economic impact of heat stress

Economic Impact of Heat Stress

N. R. St-PierreThe 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 Tu ans Hl.

• T and H integrated into a Temperature-Humidity Index (65% dry-bulb temperature, 35% wet-bulb temperature).


WeatherTwo 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 LossesDairy Cows

• Threshold at 70o THI (e.g., 75o F, 50% H)• DMI loss = 0.0760 x (THIMax-70)2 x D• Milk loss = 0.1532 x (THIMax-70)2 x D

where D = Proportion of a day above threshold

• PR = 0.20 - 0.0009 x Heatload• 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 x Heatload)


WeatherTwo Integrative Variables

(THIMAX – 70)2


Economic LossesDairy Cows

• Threshold at 70o THI (e.g., 75o F, 50% H)• DMI loss = 0.0760 x (THIMax-70)2 x D• Milk loss = 0.1532 x (THIMax-70)2 x D

where D = Proportion of a day above threshold

• PR = 0.20 - 0.0009 x Heatload• 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 x Heatload)


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

6684

55

40

68

58


Average Maximum Relative Humidity - July

94

74

47

94

81

8289


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 CowsNo Cooling - JULY

12351086

90

251

194

Loss in lbs/month Copyright 2013, N. St-Pierre, The Ohio State University

Gain Losses - Poultry BroilersNo 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 CowsMinimum Cooling - Annual Basis

1356

213

112140

1310


Total Cost - Dairy CowsMinimum Cooling- Annual Basis, in million $

199

Cost in million $Cost in million $

137

47

2053

69


Total Cost - Dairy CowsSprinklers - Annual Basis, in million $

34

47

199

104

35 12


Optimal System - Dairy Calves No Cooling Fans Sprinklers Evaporative Cooling


Optimal System - Dairy Cows No Cooling Fans Sprinklers Evaporative Cooling


Optimal System - Poultry Layers No Cooling Fans Tunnel Evaporative Cooling


Optimal System - Poultry Turkeys No Cooling Fans Tunnel Evaporative Cooling


Optimal System - Swine Sows No Cooling Fans Sprinklers Evaporative Cooling


Optimal System - Swine Feeder Pigs No Cooling Fans Sprinklers Evaporative Cooling


Economic Efficiency of Heat Abatement SystemsCost of Optimal System Cost of No Cooling

0.46

0.71

0.75

0.62

0.61

0.73

0.870.87

0.900.79

0.86

0.82 0.73

0.770.69

0.64

0.710.91

0.67

0.59 0.79

0.74

0.70

0.610.66

0.75 0.62

0.64

0.72

0.65

0.630.67

0.650.760.71

0.79

0.590.52

0.75


TX MO NE OK SD

Optimal System None None None None NoneDMI 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 CowsEconomic Losses (Million $)Five Largest Producing States


TX KS NE CO OK

Optimal System None None None None NoneDMI 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 FinishEconomic Losses (Million $)Five Largest Producing States


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 CowsEconomic Losses (Million $)

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 SowsEconomic Losses (Million $)Five Largest Producing States


NC IA MN IL MO

Optimal System None None None None NoneDMI 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 FeederEconomic Losses (Million $)Five Largest Producing States


Total Cost of Heat Stressto 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


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

kd α Δ 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


The End

economic impact of heat stress

Education

ohio state university91

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lbsmonth copyright

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