Economic Impact of Heat Stress

Economic Impact of Heat Stress
N. R. St-Pierre
The Ohio State University

Objectives
• To present a simple model for quantifying
financial losses due to heat stress across all
major commercial livestock industries in the
U.S.,
• To peek into the future:
Global warming
Increase in animal productivity

Model Overview
• Used historical weather data to quantify the
multivariate distribution of temperature and
relative humidity for each of the 48 lower States.
• Summarized research data to quantify the
relationships between magnitude of heat stress,
duration of heat stress, and expected
performance across 10 livestock classes.

Weather
• Number of reporting stations: 257
• Earliest reports start between 1871 and 1932
• Data include daily:
Minimum and maximum temperature (T)
Minimum and maximum relative humidity (H)
Rain and snow precipitation
Snow cover

Weather
• Data were summarized by State and by month:
Mean, variance and covariances of:
o Minimum temperature (Tl)
o Maximum temperature Tu)
o Minimum relative humidity (Hl)
o Maximum relative humidity (Hu)

Weather
• Within day changes in T and H modeled as sine
functions with simultaneity of Tl and Hu, and of
Tuans Hl.
• T and H integrated into a Temperature-Humidity
Index (65% dry-bulb temperature, 35% wet-bulb
temperature).

Weather
Two Integrative Variables

Livestock Classes

Economic Losses
• For each livestock class:
DMI loss (economic gain)
Production loss
Days open loss
Reproductive culling loss
Mortality loss

Economic Losses
Dairy Cows
• Threshold at 70o THI (e.g., 75o F, 50% H)
• DMI loss = 0.0760 x (THIMax-70)2x D
• Milk loss = 0.1532 x (THIMax-70)2x D
where D = Proportion of a day above threshold
• PR = 0.20 - 0.0009 xHeatload
• DO loss = 164.5 - 184.5 PR + 29.38 PR2 - 128.75
• RCullRate = 100 - 102.7(1-1.10109 EXP(10.1874 x PR)
• Pmonthlydeath = 0.000855 EXP(0.00981 xHeatload)

Weather
Two Integrative Variables
(THIMAX – 70)2

Unit Costs for Five Loss Categories

Description of Cooling Systems
Minimal
(Fans)
Moderate
(Sprinklers)
Aggressive
(Evaporative)
Beef Cows Fans +Sprinklers Evaporative
Beef Finish Fans +Sprinklers Evaporative
Dairy Calves Fans +Sprinklers Evaporative
Dairy Cows Fans +Sprinklers Evaporative
Dairy Yearlings Fans +Sprinklers Evaporative
Poultry Broilers Fans Tunnel Evaporative
Poultry Layers Fans Tunnel Evaporative
Poultry Turkey Fans Tunnel Evaporative
Swine Feeders Fans +Sprinklers Cool Cells
Swine Sows Fans +Sprinklers Cool Cells

Reduction in THI from Fan Cooling

Reduction in THI from Sprinkler Cooling

Reduction in THI from Evaporative Cooling

Cooling Costs
• Capital Cost
10 year depreciation
8% interest
2-5%/year for maintenance
• Operating Cost
$0.09/kWh
$0.01/h per unit for water
0.65 kW/h for fans (92 cm), 2.55 kW/h for
evaporative cooling

Average Minimum Temperature - July
71.7
72.1
68.2
67.1
69.8
53.6
51.4
59.0
60.6

Average Maximum Temperature - July
94.8
100.1
77.4
80.8
92.592.5
90.9
91.2

Average Minimum Relative Humidity - July
56
22
14
66
84
55
40
68
58

Average Maximum Relative Humidity - July
94
74
47
94
81
82
89

Average Minimum THI - July
68.9
65.3
51.6
60.7
72.6
58.3
66.2
65.8

Average Maximum THI - July
86.0
81.5
76.2
75.2
81.1
73.7
81.1
91.6

Milk Production Losses - Dairy Cows
No Cooling - JULY
12351086
90
251
194
Loss in lbs/month Copyright 2013, N. St-Pierre, The Ohio State University

Gain Losses - Poultry Broilers
No Cooling - JULY
18.3
Loss in lbs/month per 1000 birds
7.5
3.1
1.3
12.1
12.8

Total Cost per Animal - Dairy Cows
Minimum Cooling - Annual Basis
1356
213
112140
1310

Total Cost - Dairy Cows
Minimum Cooling- Annual Basis, in million $
199
Cost in million $Cost in million $
137
47
2053
69

Total Cost - Dairy Cows
Sprinklers - Annual Basis, in million $
34
47
199
104
35
12

Optimal System - Dairy Calves
No Cooling Fans Sprinklers Evaporative Cooling

Optimal System - Dairy Cows

Optimal System - Poultry Layers
No Cooling Fans Tunnel Evaporative Cooling

Optimal System - Poultry Turkeys
No Cooling Fans Tunnel Evaporative Cooling

Optimal System - Swine Sows

Optimal System - Swine Feeder Pigs

Economic Efficiency of Heat Abatement Systems
Cost of Optimal System Cost of No Cooling
0.46
0.71
0.75
0.62
0.61
0.73
0.87
0.87
0.90
0.79
0.86
0.82 0.73
0.77
0.69
0.64
0.71
0.91
0.67
0.59
0.79
0.74
0.70
0.61
0.66
0.75
0.62
0.64
0.72
0.65
0.63
0.67
0.650.760.71
0.79
0.59
0.52
0.75

TX MO NE OK SD
Optimal System None None None None None
DMI Loss 0 0 0 0 0
Gain Loss 0 0 0 0 0
DO Loss 15.5 2.2 1.5 3.6 1.0
Repro Cull Loss 0 0 0 0 0
Death Loss 17.7 2.9 2.0 4.4 1.3
Capital Cost 0 0 0 0 0
Operating Cost 0 0 0 0 0
Total Cost 33.2 5.1 3.4 8.0 2.2
Beef Cows
Economic Losses (Million $)
Five Largest Producing States

TX KS NE CO OK
DMI Loss (34.8) (12.2) (10.8) (1.9) (3.8)
Gain Loss 162.0 57.1 50.5 8.9 17.6
DO Loss 0 0 0 0 0
Death Loss 19.0 5.0 4.5 0.6 1.9
Total Cost 146.6 49.8 44.2 7.6 15.7
Beef Finish

CA WI NY PA MN
Optimal System Sprinkler Sprinkler Sprinkler Sprinkler Sprinkler
DMI Loss (31.6) (10.8) (3.6) (10.0) (6.2)
Gain Loss 103.2 35.3 11.6 32.7 20.4
DO Loss 23.3 11.4 4.5 8.9 5.7
Repro Cull Loss 7.4 3.2 1.2 2.8 1.7
Death Loss 2.3 1.0 0.4 0.9 0.5
Capital Cost 13.7 11.6 5.9 5.3 4.6
Operating Cost 18.3 11.6 5.4 7.3 4.8
Total Cost 136.6 63.3 25.4 47.9 31.5
Dairy Cows
Five Largest Producing States (2002)

NC IA MN IL MO
Optimal System Sprinkler Sprinkler None Sprinkler Sprinkler
DMI Loss 0 0 0 0 0
Gain Loss 0 0 0 0 0
DO Loss 10.2 6.8 4.0 3.5 5.3
Death Loss 0.1 0.1 0 0 0.1
Capital Cost 3.7 3.2 0 1.4 1.2
Operating Cost 5.4 3.3 0 1.7 2.0
Total Cost 19.3 13.4 4.1 6.7 8.5
Swine Sows

NC IA MN IL MO
DMI Loss (12.0) (7.5) (2.2) (3.9) (4.9)
Gain Loss 54.0 33.8 10.0 17.4 22.1
DO Loss 0 0 0 0 0
Death Loss 0.9 0.5 0.1 0.3 0.4
Total Cost 42.9 26.8 7.9 13.8 17.6
Swine Feeder

Total Cost of Heat Stress
to U.S. Livestock Industries
W/o Heat Abatement Systems: 2.7 billion $/yr
W Optimal Systems: 1.9 billion $/yr

Impact of Climate Change on Future Costs
An honest discussion on the difficulties
of forecasting weather and temperatures

Temperature Forecasting Issues
• IPCC forecasts failed to abide by seventy-two of
eighty-nine forecasting principles1:
Agreement among forecasters is not related to
accuracy
The complexity of the global warming problem
make’s forecasting a fool’s errand – The more
complex you make the model the worse the forecast
gets.
The forecasts do not adequately account for the
uncertainty intrinsic to the global warming problem.
Kester C. Green and J. Scott Armstrong. 2007. Global warming: Forecast by scientists verses
scientific forecasts. Energy and the Environment 18:718.

Temperature Forecasting Issues
“You cannot assume that a model with millions
and millions lines of code, literally millions
of instructions, that there isn’t a mistake in there”
K. Emmanuel, M.I.T.

Predictions and Forecasts
Data driven predictions can succeed – and they
can fail. It is when we deny our role in the
process that the odds of failure rises.
Nate Silver.

We have a prediction problem. We love to
predict things – and we aren’t very good at it.
Nate Silver.

I am a DENIER!

I am a DENIER!
I can live with doubt and uncertainty and not
knowing. I think it is much more interesting to
live not knowing than to have answers which
might be wrong.
Richard P. Feynman

The Essence of Science
When a scientist doesn’t know the answer to a
problem, he is ignorant. When he has a hunch as
to what the result is, he is uncertain. And when
he is pretty darn sure of what the result is going
to be, he is in some doubt.
Richard P. Feynman

A responsibility
If we suppress all discussion, all criticism,
saying, “This is it boys!”… and thus we doom
man for a long time to the chains of authority,
confined to the limits of our present imagination.
Richard P. Feynman

A Principled Scientist
It’s a kind of scientific integrity, a principle of
scientific thought that corresponds to a kind of
utterly honesty – a kind of leaning over
backwards.
Richard P. Feynman

U.S. Temperature Data

Trends in Hurricane Intensity

Great Lakes Ice Coverage

Arctic Ice Extent in September

Oceans Acidification

Pteropods
Seawater with pH and carbonate projected for the year 2100

The conditions of the universe are knowable only
with some degree of certainty.

Two strikes in weather forecasting:
• The systems are dynamic
The behavior of the system at one point in time
influences its behavior in the future.
• The systems are nonlinear
They abide by exponential rather than additive
relationships.

Climate Forecasts
• How much uncertainty is in the forecast?
• How right or wrong have the predictions been so
far?
• How much have politics and other perverse
incentives undermined the search for scientific
proof?
Healthy skepticism toward climate predictions!

How Cows Dissipate Heat
• Conduction
• Convection
• Radiation
• Evaporative cooling

Flow of Energy (Mcal/day)
40 lbs 120 lbs
Gross Energy 73.4 135.7
Feces 25.7 40.7
Digestible Energy 47.7 95.0
Urine 5.6 11.0
Gas 3.4 6.1
Metabolizable Energy 39.0 77.9
Heat 26.2 39.5
Milk Energy 12.8 38.4

A Simplified Cow...
Ta Te
Eg
>
Ed
The cow The environment
kd
kdαΔ T
Δ T

Increased Productivity vs. Global Warming
• The current IPCC forecasts predict that the
temperatures might increase by 1.2 °F by 2050.
• Dairy productivity has increased at a rate of 318
lbs/cow per year since 1980.

• Current animal productivity averages ~ 70
lbs/cow per day nationally.
Results in 30.1 Mcal/cow per day in heat energy.
• Assuming that improvement in productivity will
be maintained at 300 lbs/cow per year, the
average U.S. dairy will be producing 102
lbs/cow per day in 2050
Results in 35.7 Mcal/cow per day in heat energy
• The projected improvement in potential
productivity will lower the THI-threshold from
70 to 64.

• The current IPCC forecasts predict that the
temperatures might increase by 1.2 °F by 2050.
• The increased projected productivity has a net
“warming effect” equivalent to 6 °F by 2050.
Increased potential productivity will have
about 5 times more impact on heat stress in
dairy cattle than global warming.

The Real Issue
• Current cooling systems are not very energy
efficient and they all rely on significant amounts
of water being used.

The Real Issue
• Current cooling systems are not very energy
efficient and they all rely on significant amounts
of water.
Will energy costs outpace our ability to cool
animals?
Will water availability restrict our ability to cool
animals?

Closing Comments

Economic Impact of Heat Stress

Economic Impact of Heat Stress

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