LOW WIND SPEED WIND DIRECTION FREQUENCIES BASED
CALCULATION METHOD FOR LIVESTOCK SEPARATION
DISTANCES
1
Johan Meline1
Tonkin Consulting, 66 Rundle St, Kent Town 5067 SA, Australia
Abstract
In calculation of separation distances for any purpose it is desirable to achieve an as
accurate prediction as possible at the smallest possible effort and cost. This paper
demonstrates how wind direction frequencies for low wind speeds can be applied as S
factors in calculation of separation distances for livestock applications.
Keywords: separation distance, S factor, wind direction frequencies, odour impact, live stock
1. Introduction
It can be expensive for pig producers to get an
odour impact assessment conducted for calculation
of required separation distances for a piggery
development. The costs can be particularly
significant for smaller scale pig producers when
odour modelling is required.
The National Environmental Guidelines for
Piggeries (NEGP) specifies three levels of
assessment methods for calculation of separation
distances. The new improved method presented in
this paper is based the simplest assessment
method with an additional wind direction dependent
S factor. This incorporates an element of local
climatological factors in the assessment at low or
no extra cost compared to the odour dispersion
modelling based assessment currently required for
achieving a similar result.
2. Separation Distance Calculation
Methods
2.1 Current Methods
Currently the National Environmental Guidelines for
Piggeries specifies three methods for calculation of
separation distances (NEGP 2006):
• Level 1: This assessment is based on S factors
for types of piggery, number of pigs, piggery
siting, surface roughness and terrain effects and
produces separation distances that can be
adjusted in different directions depending on for
instance surface roughness. Local climatological
conditions are not included.
• Level 2: This assessment is based on generic
dispersion modelling with AUSPLUME and
standard
odour
emission
rates
and
representative meteorological data.
CASANZ 2009 Conference - Perth - 6 - 9 September, 2009
Paper 82
• Level 3: This assessment is an extension of the
Level 2 method based on site specific odour
emission rates and meteorology.
The Level 1 method is less accurate and more
conservative than the Level 2 and Level 3 methods
with the Level 3 methods being the most accurate.
While a Level 1 assessment is inexpensive and
uncomplicated a Level 2 or 3 assessment can be
expensive especially for a smaller pig producer.
2.2 Description of New Improved Method
The new improved method (referred to as Level 1.5
in figures below) is an expansion of the Level 1
method with an additional wind direction dependent
S factor that incorporates an element of local
climatological factors in the assessment.
This method produces a conservative version of
contours similar in shape to the separation
distances normally produced by a Level 2
assessment based on dispersion modelling, but
without any modelling required.
The principle behind the method relies on
AUSPLUME’s sensitivity to wind speed for
concentration calculations and the inherent
relationship between results percentiles and the
threshold wind speed for which dispersion
conditions contribute to the calculation of the result
for the percentile. When dispersion modelling
results are presented for a certain percentile, the
results are linked to a certain threshold of low wind
speeds. The higher the results percentile the lower
the wind speed threshold. Besides stability class,
wind speed is the dispersion parameter with the
greatest impact on concentrations for ground level
emissions in AUSPLUME. This has been
demonstrated in Figure 1 below.
60
Odour Concentration (OU)
50
40
30
C
20
F
B
10
E
A
D
0
0
1
2
3
4
5
6
7
8
9
10
11
12
Wind Speed (m/s)
Figure 1 Wind speed impact on
concentration predicted in AUSPLUME.
Figure 2 Compass directions for S factors
odour
The assessment criteria for the NEGP Level 2
and Level 3 methods are (NEGP 2006):
• 3 OU, 98%, 1 hour average for a rural dwelling
• 2 OU, 98%, 1 hour average for a rural
residential receptor
• 1 OU, 98%, 1 hour average for a town receptor.
For the NEGP assessment criteria relying on the
98th percentile, the threshold wind speed was found
to be close to 3 m/s for the South Australian
meteorological 12 months hourly data sets used in
the study.
Attempts have been made in the past to
incorporate S factors for prevailing wind directions
but these attempts have not resulted in satisfactory
predictions of odour footprints. This is most likely
due to the frequency of higher wind speed winds in
prevailing wind directions which do not contribute to
dispersion conditions represented in high percentile
odour modelling results.
The S factors for the improved method are
applied to 16 compass point directions as illustrated
in Figure 2 below to provide smooth contours.
The Level 1 separation distance calculation
method details have not been presented in this
paper since the method is described in full in the
NEGP (NEGP 2006). For the improved method an
S factor for each of the 16 compass points is added
to the NEGP equation to calculate the separation
distance for each direction.
The steps for calculation of the compass point
direction S factors have been described below:
1. Calculation of frequencies of wind speed hours
for each of the 16 compass directions for wind
speeds below a certain threshold wind speed
for 12 months of hourly wind speed and wind
direction data.
2. Normalization of the wind direction frequencies.
3. Addition of a safety factor of 20% of the Level 1
separation distance with a limit of 100%
4. 180º reversing of S factors to give result down
wind based on wind directions.
5. Multiplication of the S factors with the Level 1
separation distances.
For the method development work an Excel
spreadsheet was developed to read meteorological
data, to calculate the S factors and to write Atlas
Boundary files for the separation distance contour
shapes to allow for simplified evaluation against the
AUSPLUMEv6 dispersion modelling results in
Surfer8.
2.3 Evaluation of the Improved Method
The improved method separation distance contour
results were compared and evaluated against Level
2 separation distance contours for the 9
meteorological data sets in Table 2 below.
CASANZ 2009 Conference - Perth - 6 - 9 September, 2009
Paper 82
2.3.1 Type of Piggery used in Assessment
The method evaluation was applied to a deep litter
system type piggery. The Level 1 separation
distances were calculated for 19,284 Standard Pig
Units (SPU) and a S1 factor for effluent removal
and treatment of 0.63, the S2 factor according to
receptor type and a S3 factor for type of terrain of
1. The Level 1 separation distances are presented
below in Table 1.
Table 1 Level 1 Separation Distances
Receptor type
Separation Distance
Town
3,582m
Rural Residential
2,149m
Rural Dwelling
1,648m
2.3.2 Meteorological Data Files Used in the Study
The study was mainly conducted with SA EPA
meteorological data sets selected for areas with
significant pig production. Other data sets were
included for evaluation of how the method performs
for lower average wind speed data sets.
direction
direction
frequency
SN
SNNE
SNE
SENE
SE
SESE
SSE
SSSE
SS
SSSW
SSW
SWSW
SW
SWNW
SNW
SNWN
67%
67%
72%
88%
100%
53%
32%
18%
32%
40%
64%
65%
64%
55%
54%
54%
Table 2 Meteorological data used in the study
Weather
Type of data
Average Data origin
station
wind
location
speed
Murray
Bridge
Cavendish
(WA)
Observational
Observational
Observational
Observational
Observational
Observational
4.77m/s
4.36m/s
3.88m/s
4.34m/s
3.91m/s
4.15m/s
SA EPA
SA EPA
SA EPA
SA EPA
SA EPA
SA EPA
TAPM
generated
Observational
4.08m/s
3.00m/s
Observational
2.87m/s
Tonkin
Consulting
Tonkin
Consulting
WA Department
of Environment
and
Conservation
6000
5000
4000
L2-T
L2-RR
(metres)
Roseworthy
Strathalbyn
Renmark
Mt Gambier
Padthaway
Adelaide
Airport
Brinkley
direction
frequency incl.
safety factor
87%
87%
92%
100%
100%
73%
52%
38%
52%
60%
84%
85%
84%
75%
74%
74%
L2-RD
L1.5-T
3000
L1.5-RR
L1.5-RD
2000
1000
L1-T
L1-RR
L1-RD
0
0
1000
2000
3000
4000
5000
6000
L1-T
- Level 1 Separation Distance for Town
L1.5-RR - Level 1.5 Separation Distance for Rural Residential
L2-RD - Level 2 Separation Distance for Rural Dwelling
Figure 3 Achieved reduction of separation distance
3. Results
The Renmark results were selected for
presentation in this paper since they displayed a
medium level of conservatism in the separation
distances. The S factors for Renmark are
presented in Table 3 and the resulting separation
distances are presented in Figure 3. In Table 3, the
S factors are given for both with and without the
additional safety factor providing additional
conservatism in the separation distance calculation.
Table 3 S factors for Renmark
Compass point
S factor wind
S factor wind
CASANZ 2009 Conference - Perth - 6 - 9 September, 2009
Paper 82
In Figure 3 the Level 1 separation distances for the
three receptor types is represented by the circular
shaped contours, the Level 2 separation distances
are represented by the three filled areas and the
results for the improved method are represented by
the black contour lines.
4. Discussion
As can be see in Figure 3 a reduction in the
separation distance can be achieved with the
improved Level 1 method. The separation distance
reduction is significant but still conservative in
certain directions and correlate well with Level 2
predictions of separation distances.
The threshold wind speed which is the key to the
accuracy of the method was found to be 3 m/s for
the South Australian data sets with average annual
wind speeds in the range between 3.88 m/s and
4.77 m/s.
The higher the average annual wind speed
compared to the threshold wind speed the more
conservative the results. Since a wider range of
data sets with lower annual average wind speeds
were not available for the study a suitable lower
threshold wind speed for lower annual average
wind speeds could not be evaluated.
5. Conclusions
The improved method demonstrates how local
climatological factors such as wind direction
frequencies for low wind speeds can successfully
be incorporated in a Level 1 assessment with S
factors.
The improved method offers better initial
assessment and incorporates local climatology in
consideration of suitability of sites for intensive
livestock breeding. This assists in the planning and
consultation process at an early stage at little or no
additional development costs.
The method can be applied to any 12 months
wind data set. However, evaluation against a Level
2 assessment provides good evidence of the
predictions. The best control of the method is
probably gained by release of the S factors for pig
production intensive areas by a Government or
Industry Interest Organisation that can provide
evaluation of the data sets for livestock intensive
areas.
6. Acknowledgements
The development of the method described in this
paper was funded by PIRSA and APL and has
been reviewed by the South Australian EPA.
7. References
National Environmental Guidelines for Piggeries
(NEGP) August 2006, Australian Pork Limited
CASANZ 2009 Conference - Perth - 6 - 9 September, 2009
Paper 82