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Assessment of the energetics of human labor
Agriculture, Ecosystems and Environment, 32 (1990) 257-272
257
Elsevier Science Publishers B.V., Amsterdam
Assessment of the energetics of human labor Mario Giampietro t and David Pimentel2 ~lstituto Nazionale della Nutrizione, Unit of Special Food Technology, via Ardeatina 546, 00178 Rome (Italy) 2Department of Entomology, Comstock Hall, Cornell University, Ithaca, NY 14853-0999 (U.S.A.) (Accepted for publication 24 April 1990)
ABSTRACT Giampietro, M. and Pimentel, D., 1990. Assessment of the energetics of human labor. Agric. Ecosystems Environ., 32: 257-272.
The energetic analysis of farming systems implies an assessment of the energetics of human labor. The energy cost of I h of human labor is generally estimated according to its physiological requirement (the hierarchical level at which the assessment is made is at the individual level). A different way of describing the interaction between human society and the ecosystem is presented in this paper (assessment referred to the society level). The shift from the individual level to the societal level provides a new perspective when assessing the energetic efficiency of farming. For example, the power level of the system becomes a new and important parameter to consider. Numerical examples illustrate the proposed approach.
INTRODUCTION
The energetic analysis of farming systems deals in part with the important problem of assessing the energetics of human labor. The difficulty in assessing human labor begins with the choice of the boundaries of the system. In fact, different boundaries can provide different definitions for human labor (e.g. labor is traditionally considered an energetic input for cultivated crops; on the other hand, at the farm level, the requirement for human labor represents an energetic cost). Another problem is provided by the economic measure of the labor input. In a developed society, the monetary cost of manpower is high. This means that in spite of the small human labor input to the energetic budget of a farm, the requirement of human labor can heavily affect the overall economics of the system. In developing societies, however, the low level of power and low-cost labor results in the extensive use of labor in agriculture. Human labor provides both a flow of applied power and a flow of information. The quality and quantity of this information can alter the value of the labor. In societies with a high level of technological capital, humans direct the flow of machine power, while in poor traditional societies humans pro0167-8809/90/$03.50
© 1990 - - Elsevier Science Publishers B.V.
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vide the flow of power as well. This means that one hour of human labor in a western farm or in a developing country farm implies the delivery of different quantities of power. Also, the cost of power generation, defined as the quantity of energy input (joules) required to deliver a joule of applied power, is dramatically different in these two systems. For this reason, we feel that a discussion about boundaries and parameters describing the energy efficiency of agricultural labor is needed. Thus, the objective of this paper is to analyze ( 1 ) the concept of energy efficiency in farming systems and (2) the factors affecting the embodied energy ( = the energetic cost) of human labor. E N E R G Y E F F I C I E N C Y IN A G R I C U L T U R E
Energy efficiency In general, efficiency is calculated as a ratio (output/input) with respect to a single parameter. On the other hand, the typical pattern found when analyzing different efficiencies in farming systems is that an increase in efficiency with respect to one parameter implies a decrease in efficiency with respect to other parameters (e.g. maximization of economic profit vs. minimization of risk, maximization of crop yield vs. minimization of ecosystem degradation, etc. ). Therefore an objective definition of energy efficiency needs an absolute and quantifiable definition of what is best for the system. Odum ( 1971 ), examining the evolution of natural communities, suggested that the optimizing parameter for energy efficiency is the ratio between the quantity of information (the level of ecosystem organization maintained in steady state) and the quantity of energy dissipated. This indicator is perfectly consistent with the "dissipative structures theory" formulated by Nicolis and Prigogine (1977) for thermodynamic systems not in equilibrium. Ecosystems, living beings and human societies can be regarded as self-organizing systems able to maintain a defined level of complexity (their function/structure) because of the continuous dissipation of energy. Obviously, a challenge exists to assess information flows by this approach. However, we can describe the process of energy dissipation that leads to the maintenance of human society as follows. Humans invest applied power to alter ecosystems (Fig. 1 ), this energetic investment alters the organization of the ecosystem, producing a form of ecosystem less probable according to natural processes, but more profitable for humans. That is, human cultivation increases the quantity of harvestable biomass and the quantity of energy output harvested from the ecosystem per unit of area. The flow of energy output that the humans harvest from the ecosystem can be considered the return of human investment. Using the analogy
2 59
ASSESSMENT OF THE ENERGETICS OF HUMAN LABOR Solar energy
Energy dissipated by ecosystem
ECOSYSTEM
ENERGY INPUT taken fromthe ecosystem
--1 APPLIED POWER to alter the ecosystem
SOCIETY
b
I Level of energy expenditures of the society
Fig. 1. Energetic interaction human society-ecosystem.
with.an economic model, the cost of the energetic investment (the flow of applied power) can be calculated as the sum of current expenses (the energy required to generate the applied power) and fixed expenses, related to the maintenance of the capital needed to produce the investment (energy spent within the boundary of human society to maintain the societal structures). The level of energy expenditures resulting from this interaction (the level at which a dynamic equilibrium is reached between the energy invested and the energy harvested) would assess the level of technological development of this society (Giampietro and Pimentel, 1990a). Note (Fig. 1) that joules of applied power (AP) and joules of energy input (El) are different energy flows, with different costs (different levels of embodied energy).
Energy input, applied power and work done Power generation In order to produce applied power, we always lose energy in the conversion (e.g. ifa tractor's thermic engine has r/= 0.20, this means that only 20% of the joules of the fuel are converted to joules of applied power). Moreover, energy is spent in building and maintaining the structure that delivers power. This means that we can imagine the total energy requirement as the sum of two different flows of energy: one flow (N) used directly to generate power and another flow (M) calculated as the energy spent in the construction and maintenance of the structure delivering power, discounted on its life span.
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For example, if a tractor has a ratio N/M= 2, this means that an increase of 30% has to be added to its fuel consumption to assess the energy requirement for its construction and maintenance (discounted on a 10-year life span). While the ratio r/, related to the direct conversion of energy input into power, can be considered generally constant according to the device used (e.g. thermic engine, human muscle, animal muscle), the incidence of the cost of maintenance of the structure (tr=N/M) can be dramatically affected by different factors (e.g. the case of human power generation was analyzed in Giampietro and Pimentel, 1990b).
Ratio work done~power applied The conversion of a joule of energy input into a joule of applied power is only the start. The ultimate goal is the conversion of applied power into final work. The quantities of work done by two different pumps using the same amount of applied power illustrates this point (Fig. 2). The work done per joule of applied power (work done/power applied) provides a quantitative measure of the difference in knowledge of the system in energy end use. Clearly, Pump B delivers ~ 16 times more water per unit of applied power.
Power thresholds Traditional farming systems based on human labor have a low level of power and therefore generally avoid peaks of labor demand. The multi-use of mulCurves of discharges/lift for two types of hand pumps t
~ - - ~ P
A basketpipe 2 persons B == swing hasculating I person
10 Discharge tons/hr 5
ump B
\ pump A I 1
I 2
lift (metres)
Hypothesizing the same device generating the power moving the pumps (human muscle) are obtained either by the labor of I person x l 0 hours or 2 persons x 5 hours
2.7 MJ
2.7 MJ
of Applied Power with the Pump A
--->
5
tons lifted 1 m
2.7 MJ
of Applied Power with the Pump B
---> 83
tons lifted 1 m
Comparing these data with the mechanical work-output : ton lifted 1 m = 10,000 joules of mechanical work and defining the ratio ~ = mechanical work/Applied Power 1
(/,
of pump A
O~
of pump B = 0.31
= 0.02
Fig. 2. Examples of different ratios of work output per unit of applied power.
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tiple crops and livestock, typical of traditional farming, often spreads the requirement of manpower through the year. On the other hand, developed agriculture with a high level of machine power is able to effectively deal with peak power demand that eventually minimizes the human labor input. In attempting to transfer modem agricultural technologies to developing countries, care must be exercised to avoid peak power demand. See Fig. 3 for an example of this problem with high-technology sorghum (graphs from Avery et al., 1978). Societies primarily based on manpower are limited by peak power constraints. Although utilizing men and women for different tasks and using draft animals will help in reducing peak power problems, the peak problem remains without machine power (Giampietro and Pimentel, 1990b). Rappaport (1971) writes, "I found that the performances of men and women in clearing the bush were surprisingly uniform. Although in an hour some women clear little more than 200 square feet and some of the more robust men clear nearly 300 square feet, the larger men expend more energy per minute than women. The energy input of each sex is approximately equal: harvest weeding
/
400--
300-
200--
100-
I I I I I jan feb mar apr m a y j u n
.I I I jul a u g s e p
f oct n o v d e c
Labor profile related to sorghum cultivation high yield, Central Niger (Avery et al. 1978)
400--
e~
300-. weeding 200
100
I I I I I I jan feb mar apr m a y j u n
I ~ I jul a u g s e p
I ~t
I I novdec
Labor profile related to sorghum cultivation traditional technique - Bush Tua~. 8, Central Niger (Avery et al. 1978)
Fig. 3. Labor profiles for sorghum production.
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some 0.65 kcal per square foot." The performances of men and women reported by Rappaport may be uniform in terms of energy requirement per unit of surface (29 000 J m -2 using the SI system), but the difference in labor done per unit time suggests a difference in the level of power delivery. This can be illustrated by comparing the performances of men and women in terms of energy expenditures per work done. Imagine defining the work as carrying 400 kg of sand upstairs 5 m in height. Our point is that this definition of work cannot be used to compare performances without a previous specification of power level. For example, we can do this work in three ways: (a) 5 trips carrying 80 kg; (b) 20 trips carrying 20 kg; (c) 100 trips carrying 4 kg. The high power level requirement of (a) would prevent many women performing the work. In this situation, the larger body size of men would give them an advantage. On the other hand, light repetitive work as in the third case (c) would give the advantage to women, who have a smaller body size and a slower metabolism. This implies less energy expenditure in terms of work done per energy input. This example illustrates that the performances in doing work can be affected by power level requirements. Unfortunately, the examples given are only estimates because the investigators who study work and human energy expenditures do not carry out their measurements including the power level parameter. The measures of energy consumption for a certain task, related to particular people, provide data related to the energy input required by the society, but do not assess the energy efficiency in converting food energy into applied power. This is surprising, because it is like comparing the performances of different trucks by measuring the gasoline consumed, without specifying distance, speed and load. E M B O D I E D E N E R G Y O F H U M A N LABOR
Since the first development of energy analysis, quantities of energy and measures of flow of energy in time have been often reported in terms of kcal and kcal day- 1 (or kcal h - 1, or kcal year- 1). Clearly, these are not the fight units to measure energy, in fact the International System of Units calls for joule when referring to quantities and watt in the case of flow joules in time. Unfortunately, the use of kcal is still widespread today, to the point that the assessment of energy requirements and the level of energy expenditure for humans and societies in the literature are often expressed in kcal. The same problem exists for the assessment of mechanical power, traditionally measured in agriculture in terms of horsepower (HP). In order to help readers not familiar with the measurement of energy and power in joules and watts, in our text we will provide the equivalent value in kcal or HP in parentheses after the correct value in SI units.
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Energy costs allocated to human labor When measurements are made of meat or milk production in agriculture, the energy required for the production of replacement animals is included in the analysis. We propose that a similar approach be used for calculating the energy inputs for human labor, i.e. children and the non-working force be included in all labor cost measurements. The gross energy consumed per capita should be included in the analysis. Thus the cost of applied power can be measured by the ratio of the gross energy requirement per capita of the society (i.e. the quantity of energy input that the society takes from the ecosystem) divided by the quantity of applied power per capita that the society delivers to the ecosystem in managing it. Using this approach to calculate the cost of power generation for human labor, we have Energy input =joules consumed by the society in order to have human laborers In this case, we are considering the total energy input, not just nutritional calories. For example, the biomass used by a human to cook (2 J of biomass are consumed per nutritional joule of cooked food), seeds, etc., should be included in the assessment of energy input Applied power = joules of muscular power delivered by human society
Benefits of this approach This approach of including total society in the energy cost of human labor enlarges the boundaries of the agricultural system. Obviously, this complicates the energy analysis~ The societal level of exosomatic power (exosomatic power is the power delivered in human activities without using human muscles, i.e. animal power, power provided by natural process and mechanical power) can alter the meaning of human labor in agricultural activities. For example, a U.S. farmer driving a 75-kW (100-HP) tractor has his muscular power multiplied 1000 times! When human labor becomes negligiblein terms of power input (the machines are providing power for the society), humans provide the information for accomplishing the job. Nevertheless, by coupling the cost of human labor to the level of energy expenditure of society we have a way to assess the role of humans in providing information to the system (in harnessing this exosomatic power). In fact, the change in the characteristic of human labor, typical of developed societies, can be measured by the dramatic increase in energy inputs that the society spends to sustain a worker. The high level of embodied energy in an hour of human labor also explains the high level of monetary cost of human labor in developed societies.
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The measure of human labor generally found in literature is based on the biological requirement of the human body; these data are generally expressed in nutritional energy required to provide an hour of labor. This equivalence does not consider the level of embodied energy of the nutritional joules (kcal) consumed by the worker e.g. 1000 J of meat are more expensive in caloric terms than 1000 J of sorghum, 10 J (kcal) of ecosystem biomass are generally required to produce 1 J (kcal) of meat. A U.S. worker lives in a society with a level of consumption of > 9700 W of energy expenditures per capita (this means 200 000 kcal d a y - 1 i.e. 8500 kcal of energy input per hour, all day long, every day). If we charge his/her energy expenditures on a yearly basis related to 2000 hours of labor (23% of the total year hours) we have 152 MJ (37 000 kcal ) of energy input are required to have an hour of labor. If we calculate the dependents of the worker (children, elderly and other non-working members of the population), an hour of human labor requires up to 250 MJ (60 000 kcal ) of energy input to the U.S. society. This is the reason why rich societies minimize the use of human labor, switching to machine power whenever possible. Commonly, the assessment of energetic measure of human labor based on nutritional requirements would provide more or less the same value for a U.S. worker and a Mali worker: in the range of 2-2.5 MJ (450-600 kcal) required per hour of labor. The energetic analysis used in assessing human labor based on differences in physiological energy requirements would provide only small TABLE l Use of human time in food system activities: Mali vs. U.S.A. Food security activities considered Food production (input labor of population in agriculture) Processing-distribution (input labor of workers in this sector) Home preparation (input labor of housekeepers not employed in the economic sector) Eating (time spent by everyone in having meals) Country
Hours spent 2
Mali U.S.A.
7.98 2.76
The people in the U.S.A. can devote the extra time (5220 h for 1000 people day -~ ) to earning high wages in other activities, independent of the food system. In this way (owing to the multiplicative effect of the power level generated by the use of a "fossil energy/machine" energy chain ), the society as a whole can have access to a higher quantity of resources per capita ~Giampietro and Pimentel, 1987. 2Total hours of human time spent in food security-related activities (per capita day- ~).
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265
differences in energetic cost between human labor in these two societies. We feel that such assessments are inadequate to analyze the dynamics of energy utilization within these societies. As noted before, the huge multiplicative effect of technology on human power enhances the importance of information provided by humans. In developed societies, the value of human labor (e.g. difference in salary) is not related to the quantity of muscular power applied, but is related more to the quality of the information utilized. The difference in level of power can also be used to study the differences in salary between developed and developing societies (e.g. the wide difference between the salaries of a farmer in New York State and in Mali). Table 1 shows the difference in human hours spent in food supply activities in U.S.A. and Mali societies, this difference can be explained by the different cost-opportunity of human labor. Clearly, in societies where the energetic investment of the society is rotated at a higher rate (9700 W is the steady state level of energy dissipation per capita at society level) the cost/return of 1 h of human labor must consequently be higher.
Applied power of human labor The quantity of applied joules that is delivered by human labor in the society (on a yearly basis) can be calculated as Level of human power per capita × hours of labor In order to quantify these parameters, we have to know populational and societal characteristics: sex ratio, age structure, body size, labor charge.
Human power We assume that 90 W is the power of an adult man (0.12 HP) and 60 W is the power of an adult woman (0.08 HP ). A difference in power of 30% has been assumed between men and women on the basis of different performances in sporting events (i.e. running and weight lifting in Suzuki et al., 1978 ) and in work output (Rappaport, 1971 ). However, these data are used to illustrate a methodology, an assessment of men and women's power performances is not the aim of this paper. The level of power (expressed in watts) per capita of human labor is given by Power level per capita = (Xm 90 + Xf 60) where XmdS the percent of working adult males and xf is the percent of working adult females. The existence of a non-working population (Xm+ Xf< 1 ) decreases the power level per capita (a maximum power level is obtained using a population of adults only, e.g. slaves). The sex ratio can affect the power level of a group of
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people (a maximum power level is obtained using only adult males, e.g. traditional army). With a standard ratio of 50% males/females, the power level of an average worker can be assumed to be 75 W ( ~0.1 HP). The value of 75 W is the standard equivalent used to compare manpower to agricultural machinery (Pimentel and Pimentel, 1979). However, using our approach, this value must be further decreased because of the non-working share of the population.
Labor per capita The quantity of hours worked per year can vary within a defined range: starting from a minimum value of < 900 h year- ~ for hunters and gatherers in favorable conditions (Pimentel and Pimentel, 1979) to a maximum value of 4000 h year - 1 for slaves (Tardo-Dino, 1985 ); 2000 h year - ~is the average value assumed for our calculation.
Assessment of the flow of applied power Assuming a standard age structure with a 55% working population, a standard sex ratio of 50% and 2000 h year -~ of labor charge we have 75 × 0.55 × 2000 × 3600 = 297 MJ of applied power per capita per year for such a population.
Energy requirements The level of energy expenditure per capita can differ and is related to the degree of technological development of the society.
Rural poor societies based on manpower The level of energy consumption per capita for rural poor societies based on manpower is related to various factors. ( 1 ) Body size (for example, a 75-kg body size consumes more than a 55-kg body size). Concerning body size, we are not able to assess the trade-off between the disadvantage produced by the increase in energy expenditure and the advantage produced by the increase in power level that is coupled with large body size. Some traditional societies show an evolution towards small body size, but particular conditions (e.g. African populations of pastoralists exploiting large semi-arid areas) evolved towards large body size (at least in terms of height). (2) Quality of the diet (level of embodied energy in food). For example, a diet rich in animal protein implies a larger requirement for biological energy taken from the ecosystem in the form of biomass (double conversion of energy input to produce meat). (3) Exosomatic energy flows (energy flows converted to useful work outside the human body). This includes the use of fire for cooking and the use of
ASSESSMENTOF THE ENERGETICS OF HUMAN LABOR
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draft animals for agriculture. These energy flows are used to sustain society and should then be added to the direct cost of nutritional energy. Considering all these inputs, the quantity of consumption per capita in traditional societies, based on biomass input can range from 290 to 730 W per capita (6000-15 000 kcal day- 1).
Rich societies based on technological power The flow of applied power generated by human muscles is relatively negligible in rich societies with high levels of technical development. A fair assessment of the energetic expenditure per capita can be obtained from the consumption of fossil energy and electricity produced by nuclear and hydroelectric generation. The level of expenditure per capita in these societies can range from 3900 to 9700 W per capita (80 000-200 000 kcal day- ~). ENERGETIC COST OF HUMAN LABOR
Labor cost We define the cost of human power as the quantity of energy embodied in a joule of applied power. The ratio EI/AP (energy input required per joule of applied power) can be used to assess the cost of human labor. This ratio depends on two parameters: level of manpower per capita; level of energy expenditure per capita. Both of these parameters are affected by populational and societal structure. The embodied energy for human labor (cost of human labor) can be calculated as EI/APwhere: El=level of energy consumption per capita (average year) expressed in joules (having the level of consumption per capita expressed in kcal day- ~, the conversion to joules is E1 (joules) = kcal day- 1per capita × 365 × 4185 ); AP= flow of applied power per capita (average year) = watts (level of power per capita) × hours year-~ (labor charge) × 3600 (seconds in 1 h). Generally, we assume that the level of human power is constant (assuming the sex ratio is ~ 50%) at 75 W and the working part of the population is ~ 55% in developing countries. Substituting these average values we have
E I / A P - level of expenditure per capita (in watts ) level of labor charge (hours year- I ) X 212.36 From this equation, it is evident that poor developing societies facing energy constraints can improve their energy efficiency by increasing the charge for labor and/or decreasing the accepted standard of living (energy expenditure per capita). This means lowering the quality of the diet in the poorest societies. Using this equation and assuming a standard labor charge of 2000 h labor year- ~, the manpower cost becomes
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EI/AP= level of expenditure per capita (in watts ) × 0.106 (EI/AP=level of expenditure per capita (kcal day- l ) ×0.005 ) I h of human labor provides (75 × 0.55 × 3600) = 148 500 J of applied power. The energy requirement of 1 manpower hour will be Level of expenditure per capita (in watts) X 15 768 = E1 expressed in joules (level of expenditure per capita (kcal day- ~) × 0.18 =El expressed in kcal) The EI/AP ratio can change from 40 for very poor societies, i.e. level of energy expenditures= 370 W (7500 kcal day -~ ), to 80 for fairly developed rural societies, i.e. 740 W (15 000 kcal day -1 ) and to > 1000 in the U.S.A. (these EI/AP ratios refer only to the flow of power delivered by human muscles). Using this formula, in poor rural systems ( 370 W level of expenditure), the society requires 5.6 MJ (1350 kcal) of energy input for every hour of work applied by humans. The energetic cost of 1 h of labor in a fairly developed rural society (e.g. Indian rural areas at 740 W) is 10.5 MJ (2500 kcal). In the case of human labor in the U.S.A., the formula provides an energy input requirement of 151 MJ (36 000 kcal) per hour. Actually we saw previously that the energy requirement for an hour of labor in the U.S.A. is higher; the difference is due to the fact that the formula used here refers to a societal structure (age structure, labor charge, level of human power delivery) typical of developing countries, quite different from the real picture of American society.
Power generation costs In the following sections, we present an assessment of power generation costs for different systems. The scheme, parameters and equations used are presented in Fig. 4. Again, the data presented here are only illustrating a methodology.
Human power Using data from Sundarraj and Mitchell (1986) from a village in rural India (Panayakurichi, 994 people), we calculated the power generation cost of human power. Where El= total energy requirements (including foods, fuel for cooking, feed for goat and milk, seeds and fertilizers) E I = 2 0 440 GJ year -~ (4884×
10 6 kcal
year -~ )
The level of energy expenditure per capita= 654 W ( 13 500 kcal day- ~) where 23% of caloric expenditure of the entire population occurs doing work. N=0.23 EI=4716 GJ year -~ ( 1127X
10 6 kcal
year -1 ).
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ASSESSMENTOF THE ENERGETICS OF HUMAN LABOR
ENVIRONMENT EI EI = Energy Input from the environment
SYSTEM
AP= Power applied to the environment
N
x.C' C:J
N = Fraetionof energy input directly converted in applied power M = Fraction of energy input used for self-organization (maintenance of system's function/structure) ~=~
(~=NM
EI=M+AP/ Loss for conversion energy input/power
M
q
N=AP/q O= AP/~] M
~,~_ = ( O + l ) AP ~
Fig. 4. C o s t o f p o w e r g e n e r a t i o n .
This ratio has been calculated from data on energetic expenditures according to different activities from Durnin and Passmore (1967). The 23% of the embodied energy in food calories is considered as N flow (as in Fig. 4 ) M=EI-N=
15 723 GJ year-1 (3757 ×
10 6
kcal year -1 ) (the flow M as in
Fig. 4) When assessing the flow of applied power the characteristic of population was found to be: working 56% (males 49%). A reported 573 h year -~ per capita are spent on average on field work by the working population, a level of 2000 h year-~ has been assumed to include the other activities related to village life. Assuming 75 W as the power level of adults ( ~ 500/0 males/females) 75 × 0.56 × 2000× 994× 3600= 300 GJ A P = 300 GJ ~?= A P / N = 0.06 cr= N / M = 0 . 3 0
We can obtain the cost of power generation (ratio E I / A P by ( 1 ) using the formula in Fig. 4: E I / A P = 1 +cr/rla=72.22 (2) directly by dividing the values of E1 (20 440 GJ) by the value o f A P (300 GJ) =68.13; (3) using the approximated formula presented previously: level of energy expenditure (654 W) × 0.106 = 69.32 Tractor power
The formula presented in Fig. 4 enables us to calculate the power generation cost of a technical device that generates power (e.g. an engine or a tractor) if we are able to assess the r/, a parameters. For example, we know that ~/ for a thermic engine can be assumed to be 0.20. a is the ratio N / M , where N
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M. GIAMPIETRO AND D. PIMENTEL
is the fuel consumed per year and M is the quantity of energy that we can charge annually for the construction and maintenance of the piece of machinery ( 10-year life span). The value of a can be calculated from the literature (Pimentel and Pimentel, 1979) related to agricultural activities on a yearly basis: 1.7 for wheat, 2.3 for corn, 2.8 for sorghum, 0.4 for soybeans, 2.4 for beans. An average of 2 can be assumed for machinery used in agricultural activities. E I / A P = 1 + tr/rltr= 7.7
This means that a tractor requires 8 joules of energy input to deliver 1 J of applied power. These are rough estimates, but the large difference between humans and machines in terms of cost of power generation (almost 10 times higher for humans) can be used to explain the switch that developed societies have made towards technological power when capital and fossil energy are available. A n i m a l power Using data from Sundarraj and Mitchell (1986), the power generation cost of bullock power is calculated. Characteristics of the bullock population in Panayakurichi: 94 working bullocks; 938 h year- ~per capita. Assuming a level of power per bullock= 446 W (0.6 HP) E l = 3445 GJ year- ~ (823 × 106 kcal year- ~)
(This energy includes the replacement cost related to keeping 15 bullocks for under 3 years) N = 617 GJ year- ~ ( 147 X 106 kcal year- 1) M = E l - N = 2828 GJ year- ~ (676 × 106kcal year- ~) A P = 142 GJ year -~ ( 9 4 × 4 4 6 × 9 3 8 X 3 6 0 0 ) r i = A P / N = 0.23 tr= N / M = 0 . 2 2 E I / A P = 3445/142 = 24.26 E I / A P = 1 + tr/rltr= 24
A bullock requires 24 J of energy input to deliver 1 J of applied power. However, this cost of power generation refers only to energy flowing in the bullock system. In reality, the bullocks cannot work by themselves. A more accurate assessment should calculate the cost of human time coupled to the bullock activity (the same is true for tractors). Clearly, the use of animal power increases the level of power per capita of the society. In fact, 567 workers (42 525 W) and 94 bullocks (41 924 W) provide a level per capita of 85 W (84 449/994), while the village using only human power would have only 42 W (the 75 W power level of workers is
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decreased because of the 43% non-working population). Recalling the previous observation on the effects of power level requirement, note that animal power is a definite improvement in societies affected by endemic shortage of power. In fact, Sundarraj and Mitchell (1986) note that in the Panaykurichi village "decisions about what to plant and how to plant are based on the availability of labor". The use of animal power also decreases the cost of power applied by the village in agricultural activities. The lower power generation cost of animal power depends on the lower level of embodied energy of their food (r/is definitely higher for animals than for humans). Clearly, this wide difference is not generated by differences in physiological efficiency in converting food into power at the muscle level, but simply to the fact that bullocks eat raw food (saving, for example, the 2 J spent per nutritional joule when food is cooked). In rural areas, low quality feed is consumed by bullocks. Moreover, their ability to eat cellulosic biomass enables them to feed without competing with humans. In fact, they usually graze on marginal areas that would not be fit for agricultural activities. CONCLUSIONS Measuring the energetics of human labor in agriculture is highly complex. This complexity is related to the boundaries selected for a worker, the technological development of agriculture, population structure (age and sex), and the standard of living and consumption of resources by society. In poor, rural, agricultural societies, it is clear that human labor has a high relative value. This is in part one of the major reasons why children are highly valued and large families are typical under these conditions. In well-to-do, high-tech societies, human labor is of value, but has a different meaning, providing mainly a flow of information. Therefore, measuring the cost of human labor only in terms of food calories consumed per hour by a laborer is misleading if we are comparing a hand-produced agriculture and tractor-produced agriculture. The supporting energy resources for a laborer in a tractorpowered system may be more than 20 times higher than the energy supporting a laborer in hand-powered agriculture. Thus, our analysis suggests that using the total energy inputs per working member of society (instead of physiological energy input) has the advantage in assessing energy requirements for labor in agriculture for both developing and developed agriculture. REFERENCES Avery, D., Schramm,G. and Shapiro, K., 1978. ProductionSystemsin FragileEnvironments. In: Universityof Michigan- Scienceand Technologyfor ManagingFragileEnvironmentsin DevelopingNations. Ann Arbor, September1978.
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Durnin, J.V.G.A. and Passmore, R., 1967. Energy, Work and Leisure. Heinemann, London, pp. 30-104. Giampietro, M. and Pimentel, D., 1987. Food-energy security for 5 billion humans: the cost of a rapidly growing population. Paper presented to the 2nd Vienna Center Conference on Ecology and Economics, 26-29 September 1987, at Barcelona. Giampietro, M. and Pimentel, D., 1990a. Energy efficiency: assessing the interaction between humans and their environment. Ecol. Econ., in press. Giampietro, M. and Pimentel, D., 1990b. Energy efficiency and nutrition in societies based on human labor. Ecol. Food Nutr., submitted. Nicolis, G. and Prigogine, I., 1977. Self-organization in Nonequilibrium Systems. J. Wiley, New York. Odum, E.P., 1971. Fundamentals of Ecology. 3rd Edn., Saunders, Philadelphia, p. 251. Pimentel, D. and Pimentel, M., 1979. Food Energy and Society. Arnold, pp. 30-35. Rappaport, R.A., 1971. The flow of energy in an agricultural society. Sci. Am., 224: 117-133. Sundarraj, T.S.P. and Mitchell, R., 1986. Analysis of ecosystem structure and energy flow in a South Indian village. In: F.J. Hitzhusen and R.D. Macgregor (Editors), A Multidisciplinary Approach to Renewable Energy in Developing Countries. Publishing Horizons, Columbus, OH, pp. 141-167. Suzuki, S., Oshima, S., Tsuji, E. and Ohta, F., 1978. Interrelationships between nutrition, physical activity, and physical fitness. In: J. Parizkova and V.A. Rogozkin (Editors), Nutrition, Physical Fitness, and Health, University Park Press, Baltimore, MD, pp. 194-214. Tardo-Dino, F., 1985. Le collier de servitude: la condition sanitaire des esclaves aux Antilles frangaises du XVIIe au XIX e sircle. Paris: Editions caribdennes: Agence de coopdration culturelle et technique (Collection "Connaisance de la diaspora noire").
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Assessment of the energetics of human labor Mario Giampietro t and David Pimentel2 ~lstituto Nazionale della Nutrizione, Unit of Special Food Technology, via Ardeatina 546, 00178 Rome (Italy) 2Department of Entomology, Comstock Hall, Cornell University, Ithaca, NY 14853-0999 (U.S.A.) (Accepted for publication 24 April 1990)
ABSTRACT Giampietro, M. and Pimentel, D., 1990. Assessment of the energetics of human labor. Agric. Ecosystems Environ., 32: 257-272.
The energetic analysis of farming systems implies an assessment of the energetics of human labor. The energy cost of I h of human labor is generally estimated according to its physiological requirement (the hierarchical level at which the assessment is made is at the individual level). A different way of describing the interaction between human society and the ecosystem is presented in this paper (assessment referred to the society level). The shift from the individual level to the societal level provides a new perspective when assessing the energetic efficiency of farming. For example, the power level of the system becomes a new and important parameter to consider. Numerical examples illustrate the proposed approach.
INTRODUCTION
The energetic analysis of farming systems deals in part with the important problem of assessing the energetics of human labor. The difficulty in assessing human labor begins with the choice of the boundaries of the system. In fact, different boundaries can provide different definitions for human labor (e.g. labor is traditionally considered an energetic input for cultivated crops; on the other hand, at the farm level, the requirement for human labor represents an energetic cost). Another problem is provided by the economic measure of the labor input. In a developed society, the monetary cost of manpower is high. This means that in spite of the small human labor input to the energetic budget of a farm, the requirement of human labor can heavily affect the overall economics of the system. In developing societies, however, the low level of power and low-cost labor results in the extensive use of labor in agriculture. Human labor provides both a flow of applied power and a flow of information. The quality and quantity of this information can alter the value of the labor. In societies with a high level of technological capital, humans direct the flow of machine power, while in poor traditional societies humans pro0167-8809/90/$03.50
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vide the flow of power as well. This means that one hour of human labor in a western farm or in a developing country farm implies the delivery of different quantities of power. Also, the cost of power generation, defined as the quantity of energy input (joules) required to deliver a joule of applied power, is dramatically different in these two systems. For this reason, we feel that a discussion about boundaries and parameters describing the energy efficiency of agricultural labor is needed. Thus, the objective of this paper is to analyze ( 1 ) the concept of energy efficiency in farming systems and (2) the factors affecting the embodied energy ( = the energetic cost) of human labor. E N E R G Y E F F I C I E N C Y IN A G R I C U L T U R E
Energy efficiency In general, efficiency is calculated as a ratio (output/input) with respect to a single parameter. On the other hand, the typical pattern found when analyzing different efficiencies in farming systems is that an increase in efficiency with respect to one parameter implies a decrease in efficiency with respect to other parameters (e.g. maximization of economic profit vs. minimization of risk, maximization of crop yield vs. minimization of ecosystem degradation, etc. ). Therefore an objective definition of energy efficiency needs an absolute and quantifiable definition of what is best for the system. Odum ( 1971 ), examining the evolution of natural communities, suggested that the optimizing parameter for energy efficiency is the ratio between the quantity of information (the level of ecosystem organization maintained in steady state) and the quantity of energy dissipated. This indicator is perfectly consistent with the "dissipative structures theory" formulated by Nicolis and Prigogine (1977) for thermodynamic systems not in equilibrium. Ecosystems, living beings and human societies can be regarded as self-organizing systems able to maintain a defined level of complexity (their function/structure) because of the continuous dissipation of energy. Obviously, a challenge exists to assess information flows by this approach. However, we can describe the process of energy dissipation that leads to the maintenance of human society as follows. Humans invest applied power to alter ecosystems (Fig. 1 ), this energetic investment alters the organization of the ecosystem, producing a form of ecosystem less probable according to natural processes, but more profitable for humans. That is, human cultivation increases the quantity of harvestable biomass and the quantity of energy output harvested from the ecosystem per unit of area. The flow of energy output that the humans harvest from the ecosystem can be considered the return of human investment. Using the analogy
2 59
ASSESSMENT OF THE ENERGETICS OF HUMAN LABOR Solar energy
Energy dissipated by ecosystem
ECOSYSTEM
ENERGY INPUT taken fromthe ecosystem
--1 APPLIED POWER to alter the ecosystem
SOCIETY
b
I Level of energy expenditures of the society
Fig. 1. Energetic interaction human society-ecosystem.
with.an economic model, the cost of the energetic investment (the flow of applied power) can be calculated as the sum of current expenses (the energy required to generate the applied power) and fixed expenses, related to the maintenance of the capital needed to produce the investment (energy spent within the boundary of human society to maintain the societal structures). The level of energy expenditures resulting from this interaction (the level at which a dynamic equilibrium is reached between the energy invested and the energy harvested) would assess the level of technological development of this society (Giampietro and Pimentel, 1990a). Note (Fig. 1) that joules of applied power (AP) and joules of energy input (El) are different energy flows, with different costs (different levels of embodied energy).
Energy input, applied power and work done Power generation In order to produce applied power, we always lose energy in the conversion (e.g. ifa tractor's thermic engine has r/= 0.20, this means that only 20% of the joules of the fuel are converted to joules of applied power). Moreover, energy is spent in building and maintaining the structure that delivers power. This means that we can imagine the total energy requirement as the sum of two different flows of energy: one flow (N) used directly to generate power and another flow (M) calculated as the energy spent in the construction and maintenance of the structure delivering power, discounted on its life span.
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For example, if a tractor has a ratio N/M= 2, this means that an increase of 30% has to be added to its fuel consumption to assess the energy requirement for its construction and maintenance (discounted on a 10-year life span). While the ratio r/, related to the direct conversion of energy input into power, can be considered generally constant according to the device used (e.g. thermic engine, human muscle, animal muscle), the incidence of the cost of maintenance of the structure (tr=N/M) can be dramatically affected by different factors (e.g. the case of human power generation was analyzed in Giampietro and Pimentel, 1990b).
Ratio work done~power applied The conversion of a joule of energy input into a joule of applied power is only the start. The ultimate goal is the conversion of applied power into final work. The quantities of work done by two different pumps using the same amount of applied power illustrates this point (Fig. 2). The work done per joule of applied power (work done/power applied) provides a quantitative measure of the difference in knowledge of the system in energy end use. Clearly, Pump B delivers ~ 16 times more water per unit of applied power.
Power thresholds Traditional farming systems based on human labor have a low level of power and therefore generally avoid peaks of labor demand. The multi-use of mulCurves of discharges/lift for two types of hand pumps t
~ - - ~ P
A basketpipe 2 persons B == swing hasculating I person
10 Discharge tons/hr 5
ump B
\ pump A I 1
I 2
lift (metres)
Hypothesizing the same device generating the power moving the pumps (human muscle) are obtained either by the labor of I person x l 0 hours or 2 persons x 5 hours
2.7 MJ
2.7 MJ
of Applied Power with the Pump A
--->
5
tons lifted 1 m
2.7 MJ
of Applied Power with the Pump B
---> 83
tons lifted 1 m
Comparing these data with the mechanical work-output : ton lifted 1 m = 10,000 joules of mechanical work and defining the ratio ~ = mechanical work/Applied Power 1
(/,
of pump A
O~
of pump B = 0.31
= 0.02
Fig. 2. Examples of different ratios of work output per unit of applied power.
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tiple crops and livestock, typical of traditional farming, often spreads the requirement of manpower through the year. On the other hand, developed agriculture with a high level of machine power is able to effectively deal with peak power demand that eventually minimizes the human labor input. In attempting to transfer modem agricultural technologies to developing countries, care must be exercised to avoid peak power demand. See Fig. 3 for an example of this problem with high-technology sorghum (graphs from Avery et al., 1978). Societies primarily based on manpower are limited by peak power constraints. Although utilizing men and women for different tasks and using draft animals will help in reducing peak power problems, the peak problem remains without machine power (Giampietro and Pimentel, 1990b). Rappaport (1971) writes, "I found that the performances of men and women in clearing the bush were surprisingly uniform. Although in an hour some women clear little more than 200 square feet and some of the more robust men clear nearly 300 square feet, the larger men expend more energy per minute than women. The energy input of each sex is approximately equal: harvest weeding
/
400--
300-
200--
100-
I I I I I jan feb mar apr m a y j u n
.I I I jul a u g s e p
f oct n o v d e c
Labor profile related to sorghum cultivation high yield, Central Niger (Avery et al. 1978)
400--
e~
300-. weeding 200
100
I I I I I I jan feb mar apr m a y j u n
I ~ I jul a u g s e p
I ~t
I I novdec
Labor profile related to sorghum cultivation traditional technique - Bush Tua~. 8, Central Niger (Avery et al. 1978)
Fig. 3. Labor profiles for sorghum production.
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some 0.65 kcal per square foot." The performances of men and women reported by Rappaport may be uniform in terms of energy requirement per unit of surface (29 000 J m -2 using the SI system), but the difference in labor done per unit time suggests a difference in the level of power delivery. This can be illustrated by comparing the performances of men and women in terms of energy expenditures per work done. Imagine defining the work as carrying 400 kg of sand upstairs 5 m in height. Our point is that this definition of work cannot be used to compare performances without a previous specification of power level. For example, we can do this work in three ways: (a) 5 trips carrying 80 kg; (b) 20 trips carrying 20 kg; (c) 100 trips carrying 4 kg. The high power level requirement of (a) would prevent many women performing the work. In this situation, the larger body size of men would give them an advantage. On the other hand, light repetitive work as in the third case (c) would give the advantage to women, who have a smaller body size and a slower metabolism. This implies less energy expenditure in terms of work done per energy input. This example illustrates that the performances in doing work can be affected by power level requirements. Unfortunately, the examples given are only estimates because the investigators who study work and human energy expenditures do not carry out their measurements including the power level parameter. The measures of energy consumption for a certain task, related to particular people, provide data related to the energy input required by the society, but do not assess the energy efficiency in converting food energy into applied power. This is surprising, because it is like comparing the performances of different trucks by measuring the gasoline consumed, without specifying distance, speed and load. E M B O D I E D E N E R G Y O F H U M A N LABOR
Since the first development of energy analysis, quantities of energy and measures of flow of energy in time have been often reported in terms of kcal and kcal day- 1 (or kcal h - 1, or kcal year- 1). Clearly, these are not the fight units to measure energy, in fact the International System of Units calls for joule when referring to quantities and watt in the case of flow joules in time. Unfortunately, the use of kcal is still widespread today, to the point that the assessment of energy requirements and the level of energy expenditure for humans and societies in the literature are often expressed in kcal. The same problem exists for the assessment of mechanical power, traditionally measured in agriculture in terms of horsepower (HP). In order to help readers not familiar with the measurement of energy and power in joules and watts, in our text we will provide the equivalent value in kcal or HP in parentheses after the correct value in SI units.
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Energy costs allocated to human labor When measurements are made of meat or milk production in agriculture, the energy required for the production of replacement animals is included in the analysis. We propose that a similar approach be used for calculating the energy inputs for human labor, i.e. children and the non-working force be included in all labor cost measurements. The gross energy consumed per capita should be included in the analysis. Thus the cost of applied power can be measured by the ratio of the gross energy requirement per capita of the society (i.e. the quantity of energy input that the society takes from the ecosystem) divided by the quantity of applied power per capita that the society delivers to the ecosystem in managing it. Using this approach to calculate the cost of power generation for human labor, we have Energy input =joules consumed by the society in order to have human laborers In this case, we are considering the total energy input, not just nutritional calories. For example, the biomass used by a human to cook (2 J of biomass are consumed per nutritional joule of cooked food), seeds, etc., should be included in the assessment of energy input Applied power = joules of muscular power delivered by human society
Benefits of this approach This approach of including total society in the energy cost of human labor enlarges the boundaries of the agricultural system. Obviously, this complicates the energy analysis~ The societal level of exosomatic power (exosomatic power is the power delivered in human activities without using human muscles, i.e. animal power, power provided by natural process and mechanical power) can alter the meaning of human labor in agricultural activities. For example, a U.S. farmer driving a 75-kW (100-HP) tractor has his muscular power multiplied 1000 times! When human labor becomes negligiblein terms of power input (the machines are providing power for the society), humans provide the information for accomplishing the job. Nevertheless, by coupling the cost of human labor to the level of energy expenditure of society we have a way to assess the role of humans in providing information to the system (in harnessing this exosomatic power). In fact, the change in the characteristic of human labor, typical of developed societies, can be measured by the dramatic increase in energy inputs that the society spends to sustain a worker. The high level of embodied energy in an hour of human labor also explains the high level of monetary cost of human labor in developed societies.
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The measure of human labor generally found in literature is based on the biological requirement of the human body; these data are generally expressed in nutritional energy required to provide an hour of labor. This equivalence does not consider the level of embodied energy of the nutritional joules (kcal) consumed by the worker e.g. 1000 J of meat are more expensive in caloric terms than 1000 J of sorghum, 10 J (kcal) of ecosystem biomass are generally required to produce 1 J (kcal) of meat. A U.S. worker lives in a society with a level of consumption of > 9700 W of energy expenditures per capita (this means 200 000 kcal d a y - 1 i.e. 8500 kcal of energy input per hour, all day long, every day). If we charge his/her energy expenditures on a yearly basis related to 2000 hours of labor (23% of the total year hours) we have 152 MJ (37 000 kcal ) of energy input are required to have an hour of labor. If we calculate the dependents of the worker (children, elderly and other non-working members of the population), an hour of human labor requires up to 250 MJ (60 000 kcal ) of energy input to the U.S. society. This is the reason why rich societies minimize the use of human labor, switching to machine power whenever possible. Commonly, the assessment of energetic measure of human labor based on nutritional requirements would provide more or less the same value for a U.S. worker and a Mali worker: in the range of 2-2.5 MJ (450-600 kcal) required per hour of labor. The energetic analysis used in assessing human labor based on differences in physiological energy requirements would provide only small TABLE l Use of human time in food system activities: Mali vs. U.S.A. Food security activities considered Food production (input labor of population in agriculture) Processing-distribution (input labor of workers in this sector) Home preparation (input labor of housekeepers not employed in the economic sector) Eating (time spent by everyone in having meals) Country
Hours spent 2
Mali U.S.A.
7.98 2.76
The people in the U.S.A. can devote the extra time (5220 h for 1000 people day -~ ) to earning high wages in other activities, independent of the food system. In this way (owing to the multiplicative effect of the power level generated by the use of a "fossil energy/machine" energy chain ), the society as a whole can have access to a higher quantity of resources per capita ~Giampietro and Pimentel, 1987. 2Total hours of human time spent in food security-related activities (per capita day- ~).
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differences in energetic cost between human labor in these two societies. We feel that such assessments are inadequate to analyze the dynamics of energy utilization within these societies. As noted before, the huge multiplicative effect of technology on human power enhances the importance of information provided by humans. In developed societies, the value of human labor (e.g. difference in salary) is not related to the quantity of muscular power applied, but is related more to the quality of the information utilized. The difference in level of power can also be used to study the differences in salary between developed and developing societies (e.g. the wide difference between the salaries of a farmer in New York State and in Mali). Table 1 shows the difference in human hours spent in food supply activities in U.S.A. and Mali societies, this difference can be explained by the different cost-opportunity of human labor. Clearly, in societies where the energetic investment of the society is rotated at a higher rate (9700 W is the steady state level of energy dissipation per capita at society level) the cost/return of 1 h of human labor must consequently be higher.
Applied power of human labor The quantity of applied joules that is delivered by human labor in the society (on a yearly basis) can be calculated as Level of human power per capita × hours of labor In order to quantify these parameters, we have to know populational and societal characteristics: sex ratio, age structure, body size, labor charge.
Human power We assume that 90 W is the power of an adult man (0.12 HP) and 60 W is the power of an adult woman (0.08 HP ). A difference in power of 30% has been assumed between men and women on the basis of different performances in sporting events (i.e. running and weight lifting in Suzuki et al., 1978 ) and in work output (Rappaport, 1971 ). However, these data are used to illustrate a methodology, an assessment of men and women's power performances is not the aim of this paper. The level of power (expressed in watts) per capita of human labor is given by Power level per capita = (Xm 90 + Xf 60) where XmdS the percent of working adult males and xf is the percent of working adult females. The existence of a non-working population (Xm+ Xf< 1 ) decreases the power level per capita (a maximum power level is obtained using a population of adults only, e.g. slaves). The sex ratio can affect the power level of a group of
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people (a maximum power level is obtained using only adult males, e.g. traditional army). With a standard ratio of 50% males/females, the power level of an average worker can be assumed to be 75 W ( ~0.1 HP). The value of 75 W is the standard equivalent used to compare manpower to agricultural machinery (Pimentel and Pimentel, 1979). However, using our approach, this value must be further decreased because of the non-working share of the population.
Labor per capita The quantity of hours worked per year can vary within a defined range: starting from a minimum value of < 900 h year- ~ for hunters and gatherers in favorable conditions (Pimentel and Pimentel, 1979) to a maximum value of 4000 h year - 1 for slaves (Tardo-Dino, 1985 ); 2000 h year - ~is the average value assumed for our calculation.
Assessment of the flow of applied power Assuming a standard age structure with a 55% working population, a standard sex ratio of 50% and 2000 h year -~ of labor charge we have 75 × 0.55 × 2000 × 3600 = 297 MJ of applied power per capita per year for such a population.
Energy requirements The level of energy expenditure per capita can differ and is related to the degree of technological development of the society.
Rural poor societies based on manpower The level of energy consumption per capita for rural poor societies based on manpower is related to various factors. ( 1 ) Body size (for example, a 75-kg body size consumes more than a 55-kg body size). Concerning body size, we are not able to assess the trade-off between the disadvantage produced by the increase in energy expenditure and the advantage produced by the increase in power level that is coupled with large body size. Some traditional societies show an evolution towards small body size, but particular conditions (e.g. African populations of pastoralists exploiting large semi-arid areas) evolved towards large body size (at least in terms of height). (2) Quality of the diet (level of embodied energy in food). For example, a diet rich in animal protein implies a larger requirement for biological energy taken from the ecosystem in the form of biomass (double conversion of energy input to produce meat). (3) Exosomatic energy flows (energy flows converted to useful work outside the human body). This includes the use of fire for cooking and the use of
ASSESSMENTOF THE ENERGETICS OF HUMAN LABOR
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draft animals for agriculture. These energy flows are used to sustain society and should then be added to the direct cost of nutritional energy. Considering all these inputs, the quantity of consumption per capita in traditional societies, based on biomass input can range from 290 to 730 W per capita (6000-15 000 kcal day- 1).
Rich societies based on technological power The flow of applied power generated by human muscles is relatively negligible in rich societies with high levels of technical development. A fair assessment of the energetic expenditure per capita can be obtained from the consumption of fossil energy and electricity produced by nuclear and hydroelectric generation. The level of expenditure per capita in these societies can range from 3900 to 9700 W per capita (80 000-200 000 kcal day- ~). ENERGETIC COST OF HUMAN LABOR
Labor cost We define the cost of human power as the quantity of energy embodied in a joule of applied power. The ratio EI/AP (energy input required per joule of applied power) can be used to assess the cost of human labor. This ratio depends on two parameters: level of manpower per capita; level of energy expenditure per capita. Both of these parameters are affected by populational and societal structure. The embodied energy for human labor (cost of human labor) can be calculated as EI/APwhere: El=level of energy consumption per capita (average year) expressed in joules (having the level of consumption per capita expressed in kcal day- ~, the conversion to joules is E1 (joules) = kcal day- 1per capita × 365 × 4185 ); AP= flow of applied power per capita (average year) = watts (level of power per capita) × hours year-~ (labor charge) × 3600 (seconds in 1 h). Generally, we assume that the level of human power is constant (assuming the sex ratio is ~ 50%) at 75 W and the working part of the population is ~ 55% in developing countries. Substituting these average values we have
E I / A P - level of expenditure per capita (in watts ) level of labor charge (hours year- I ) X 212.36 From this equation, it is evident that poor developing societies facing energy constraints can improve their energy efficiency by increasing the charge for labor and/or decreasing the accepted standard of living (energy expenditure per capita). This means lowering the quality of the diet in the poorest societies. Using this equation and assuming a standard labor charge of 2000 h labor year- ~, the manpower cost becomes
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EI/AP= level of expenditure per capita (in watts ) × 0.106 (EI/AP=level of expenditure per capita (kcal day- l ) ×0.005 ) I h of human labor provides (75 × 0.55 × 3600) = 148 500 J of applied power. The energy requirement of 1 manpower hour will be Level of expenditure per capita (in watts) X 15 768 = E1 expressed in joules (level of expenditure per capita (kcal day- ~) × 0.18 =El expressed in kcal) The EI/AP ratio can change from 40 for very poor societies, i.e. level of energy expenditures= 370 W (7500 kcal day -~ ), to 80 for fairly developed rural societies, i.e. 740 W (15 000 kcal day -1 ) and to > 1000 in the U.S.A. (these EI/AP ratios refer only to the flow of power delivered by human muscles). Using this formula, in poor rural systems ( 370 W level of expenditure), the society requires 5.6 MJ (1350 kcal) of energy input for every hour of work applied by humans. The energetic cost of 1 h of labor in a fairly developed rural society (e.g. Indian rural areas at 740 W) is 10.5 MJ (2500 kcal). In the case of human labor in the U.S.A., the formula provides an energy input requirement of 151 MJ (36 000 kcal) per hour. Actually we saw previously that the energy requirement for an hour of labor in the U.S.A. is higher; the difference is due to the fact that the formula used here refers to a societal structure (age structure, labor charge, level of human power delivery) typical of developing countries, quite different from the real picture of American society.
Power generation costs In the following sections, we present an assessment of power generation costs for different systems. The scheme, parameters and equations used are presented in Fig. 4. Again, the data presented here are only illustrating a methodology.
Human power Using data from Sundarraj and Mitchell (1986) from a village in rural India (Panayakurichi, 994 people), we calculated the power generation cost of human power. Where El= total energy requirements (including foods, fuel for cooking, feed for goat and milk, seeds and fertilizers) E I = 2 0 440 GJ year -~ (4884×
10 6 kcal
year -~ )
The level of energy expenditure per capita= 654 W ( 13 500 kcal day- ~) where 23% of caloric expenditure of the entire population occurs doing work. N=0.23 EI=4716 GJ year -~ ( 1127X
10 6 kcal
year -1 ).
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ASSESSMENTOF THE ENERGETICS OF HUMAN LABOR
ENVIRONMENT EI EI = Energy Input from the environment
SYSTEM
AP= Power applied to the environment
N
x.C' C:J
N = Fraetionof energy input directly converted in applied power M = Fraction of energy input used for self-organization (maintenance of system's function/structure) ~=~
(~=NM
EI=M+AP/ Loss for conversion energy input/power
M
q
N=AP/q O= AP/~] M
~,~_ = ( O + l ) AP ~
Fig. 4. C o s t o f p o w e r g e n e r a t i o n .
This ratio has been calculated from data on energetic expenditures according to different activities from Durnin and Passmore (1967). The 23% of the embodied energy in food calories is considered as N flow (as in Fig. 4 ) M=EI-N=
15 723 GJ year-1 (3757 ×
10 6
kcal year -1 ) (the flow M as in
Fig. 4) When assessing the flow of applied power the characteristic of population was found to be: working 56% (males 49%). A reported 573 h year -~ per capita are spent on average on field work by the working population, a level of 2000 h year-~ has been assumed to include the other activities related to village life. Assuming 75 W as the power level of adults ( ~ 500/0 males/females) 75 × 0.56 × 2000× 994× 3600= 300 GJ A P = 300 GJ ~?= A P / N = 0.06 cr= N / M = 0 . 3 0
We can obtain the cost of power generation (ratio E I / A P by ( 1 ) using the formula in Fig. 4: E I / A P = 1 +cr/rla=72.22 (2) directly by dividing the values of E1 (20 440 GJ) by the value o f A P (300 GJ) =68.13; (3) using the approximated formula presented previously: level of energy expenditure (654 W) × 0.106 = 69.32 Tractor power
The formula presented in Fig. 4 enables us to calculate the power generation cost of a technical device that generates power (e.g. an engine or a tractor) if we are able to assess the r/, a parameters. For example, we know that ~/ for a thermic engine can be assumed to be 0.20. a is the ratio N / M , where N
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is the fuel consumed per year and M is the quantity of energy that we can charge annually for the construction and maintenance of the piece of machinery ( 10-year life span). The value of a can be calculated from the literature (Pimentel and Pimentel, 1979) related to agricultural activities on a yearly basis: 1.7 for wheat, 2.3 for corn, 2.8 for sorghum, 0.4 for soybeans, 2.4 for beans. An average of 2 can be assumed for machinery used in agricultural activities. E I / A P = 1 + tr/rltr= 7.7
This means that a tractor requires 8 joules of energy input to deliver 1 J of applied power. These are rough estimates, but the large difference between humans and machines in terms of cost of power generation (almost 10 times higher for humans) can be used to explain the switch that developed societies have made towards technological power when capital and fossil energy are available. A n i m a l power Using data from Sundarraj and Mitchell (1986), the power generation cost of bullock power is calculated. Characteristics of the bullock population in Panayakurichi: 94 working bullocks; 938 h year- ~per capita. Assuming a level of power per bullock= 446 W (0.6 HP) E l = 3445 GJ year- ~ (823 × 106 kcal year- ~)
(This energy includes the replacement cost related to keeping 15 bullocks for under 3 years) N = 617 GJ year- ~ ( 147 X 106 kcal year- 1) M = E l - N = 2828 GJ year- ~ (676 × 106kcal year- ~) A P = 142 GJ year -~ ( 9 4 × 4 4 6 × 9 3 8 X 3 6 0 0 ) r i = A P / N = 0.23 tr= N / M = 0 . 2 2 E I / A P = 3445/142 = 24.26 E I / A P = 1 + tr/rltr= 24
A bullock requires 24 J of energy input to deliver 1 J of applied power. However, this cost of power generation refers only to energy flowing in the bullock system. In reality, the bullocks cannot work by themselves. A more accurate assessment should calculate the cost of human time coupled to the bullock activity (the same is true for tractors). Clearly, the use of animal power increases the level of power per capita of the society. In fact, 567 workers (42 525 W) and 94 bullocks (41 924 W) provide a level per capita of 85 W (84 449/994), while the village using only human power would have only 42 W (the 75 W power level of workers is
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decreased because of the 43% non-working population). Recalling the previous observation on the effects of power level requirement, note that animal power is a definite improvement in societies affected by endemic shortage of power. In fact, Sundarraj and Mitchell (1986) note that in the Panaykurichi village "decisions about what to plant and how to plant are based on the availability of labor". The use of animal power also decreases the cost of power applied by the village in agricultural activities. The lower power generation cost of animal power depends on the lower level of embodied energy of their food (r/is definitely higher for animals than for humans). Clearly, this wide difference is not generated by differences in physiological efficiency in converting food into power at the muscle level, but simply to the fact that bullocks eat raw food (saving, for example, the 2 J spent per nutritional joule when food is cooked). In rural areas, low quality feed is consumed by bullocks. Moreover, their ability to eat cellulosic biomass enables them to feed without competing with humans. In fact, they usually graze on marginal areas that would not be fit for agricultural activities. CONCLUSIONS Measuring the energetics of human labor in agriculture is highly complex. This complexity is related to the boundaries selected for a worker, the technological development of agriculture, population structure (age and sex), and the standard of living and consumption of resources by society. In poor, rural, agricultural societies, it is clear that human labor has a high relative value. This is in part one of the major reasons why children are highly valued and large families are typical under these conditions. In well-to-do, high-tech societies, human labor is of value, but has a different meaning, providing mainly a flow of information. Therefore, measuring the cost of human labor only in terms of food calories consumed per hour by a laborer is misleading if we are comparing a hand-produced agriculture and tractor-produced agriculture. The supporting energy resources for a laborer in a tractorpowered system may be more than 20 times higher than the energy supporting a laborer in hand-powered agriculture. Thus, our analysis suggests that using the total energy inputs per working member of society (instead of physiological energy input) has the advantage in assessing energy requirements for labor in agriculture for both developing and developed agriculture. REFERENCES Avery, D., Schramm,G. and Shapiro, K., 1978. ProductionSystemsin FragileEnvironments. In: Universityof Michigan- Scienceand Technologyfor ManagingFragileEnvironmentsin DevelopingNations. Ann Arbor, September1978.
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Durnin, J.V.G.A. and Passmore, R., 1967. Energy, Work and Leisure. Heinemann, London, pp. 30-104. Giampietro, M. and Pimentel, D., 1987. Food-energy security for 5 billion humans: the cost of a rapidly growing population. Paper presented to the 2nd Vienna Center Conference on Ecology and Economics, 26-29 September 1987, at Barcelona. Giampietro, M. and Pimentel, D., 1990a. Energy efficiency: assessing the interaction between humans and their environment. Ecol. Econ., in press. Giampietro, M. and Pimentel, D., 1990b. Energy efficiency and nutrition in societies based on human labor. Ecol. Food Nutr., submitted. Nicolis, G. and Prigogine, I., 1977. Self-organization in Nonequilibrium Systems. J. Wiley, New York. Odum, E.P., 1971. Fundamentals of Ecology. 3rd Edn., Saunders, Philadelphia, p. 251. Pimentel, D. and Pimentel, M., 1979. Food Energy and Society. Arnold, pp. 30-35. Rappaport, R.A., 1971. The flow of energy in an agricultural society. Sci. Am., 224: 117-133. Sundarraj, T.S.P. and Mitchell, R., 1986. Analysis of ecosystem structure and energy flow in a South Indian village. In: F.J. Hitzhusen and R.D. Macgregor (Editors), A Multidisciplinary Approach to Renewable Energy in Developing Countries. Publishing Horizons, Columbus, OH, pp. 141-167. Suzuki, S., Oshima, S., Tsuji, E. and Ohta, F., 1978. Interrelationships between nutrition, physical activity, and physical fitness. In: J. Parizkova and V.A. Rogozkin (Editors), Nutrition, Physical Fitness, and Health, University Park Press, Baltimore, MD, pp. 194-214. Tardo-Dino, F., 1985. Le collier de servitude: la condition sanitaire des esclaves aux Antilles frangaises du XVIIe au XIX e sircle. Paris: Editions caribdennes: Agence de coopdration culturelle et technique (Collection "Connaisance de la diaspora noire").