a FEA (College of Food Engineering) – Unicamp, CP 6121, CEP 13083-862 Campinas, SP, Brazilb Sıtio Duas Cachoeiras (Farm) – Rodovia SP 360, Km 121, CEP 13908-009 Arcadas, Amparo, SP, Brazilc Escuela de Ingenierıa Agroindustrial – Facultad de Ciencias Agropecuarias, Universidad National de Trujillo,Av. Juan Pablo II s/n. C. Universitaria, Trujillo, Peru
a r t i c l e i n f o
Article history:
Received 14 July 2006
Received in revised form
29 June 2007
Accepted 9 July 2007
Published on line 24 August 2007
Keywords:
Agroecology
Emergy assessment
Geographical Information System
Sustainable development
a b s t r a c t
In this work, emergy analysis was used in association with the Geographical Information
System (GIS) in order to improve the evaluation of family-managed farms that adopt either
the ecological or the chemical production models. Three small farms, located in Amparo
County, in Sao Paulo state, Brazil, were studied. One of them, Duas Cachoeiras farm, uses
agroecological concepts for its agricultural production. The two others (Santa Helena farm
and Tres Lagos farm) use the conventional chemical model. In an attempt to improve the
precision of the data used in emergy analysis, the Universal Soil Loss Equation (USLE) was
incorporated to the GIS tool to calculate the topsoil loss in the farms. The GIS tool also
allowed the calculation of the amount of rain water that infiltrates the ground and can
recharge the aquifer. This percolated water is a system output and was incorporated in the
emergy accounting. Another modification in comparison to previous emergy analyses was
that the renewability factor of each input was considered in the emergy accounting. Results
showed that the agroecological farm is more sustainable and can be used as a model for small
farms in their transition to ecological agriculture. The GIS–emergy tools were used to com-
pare the environmental performance of the four main productive areas of Duas Cachoeiras
farm (annual cultures, orchard, forest, and pasture). These results demonstrate the emergy
performance of each kind of land use and may be used in watershed planning.
1
Apaobc
content, pH, micro-biota, rain drop protection); therefore, the
0d
. Introduction
wrong, widespread idea is that in order to solve the famineroblem, it is necessary to increase agricultural productionnd that this increase can only be achieved through the use
f more industry-made chemicals (using fossil fuels). We mayelieve that there is, in fact, enough food, and that the problemomes not from production but from distribution; better still,
it is a problem of the production and consumption model. Sothe problem is not technological but political.
The chemical agriculture establishes a vicious cycle: chem-icals destroy the topsoil quality (structure, organic matter
ground absorbs less water and becomes nutrient-deficient andvulnerable to erosion. The soil loses ecological functions anddecreases in quantity and quality.
Fig. 1 – Study area. Brazil Country, Sao Paulo State, Amparo
This work incorporates some changes in emergy method-ology in order to get closer to reality. These changes are thefollowing:
38 e c o l o g i c a l m o d e l
In a future perspective where no fossil fuels are avail-able, food production will have to be supported by renewableresources. This situation brings uncertainties about the limitsfor human existence on the planet (MEA, 2005; Wackernagelet al., 1999; WCED, 1987; Meadows et al., 1972).
It is necessary to adopt agroecological procedures and toprepare new assessment tools to diagnose farms in a fast andefficient way. This analysis should consider the resources fromhuman economy as well as all contributions from nature toproduce the output and absorb environmental impacts. Theemergy methodology was proposed by Odum (1996) for sys-tem analysis, accounting, and diagnosis. The methodologywas improved during the last decade. Emergy measures ofnatural and economic resources are expressed in a commonbasis: solar equivalent Joules (seJ). Emergy analysis is based onBiology Energetics (Lotka, 1922), General Systems Theory (VonBertalanffy, 1968) and Systems Ecology (Odum, 1983). Severalecosystems and economic systems emergy evaluations weremade all over the world (Brown and Ulgiati, 2004; Higgins,2003; Brown and Buranakarn, 2003; Yang et al., 2003; Lefroyand Rydberg, 2003; Qin et al., 2000; Panzieri et al., 2002, 2000;Ulgiati and Brown, 1998), as well as theoretical studies anddiscussions (Herendeen, 2004; Hau and Bakshi, 2004; Brownet al., 2004; Bastianoni and Marchettini, 2000). However, thereare few emergy studies that evaluate agricultural production(Ortega et al., 2002; Martin et al., 2006; Castellini et al., 2006),especially of small family farms, which have singular charac-teristics.
The objective of this research is to demonstrate thatemergy analysis can show farm performance more clearlywith the support of Geographical Information Systems, andto suggest better management practices for the improvementof farming systems.
2. Methodology
2.1. Description of the farming systems
Two agricultural production models were compared: (a) thechemical or conventional model, which has the increase ofeconomic profit as its unique objective, and (b) the agroe-cological model, that envisions sustainable development.Three agricultural farms located in Amparo County, Sao Paulostate, Brazil (Fig. 1) were evaluated: Duas Cachoeiras farm(29.7 ha), Santa Helena farm (15.6 ha) and Tres Lagos farm(25.3 ha). The three farms have the same climate condi-tions (solar radiation, wind speed and direction, amount ofrain, relative humidity), the same soil characteristics, thesame land relief, approximately the same area, and all arefamily managed. The main difference between the farmsis the production model (conventional or agroecological)adopted.
Duas Cachoeiras farm adopted Agroecology in 1985. Duringthe last two decades, it has implemented soil decontami-nation and natural fertility recovery, reforestation and local
biodiversity recovery, chemical input free food production,internal residue cycling (nutrients), enhanced use of localresources, and introduction of extension work, ecologicaltourism and education. The other two farms use the chemical
County. TL: Tres Lagos farm; DC: Duas Cachoeiras farm; SH:Santa Helena farm.
model. Santa Helena produces vegetables, fruits, and coffee.Tres Lagos produces milk and meat.
2.2. Emergy methodology
The emergy analysis is based on the works of Odum (1996),Ulgiati and Brown (1998), and Brown and Ulgiati (2004). Thefirst step in the application of the emergy methodology is toconstruct system diagrams to identify all components andtheir relationships. Fig. 2 shows an aggregated flow diagramthat uses a symbolic language to represent the flows andinteractions. Table 1 shows the description of the emergyflows.
The second step is to build the emergy table, placing thenumerical value and the units of each flow mentioned in thediagram. The table allows the conversion of all the resourcesin terms of solar emergy Joules using transformities (Odum,1996). The third step is to obtain the emergy indicators (Table 2)in order to evaluate the system environmental performance.
Fig. 2 – Emergy system diagram of a generic productionsystem.
e c o l o g i c a l m o d e l l i n g
Table 1 – Classification of emergy flows used inenvironmental accounting
Inputs and services Description
Nature contributions (I) R + NRenewable natural
resources (R)Rain, materials, andservices from preservedareas, nutrients from soilminerals and air
Non-renewable naturalresources (N)
Soil, biodiversity, peopleexclusion
Feedback from economy (F) F = M + SMaterials (M) M = MR + MN
1) The renewability factor of each item have been consid-ered, according to Ulgiati et al. (1994), Ortega et al. (2005,2002), Ortega and Polidoro (2002), Ulgiati et al. (2005) andCavalett et al. (2006). The emergy indexes were slightlychanged to evaluate sustainability more properly, by con-sidering renewability of each of the economic resourceused. The incorporation of the renewability factor is partic-ularly valid when the system uses materials and services,purchased at the local or regional economy, that arenot totally considered as nonrenewable resource (such as
labor, electricity power, manure and services). Thus, theincorporation of the renewability factor should be addedto emergy methodology when applied to assess sustain-ability (Ortega et al., 2005, 2002).
Table 2 – Emergy indicators
Indicator Expression
Solar transformity (Tr) Y/E
Renewability (%R) 100x(R + MR + SR)/Y
Emergy yield ratio (EYR) Y/(MN + SN)
Emergy investment ratio (EIR) (MN + SN)/(R + MR + SR + N
Emergy exchange ratio (EER) Y/[($) × (seJ/$)]
Environmental loading ratio (ELR) (N + MN + SN)/(R + MR + S
Emergy sustainability index (ESI) EYR/ELR
Source: Ortega et al., 2002; based on Odum, 1996.
2 1 0 ( 2 0 0 8 ) 37–57 39
(2) The soil loss was calculated through the Univer-sal Soil Loss Equation (USLE) in accordance withWischmeier and Smith (1978) and the aid of the Geo-graphical Information System (GIS). Soil loss equationenumerates the main factors that influence the rainerosion. The equation (USLE) is expressed as follows:A = R × K × L × S × C × P, where A = soil loss given by areaunit [t/(ha year)]; R = rain factor; expression of rain erosion[MJ mm/(ha h year)]; K = soil erodibility factor [t h/(MJ mm)];L = slope length factor [non-dimensional]; S = slope steep-ness factor [non-dimensional]; C = cover-managementfactor [non-dimensional]; P = support practice factor [non-dimensional]. Aerial photographs were obtained from thearchives of Amparo City Hall (scale 1:30,000), coveringthe three research units. Initially, they were geographi-cally located through ERDAS Imagine software (version 8.7)and exported to GIS software (ArcGIS 9.0) for construct-ing thematic maps (land use and soil type). The factorsrequired by soil loss equation were obtained throughseveral works (Resende and Almeida, 1985; Bertoni andLombardi Neto, 1999; Guerra et al., 1999; Gabriels etal., 2003; Lu et al., 2004; Shi et al., 2004) and linkedto these maps. An Arc Macro Language (AML) routinewas used to determine the topographical factor in ArcInfo Workstation 9.0, according to Lu et al. (2004). TheAML routine was developed by Hickey (2000) and VanRemortel et al. (2001), and is available at the Internetaddress: http://www.cwu.edu/∼rhickey/slope/slope.html.The flowchart used to calculate soil loss can be seen inFig. 3. Through this procedure, the amount of soil losscalculated is closer to the reality of the specific location;
(3) For the agroecological system analyzed in this work,the ground macronutrients (nitrogen, potash, phospho-rus and limestone) removed in the harvest (see Table 3)
have been considered as renewable resources from nature,since the process used in the farm makes the acquisi-tion of macronutrients from external sources unnecessary(Agostinho, 2005). The green manure (fertilization using
Meaning
The ratio of the emergy of the output divided bythe energy of the products.The ratio of the renewable inputs divided by thetotal emergy of the system.The ratio of total emergy used divided by theemergy of nonrenewable inputs from theeconomy.
) The ratio of emergy of nonrenewable economicinputs divided by the emergy of natureinvestment (nature input plus renewable inputsfrom economy).The ratio of emergy delivered by the producer tothe economy divided by the emergy receivedfrom the buyer.
R) The ratio of nonrenewable emergy andrenewable inputs.Indicates the sustainability of the system.
Duas Cachoeiras farm, year 2003.a Source: Table of Chemical Composition of Foods. U.S. Department of Agriculture, Agricultural Research Service. Nutrient Database for Standard
Reference, release 14. Amount of nutrients in 100 g of sample. Available2004. P, phosphate; K, Potash; N, Nitrogen; Ca, Limestone;
b The amount of nitrogen corresponds approximately 16% of protein amo
Fig. 3 – Flowchart used in soil loss calculation.
at http://www.unifesp.br/dis/servicos/nutri, accessed on 18th June
unt.
leguminous plants), the incorporation of animal manure,compost and organic matter surplus after harvest tothe ground ensure that the amount of ground mineralsremoved in the crop could be replaced in a renewable way.Since 1985, Duas Cachoeiras farm uses no chemical inputsin food production, displaying a ground mineral extractionequal to or lower than natural restoration;
(4) The fact that the farms have native vegetation areas,which besides serving as a natural defense againstplagues, causes some rain water to infiltrate the ground.This increases the amount of water in underground water-sheds (Agostinho, 2005). The land use, soil type, soilhandling and landscape slope are the most importantfactors that affect the water pathways after the rain ini-tiates. There are mathematical models able to estimatethe water infiltration in the ground, runoff and intercep-tion by vegetal covering, but all of them demand many rawdata. The calculation of water infiltration into the groundconsidering vegetable covering was not the main aim ofthis paper, thus there were used previous works by otherresearchers (Adekalu et al., 2007; Souza and Alves, 2003;Centurion et al., 2001; Lima, 1996). The following percent-ages were considered: 30% for forest areas and silviculture;20% for Napier grass, maize, orchard, chayote, meadowsand annual culture; 5% for grassland and cultures with low
biomass accumulation. Through the GIS land use map ofthe three properties (Figs. 4–6) with the values of plant cov-ering areas expressed in hectares and the respective raininfiltration ratio (%), it was possible to estimate the water
e c o l o g i c a l m o d e l l i n g 2 1 0 ( 2 0 0 8 ) 37–57 41
Dua
(biomass was considered as a flow of renewable natural
Fig. 4 – Land use of
infiltrated into the ground (see Tables 4–6). The infiltratedwater was considered in the emergy analysis as anotheroutput. A great part of this high quality resource leaves thefarms and become available to the down-stream water-shed users;
5) One characteristic of small family farms in Brazil is thediversity of their production and the presence of native
vegetation areas in a greater proportion than of the chem-ical farming enterprises (agribusiness), because the smallfarms obey environmental laws and need the environ-mental services of preserved forested areas. In preserved
Fig. 5 – Land use of Santa Helena farm.
s Cachoeiras farm.
natural areas, the accumulation of biomass does not leavethe system immediately, it is a novelty to consider thischaracteristic in the emergy evaluation. The farm biomassaccumulation was estimated through net primary produc-tivity (Aber and Melillo, 2001) data and land use mapsobtained from GIS (see Tables 7–9). The native vegetation
resources because the farm depends on the environmentalservices and products produced in those areas.
Fig. 6 – Land use of Tres Lagos farm.
42 e c o l o g i c a l m o d e l l i n g 2 1 0 ( 2 0 0 8 ) 37–57
Table 4 – Total percolated water in Duas Cachoeiras farm, year 2003
Vegetation covering Area (ha) Total water in areaa
a 1250 mm of water/year.b Percentage estimate about: Adekalu et al., 2007; Souza and Alves, 2
(6) Finally, the emergy ternary diagram proposed by Giannettiet al. (2006) was used to graphically represent the emergysustainability index (ESI) to help the visualization of
emergy flows (R, N and F) of the studied systems. This rep-resentation granted more clarity to the interpretation ofresults.
Table 6 – Total percolated water in Tres Lagos farm, year 2003
Vegetation covering Area (ha) Total water in areaa
a 1250 mm of water/year.b Percentage estimate about: Adekalu et al., 2007; Souza and Alves, 2003; C
enturion et al., 2001; Lima, 1996.
3. Results and discussion
The emergy indices calculated in this paper (see Table 2)were: transformity (Tr), renewability (%R), emergy yieldratio (EYR), emergy investment ratio (EIR), emergy exchangeratio (EER) and environmental loading ratio (ELR). The
Percolationb (%) Total water percolated(million of l/year)
30 7.4220 8.4720 1.27
2 4.4420 0.65
5 0.380 0.00
22.64
enturion et al., 2001; Lima, 1996.
e c o l o g i c a l m o d e l l i n g 2 1 0 ( 2 0 0 8 ) 37–57 43
Table 7 – Total biomass flow in Duas Cachoeiras farm, year 2003
Vegetal covering Area (ha) Net primary productivitya
(gC/m2/year)Reference for (gC/m2/year) Total biomass storagedb
(kg/year)
Forest 2.00 800 Aber and Melillo, 2001 32,000Mixed forest 3.83 800 Aber and Melillo, 2001 61,280Riparian forest 1.91 800 Aber and Melillo, 2001 30,560Orchard 0.30 290 Aber and Melillo, 2001 1,740Orange 0.04 290 Aber and Melillo, 2001 232Meadow 3.96 315 Aber and Melillo, 2001 24,948Napier grass 2.90 400 Estimated 23,200Annual culture 4.30 290 Aber and Melillo, 2001 24,940Clean pasture 1.44 225 Aber and Melillo, 2001 6,480Dirty pasture 6.22 300 Estimated 37,320Grassland 0.87 225 Aber and Melillo, 2001 3,915Lake 0.16 225 Aber and Melillo, 2001 720
Total biomass flow 247,335
a 55% of total biomass = carbon (Ponce-Hernandez et al., 2004).b Total biomass storaged = area × net primary productivity.
Table 8 – Total biomass flow in Santa Helena farm, year 2003
Vegetal covering Area (ha) Net primary productivitya
(gC/m2/year)Reference for (gC/m2/year) Total biomass storagedb
(kg/year)
Forest 3.18 800 Aber and Melillo, 2001 50,880Reforestation 1.11 800 Aber and Melillo, 2001 17,760Eucalyptus tree 0.30 800 Aber and Melillo, 2001 4,800Peach crop 0.13 290 Aber and Melillo, 2001 754Coffee crop 5.57 290 Aber and Melillo, 2001 32,306Dirty pasture 1.16 300 Estimated 6,960Bell pepper crop 0.93 290 Aber and Melillo, 2001 5,394Chayote crop 0.87 290 Aber and Melillo, 2001 5,046Grassland 0.27 225 Aber and Melillo, 2001 1,215Lake 0.18 225 Aber and Melillo, 2001 810
Total biomass flow 125,925
etwm
a 55% of total biomass = carbon (Ponce-Hernandez et al., 2004).b Total biomass storaged = area × net primary productivity.
mergy sustainability index (ESI) was used only in aernary diagram. Moreover, some Best Management Practicesere suggested as a means to improve their perfor-ance.
Table 9 – Total biomass flow in Tres Lagos farm, year 2003
Vegetal covering Area (ha) Net primary productivitya
a 55% of total biomass = carbon (Ponce-Hernandez et al., 2004).b Total biomass storaged = area × net primary productivity.
3.1. Comparing agricultural production models
The emergy evaluation of farms is presented in Tables 10–12,and the aggregate emergy flows are presented in Table 13. In
Reference for (gC/m2/year) Total biomass storagedb
(kg/year)
Aber and Melillo, 2001 31,680Estimated 27,120Aber and Melillo, 2001 2,958Aber and Melillo, 2001 79,875Aber and Melillo, 2001 1,508Aber and Melillo, 2001 2,745Aber and Melillo, 2001 1,980
147,866
44e
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gic
al
mo
de
ll
ing
21
0(2
00
8)
37–57
Table 10 – Emergy evaluation of Duas Cachoeiras farm (DC) in the year 2003 (emergy flows in E + 13 seJ/ha/year)
Note Item Renewabilityfraction
Unit Unit/ha/year seJ/unit Reference for seJ/unit Renewableemergy flow
he emergy evaluation tables, all the flows that enter the sys-em have been converted into emergy through transformityalues available in the literature, after their applicability waserified in the studied systems. The flows of materials andervices that enter the system were multiplied by their cor-esponding renewability factors, in order to divide them inheir renewable and non-renewable fractions. Total renewableR), non-renewable (N), services (S) and materials (M) emergyows were calculated by summing up the respective fractionsf each input flow.
The renewability factor of purchased inputs used in thisork was obtained from previous works about soybean andaize production in Brazil (Ortega et al., 2005, 2002) and about
sh production (Cavalett et al., 2006).Table 14 presents the emergy indicators for the three prop-
rties.
.1.1. Transformityastianoni and Marchettini (2000), studying systems that
nclude co-production of goods, calculated their transformityTr = Y/˙Ep) by dividing the total emergy entering the systemY) by the sum of energies of all co-products (˙Ep) insteadf using the energy of the main product (Ep) as the denom-
nator. According to these authors, this calculation providesbetter indicator in cases where production is diversified.
ince small agricultural properties in Brazil usually cultivateore than one product, the present work has adopted this
achoeiras), 870,000 seJ/J (Santa Helena), and 2,620,000 seJ/JTres Lagos). These results indicate that family-managedcological small farms can be more efficient in the trans-ormation of potential energy when compared to chemicalamily-managed farms.
.1.2. Renewabilityhe renewability ratio (%R = R/Y) is the percentage of renew-ble emergy used by the system. In the long term, productionystems with a high percentage of renewable emergy are likelyo be more sustainable and to prevail (they are more able tourvive the economical stress) than those using a high amount
f non-renewable emergy (Brown and Ulgiati, 2004; Lefroy andydberg, 2003).
The renewability of Duas Cachoeiras farm was 59%, whileor Santa Helena farm and Tres Lagos farm the values were
419.22 157.08
1444.48 1784.08
34% and 20%, respectively, indicating that agroecological prop-erties are more sustainable than chemical ones.
Since non-renewable resources are the driving force of themajority of the current production systems, the foreseen oildepletion in the next decades will be a great problem that sys-tems with a low renewability indicator will have to face. Theadoption of agroecological practices (product diversification,nutrient recycling, planning of cultures to favor water percola-tion, conservation of topsoil, and biological control of plagues)reduces the purchasing of chemical inputs and contributes formore renewability. Agenda 21 recommendations or Best Man-agement Practices can be used to promote the adjustment ofchemical–agriculture farms in order to reduce negative socialand environmental impacts.
3.1.3. Emergy yield ratioThe emergy yield ratio (EYR = Y/F) is the ratio between totalemergy and emergy value of purchased inputs. This ratio is ameasure of the ability of a process to exploit and make localresources available by investing in outside resources. It pro-vides a measure of the appropriation of local resources by aprocess, which can be read as a potential additional contribu-tion to the main economy, gained through the investment ofresources.
The EYR for Duas Cachoeiras was of 15.4, while for SantaHelena and Tres Lagos the values were 4.9 and 18.8, respec-tively. These results indicate that Duas Cachoeiras and TresLagos farms use more natural resources (renewable and non-renewable), showing less dependency on economic resources.However, although Tres Lagos farm EYR value was high, 81% ofits nature emergy input (R + N) is non-renewable (N), while forDuas Cachoeiras only 39% are non-renewable natural emergyinput (N).
Intensive conventional agricultural systems have EYR val-ues lower than two (Ortega et al., 2002; Panzieri et al., 2000;Odum, 1996; Ulgiati et al., 1994), indicating that all studiedfarms display a low dependency on non-renewable economicresources.
3.1.4. Emergy investment ratioThe emergy investment ratio (EIR = F/I) evaluates if a process
is a good user of the invested emergy while compared to otheralternatives for the use of the same resources (Brown andUlgiati, 2004). The EIR value for Duas Cachoeiras farm was0.07, while for Santa Helena farm and Tres Lagos farm they
48 e c o l o g i c a l m o d e l l i n g 2 1 0 ( 2 0 0 8 ) 37–57
Table 14 – Emergy indicators calculated considering the renewability factor of material and services—year 2003
Emergy indicators Duas Cachoeiras farm Santa Helena farm Tres Lagos farm
tively.Emergy sustainability index (ESI) measures the potential
contribution of a resource or process to the economy perunit of environmental loading (Brown and Ulgiati, 2004). ESI
Fig. 7 – Ternary emergy diagram for assessment of farms in
EIR 0.07EER 4.31ELR 0.69
were 0.25 and 0.06, respectively. The results indicate that both,Duas Cachoeiras and Tres Lagos farms, use more environ-mental inputs than Santa Helena farm. Therefore, productioncosts are reduced, representing better market performance.Current global trends indicate that low cost energy will notbe available in the future. Moreover, agriculture could facemany difficulties due to market opening in consequence ofglobalization (Campbell and Laherrere, 1998). Thus, produc-tion systems based on non-renewable natural resources maynot be able to compete with systems characterized by lowereconomic investment (F) and greater renewable nature con-tribution (R), and might become unsustainable in the comingfuture. Tres Lagos can be considered to have a good EIR invest-ment ratio, although about 81% of its natural resources comefrom non-renewable resources, while for Duas Cachoeirasfarm this percentage is only 39%. This result indicates thatTres Lagos farm is highly dependent on non-renewable nat-ural resources, and therefore is not sustainable over a longperiod.
3.1.5. Emergy exchange ratioThe emergy exchange ratio (EER = Y/(sales × emergy/money))is calculated by dividing the total solar emergy of productsby the emergy received in the sales. The EER measures theadvantage of one partner over the other, providing a measureof who “wins” and who “loses” in economic trade (Brown andUlgiati, 2004, 2001).
The calculated EER value for Duas Cachoeiras farm was 4.3,while for Santa Helena farm and Tres Lagos farm it was 2.9and 14.0, respectively. The indicator was greater than one forthe three properties, indicating that all supply more emergyto the consumer than they receive in exchange—or, in otherwords, they have received less emergy than they have used toproduce goods. Tres Lagos presented the worst performancewhile Santa Helena presented the best one. Duas Cachoeirasfarm adds value to its products, but does not receive backall emergy that was employed in the production. Farm prod-uct prices usually underestimate their real cost, and shouldtherefore be higher than those currently determined by themarket.
3.1.6. Emergy loading ratioThe emergy loading ratio (ELR) is an index of pressure thatthe system carries out on the environment and can be consid-ered as a measure of ecosystem stress. ELR values lesser than2 indicate low impact on the environment; values between
2 and 10 mean that the system cause a moderate impact;up to 10 mean that the system cause big impact (Brown andUlgiati, 2004). For the agroecological model, represented byDuas Cachoeiras farm, the environmental impact was small
0.25 0.062.85 13.991.94 3.92
(0.69). For the conventional model, the result was a moder-ate impact (1.94 for Santa Helena farm and 3.92 for Tres Lagosfarm). Agroecology makes possible the use of more renewableresources.
3.1.7. Ternary diagramTo assist environmental decision making based on emergyanalysis, a ternary diagram proposed by Giannetti et al. (2006)was used (see Fig. 7).
The emergy ternary diagram has three components: R, Nand F. Each corner of the triangle represents a component andeach side a binary system. The composition of any systemplotted on a ternary diagram can be determined by readingfrom zero along the basal line at the bottom line of the diagramto 100% at the vertex of the triangle (Giannetti et al., 2006).The size of dots in Fig. 7 is proportional to the emergy used(Y), showing that Tres Lagos farm (3) uses a greater amountof emergy than the other two farms. The diagram shows thatDuas Cachoeiras (1) and Tres Lagos (3) use approximately thesame small percentage of nonrenewable purchased emergy(6%) but Duas Cachoeiras uses a greater amount of renewableinputs (59%), while Tres Lagos uses more nonrenewable nat-ural inputs (74%). This explains the position on the ternarydiagram of these two farms closer to R and N vertices, respec-
2003. (1) Duas Cachoeiras farm; (2) Santa Helena farm; (3)Tres Lagos farm; R, renewable resources; N, non-renewablenatural resources; F, non-renewable economic resources;ESI, emergy sustainability index.
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ndicates the system benefit/cost ratio; e.g., the benefit pro-ortioned by a process to the economy in relation to itsnvironmental impact. Fig. 7 shows that Santa Helena (2)resents the lowest ESI value, even though it uses a lowermount of non-renewable natural resources than Tres Lagos3). In order to obtain better performance, Santa Helena (2)hould reduce the use of economic inputs. Duas Cachoeiras1) presented the best performance, but Santa Helena (2) andres Lagos (3) farms also obtained an ESI higher than one,ndicating that they contribute to economy through low envi-onmental load.
.2. Comparing vegetation coverings
nitially, the Geographical Information System was used torepare a map of land use. After that, was realized an emergynalysis of vegetation covering by annual culture, orchard,asture, and forest of Duas Cachoeiras farm. Table 15 presentshe emergy indicators for these subsystems.1
.2.1. Transformityorest areas have the lowest transformity (120,000 seJ/J), indi-ating high efficiency and low use of non-renewable economicesources (7% of total emergy used). The pasture revealed
transformity of 405,000 seJ/J, and 75% of the total emergysed was derived from non-renewable natural resources.rchard area presented the greatest transformity, 980,000 seJ/J,nd 95% of its total emergy input was due to humanconomy services. Annual culture showed an intermediateransformity (305,000 seJ/J) and reasonable use of renewableatural resources, due to incorporation of agroecologicalractices.
.2.2. Renewability factororest area presented the best renewability (85%) while pas-ure showed the worst (18%). Orchard and annual culturebtained a good value (70% and 44%, respectively). Pastureenewability can be improved through the reduction of soiloss, since it is responsible for approximately 75% of all emergysed and is considered a natural non-renewable resource. Inrchard and annual culture areas, the use of labor and mate-ials (for maintenance) could decrease. The results obtainedndicate that forest, annual cultures, and orchard areas areighly sustainable due to the ecological practices and man-gement.
.2.3. Emergy yield ratioorest area presented the best emergy yield ratio (20.22), whilerchard showed the worst (3.37). Pasture and annual cultureresented respectively 14.49 and 8.23. It is important to pointut that for pasture, 75% of all emergy used is derived from
oil loss, while for the annual culture area this percentageells down to 43%. In order to obtain a better performance, therchard should reduce the use of resources purchased fromhe economy (external labor and materials for maintenance)
1 To receive the emergy analysis table of Duas Cachoeirasarm vegetation covering, contact Enrique Ortega [email protected]>.
2 1 0 ( 2 0 0 8 ) 37–57 49
and should increase the use of renewable resources (highernumber of plants per area). Forest uses the lowest amountof purchased resources (7% of total emergy), followed by pas-ture (17%), annual cultures (20%) and orchard (95%), suggestinga sequence of covering with lower dependency on externalinputs.
3.2.4. Emergy investment ratioFor this indicator, the forest area demonstrates that for eachunit of emergy of natural resources only 0.05 units of eco-nomic resources are necessary, meaning low production cost.Therefore, their products could be competitive in an idealmarket (without subsidies and hidden externalities). Orchardarea had the worst performance (0.42), since this area needsmore economic resources (mainly labor and maintenancematerials). Annual culture and pasture areas presented goodperformances, 0.14 and 0.07, respectively, but it is importantto point out that 43% of the total of emergy used in annual cul-ture came from a non-renewable natural resource (soil loss),while pasture area used 75% and forest used 9% of the samekind of source. Thus, the pasture area would have to decreasesoil losses through the use of terraces with natural vegetationlines, in order to improve environmental performance.
3.2.5. Emergy exchange ratioDue to market forces that tend to reduce the prices of agricul-tural products, emergy exchange ratio (EER) of all subsystemsindicate that more emergy is being supplied through theproducts than being received back as payment. In an ideal sit-uation, the EER is equal to 1—in this case, the exact amountof emergy used to yield a product should be received back inexchange.
As it can be seen in Table 15, the forest presented thebest performance (2.53) of all subsystems, followed by pas-ture (3.17), annual culture (5.67) and orchard (6.03). In orderto improve this indicator, vegetation covering should becomemore efficient in energy transformation and should add valueto its products, through certification or through the use of dif-ferent sales channels such as organic/agroecological stores orfood markets.
3.2.6. Emergy loading ratioPasture is the vegetal covering that causes the greatest envi-ronmental impact (4.43). The others systems, annual culture,orchard and forest resulted in lower values: 1.25, 0.43 and 0.17,respectively. The forest and orchard systems uses more renew-able resources than non-renewable ones then their ELR valuesare lesser than 1, thus, these systems are extremely sustain-able.
3.2.7. Ternary diagramA ternary diagram for Duas Cachoeiras vegetation coveringwas also made (Fig. 8), in the same way as for emergy indica-tors in the farm comparison.
Again, the size of dots represents the amount of emergyused by the system. Thus, orchard (2) used more emergy
that the others. The diagram indicates that subsystems (3)and (4) use approximately the same percentage (5%) of non-renewable purchased resources; however, subsystems (4) uselower amounts of non-renewable natural resources (9%) and
50 e c o l o g i c a l m o d e l l i n g 2 1 0 ( 2 0 0 8 ) 37–57
Table 15 – Emergy indicators calculated considering the renewability factor of material and services for the vegetationcovering of Duas Cachoeiras farm—year 2003
Emergy indicators Annual culture 4.3 ha Orchard 0.3 ha Pasture 1.44 ha Forest 7.75 ha
greater amounts of renewable emergy (86%), resulting in abetter performance of emergy indicators. For the sustainabil-ity index, forest (4) obtained the best performance, althoughannual culture (1) and orchard (2) also have a high value. Pas-ture (3) was in the 2.5 < ESI < 5 range, indicating that it mayhave a great contribution to the economy at low environmen-tal impact. It’s important to note that the systems plotted inthe ternary diagram are distant to the F vertex because this is acharacteristic of small family farms model of agricultural pro-duction that uses low quantities of nonrenewable resourcesfrom economy and high quantities of renewable flows fromnature. The systems (1) and (3) are nearest to the N vertex dueto soil loss.3.3. Best Management Practices (BMPs) to improvefarming systems
The emergy analysis was successfully used with in the diag-nosis of the properties studied in this work. However, for amore comprehensive work, it is necessary to suggest prac-tices and public policies in order to improve farm performance.Cavalett et al. (2006) suggested some Best Management Prac-tices for integrated farm systems for corn, swine, and fishproduction in the South of Brazil. According to the authors,“BMPs are the best means of preventing environmental prob-lems while allowing production to be held in an economically
efficient manner.” In a broad sense, BMPs aim to reducethe dependency on economic inputs, to reduce the usageof non-renewable natural resources, to improve the sys-tem’s efficiency in the transformation of potential available
energy, and to promote the conservation of environmentalservices.
According to the results obtained in this research, the fol-lowing BMPs can be suggested to small family farms for betterenvironmental and economic performances:
(a) Reduce the usage of chemical inputs (until elimination)through the promotion of recycling, crop rotation, cropdiversity, composting and mulching with the use of localmanure and crop residues.
(b) Establish economical and environmental incentives tofarmers in order to promote the preservation of naturalforests. This will increase the area of legal reserve in thesystem and, consequently, will help to decrease soil loss,improve biological control of plagues, and increase the rainwater infiltration in the ground.
(c) Correct land use, considering its declivity, properties andclimate conditions. This will decrease soil erosion andincrease rain water percolation in aquifer and watershed.
d) Take into consideration the needs of people in the regionand the agricultural watershed potential.
(e) Obtain certification to testify that farmers that follow eco-logical procedures have high sustainability and can havegreater profit per unit of area. By using emergy indica-tors, certification could suggest the proper price for eachproduct (Cavalett et al., 2006).
Great efforts from the government, from research institu-tions, and from technical assistance agents will be necessaryto demonstrate the great potential of ecological agricultureto farmers through Best Management Practices. Besides theBMPs, some ideas for the elaboration of public policies weresuggested:
(a) Promote the adoption of agroecological farming conceptsin critical watershed areas in order to increase waterquality and quantity. Ecological farms do not use haz-ardous chemical inputs, thus improving soil structure andincreasing rain water infiltration in the ground.
(b) Promote the adoption of Agroecology in agrarian reformsettlements, because it lowers the dependency on externaleconomic resources, establishes better interaction withthe environment, has great product diversity, and is awater producing system.
All the BMPs and suggestions described above have twoobjectives: (a) to improve the economic yield of agriculturalproducers and (b) to increase environmental services that arein full decline (66% in accordance with MEA (2005)) and whose
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alue was estimated in US$ 33 trillion (33.00E + 12)/year for thelanet (Costanza et al., 1997).
. Conclusion
he combination of emergy analysis with the Geographi-al Information System improved the data quality of farmiagnosis, since it allowed a more precise calculation ofoil loss − soil is a very important non-renewable naturalesource.
GIS allowed us to estimate the amount of rain water infil-rated into the ground. Percolated water was considered ao-product of the agricultural ecosystem.
The utilization of the renewability factor is adequate, sinceocal resources could have intermediate or high renewabil-ty values. This characteristic made these resources “moreustainable” in comparison to resources from other regionsnd to those that undergo more industrial transformationsnd need to be moved over long distances. With this concept,e have a better description of small family farms, improv-
ng the proposals of environmental resources usage throughest Management Practices. Duas Cachoeiras farm had a bet-er performance in almost all emergy indicators compared tohe other two farms, which use chemical agricultural produc-ion. The agroecological system revealed: (a) good efficiencyn energy transformation (low value of transformity); (b) lessependency on economic resources, because only 11% of totalmergy used comes from this source; (c) high sustainabil-ty, with a renewability of 59%; (d) low environmental impactELR = 0.69) and a greater sustainability index compared to the
ther systems. Thus, the expansion of agroecological produc-ion models should be promoted and encouraged to promoteocial welfare, economic profit, and good relationship with thenvironment.
Through emergy analysis, we could where the system is outf balance in relation to nature, making it possible to suggest
Rain Rainfall = 1.25 m3/mWater energy = 5000Water density = 100Conversion = (m3/mEnergy = 6.25E + 10 J
Wind Air density = 1.3 kg/Annual average of wGeotropic wind = 3.Drag coefficient = 0.Conversion = (29.7EEnergy = 1.52E + 10 J
Water spring Outflow of the sprin
2 1 0 ( 2 0 0 8 ) 37–57 51
management practices to improve farm performance. The useof the GIS and the renewability factor resulted in a greater pre-cision in emergy analysis, but for the diagnosis to be complete,it is necessary to consider the negative and positive external-ities produced by the systems.
Emergy analysis of the vegetation covering, which can becalled “spatial emergy analysis”, must be studied to allow itsapplication in future projects concerning the analysis of largersystems (watersheds, for example), where the acquisition ofinput and output data demands time and money, and manytimes do not exist. An adequate satellite image or air photo-graph in good scale could assist in the application of “spatialemergy analysis” in watersheds.
The emergy assessment combined with GIS has provedto be a useful tool in performing environmental accountingof production systems, since it takes into considera-tion the contribution of nature beyond production means,labor, and services, according to different spaces. Theemergy methodology can be very helpful in develop-ing administrative tools, which are needed for planningmore sustainable development, according to the Agenda 21recommendations.
Acknowledgements
We are grateful to Antonio Padilha for his kind help in col-lecting data. Thanks also to Consuelo Pereira, Otavio Cavalett,and Gabriela Vernaza for reviewing the paper. Feni DalanoRoosevelt Agostinho is grateful to CAPES (Coordenacao deAperfeicoamento de Pessoal de Nıvel Superior) for the master’sdegree grant. This study was made possible through CAPES’
financial support.
Appendix A. Calculations and references toTable 10
ind velocity = 5.55 m/s33 m/s 60% of 5.55001 adimensional+ 4 m2/29.7 ha) × (kg/m3) × (m/s)3 × 0.001 × (3.16E + 7s/year)/ha year
gs = 35659 m3/year
52 e c o l o g i c a l m o d e l l i n g 2 1 0 ( 2 0 0 8 ) 37–57
Appendix A (Continued )Water used in system = 1.36E + 4 m3/yearConversion = (m3/year) × (1/29.7 ha) × (1000 kg/m3)× (5000 J/kg)Energy = 2.29E + 9 J/ha year
5 River water Time of pump use = 0.50 h/dayOutflow = 1.00 l/sOutflow = 6.48E + 2 m3/yearConversion = (m3/year) × (1/29.7 ha) × (1000 kg/m3)× (5000 J/kg)Energy = 1.09E + 8 J/ha year
6 Nitrogen Mass flow = 313.2 kg/ha year7 Phosphate rock Mass flow = 44.0 kg/ha year8 Potash Mass flow = 194.6 kg/ha year9 Limestone Mass flow = 21.7 kg/ha year
4 Water spring Water spring outflow = 6312 m3/yearWater used in the system = 5.05E + 3 m3/yearConversion = (m3/year) × (1/25.3 ha) × (1000 kg/m3)× (5000 J/kg)Energy flow = 9.98E + 8 J/ha year
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