change Project, Wellington, 190p.

Okada, S., Tezuka, M., 1989. Some problems of estimation of

Carbon Stable Isotope Ratio of methane in natural gases

and in cuttings gases. Journal of the Japanese Association

for Petrolium Technology 54, 1.

Quay, P., Stutsman, J., Wilbur, D., Snover, A., Dlugokencky,

E., Brown, T., 1999. The isotopic composition of atmo-

spheric methane. Global Biogeochemical Cycles 13,

445–11461.

Rust, F., 1981. Ruminant methane delta (13C/12C)

values: Relation to atmospheric methane. Science 211,

1044–1046.

Stevens, C.M., Engelkemeir, A., 1988. Stable carbon isotopic

composition of methane from some natural and anthro-

pogenic sources. Journal of Geophysical Research 93,

725–733.

Thom, A.S., 1975. Momentum, mass and heat exchange of

plant communities. In: Monteith, J.L. (Ed.), Vegetation and

the Atmosphere. Academic Press, London.

VEPA, 1986. The Ausplume Gaussian Plume Dispersion

Model. Victorian Envionmental Protection Authority,

Melbourne, Victoria.


Wahlen, M., 1994. Carbon dioxide, carbon monoxide and

methane in the atmosphere: abundance and isotopic

composition. In: Lajtha, K., Michener, R.H. (Eds.), Stable

Isotopes in Ecology and Environmental Science. Blackwell

Scientific Publications, Oxford.

Wratt, D.S., Gimson, N.R., Brailsford, G.W., Lassey, K.R.,

Bromley, A.M., Bell, M.J., 2001. Estimating regional

greenhouse gas emissions from agriculture using aircraft

measurements of concentration profiles. Atmospheric



boundary-layer isotope dilution/mass balance methods for measurement of nocturnal methane emissions...

Documents