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Fearnside, P.M. 1995.  Hydroelectric dams in the Brazilian Amazon as sources of 'greenhouse' gases. Environmental Conservation 22(1): 7-19.


ISSN: 0376-8929


Copyright: Cambridge University Press


The original publication is available at     <publisher link>







Philip M. Fearnside, MS, PhD (Michigan)

Research Professor, Department of Ecology,

National Institute for Research in the Amazon (INPA)

Caixa Postal 478

69011-970 Manaus, Amazonas



              7961 words

              14 Nov. 1994

              25 Feb. 1995

                   TABLE OF CONTENTS


Table of Contents ..........................................  i


List of Tables .............................................  ii


List of Figures ............................................ iii


INTRODUCTION ................................................. 1






     Parameters for Emissions Calculations ................... 10


     Simulation of Emissions over Time ....................... 12


     Comparison with Fossil Fuel Emissions ................... 14


CONCLUSIONS .................................................. 15


ACKNOWLEDGMENTS .............................................. 16


SUMMARY ...................................................... 17


REFERENCES.................................................... 18

List of Tables


Table I:  Existing and planned dams in Brazilian Amazonia.


Table II:Riverbed areas in Amazonian reservoirs.


Table III:Flooding by hydroelectric dams.


Table IV:Biomass by stratum at Manaus: Approximate dry weights.


Table V:Biomass present and division by zones in Amazonian reservoirs.


Table VI:Parameters for hydroelectric dam emissions calculations.


Table VII:Approximate quantities of biomass present in 1990.


Table VIII:Methane emissions from Amazon floodplain ecosystems.


Table IX:Greenhouse gas fluxes by process in 1990 from hydroelectric dams.


Table X:Calculation of emissions from fossil fuel displaced by Balbina and Tucuruí.


Table XI:Comparison of Balbina and Tucuruí 1990 hydroelectric generating emissions with other emission sources.





List of Figures


Figure 1:  Brazilian Amazonia.


Figure 2:  Existing and planned reservoirs in Brazilian Amazonia.


Figure 3:  Zones for distribution of biomass in reservoirs.


Figure 4: Hydroelectric greenhouse gas emissions (CO2-equivalent   carbon).


Figure 5:  Balbina: CO2 and CH4 emissions (million t of gas).


Figure 6: Balbina: Greenhouse gas emissions (CO2-equivalent        carbon).



     Hydroelectric dams are commonly believed to have no serious impact on the greenhouse effect, in contrast to fossil fuel use.  However, the principal reason for this frequent assumption is ignorance of emissions of hydroelectric dams.  Reservoirs in the Brazilian Amazonia (Legal Amazon) contribute to greenhouse gas emissions from the region, although contributions from currently existing reservoirs are small relative to other anthropogenic sources such as deforestation for cattle pasture.  The four existing 'large' [> 10 megawatt (MW)] dams in the region are Balbina in the State of Amazonas (filled in 1987), Curuá-Una in Pará (1977), Samuel in Rondônia (1988) and Tucuruí in Pará (1984) (Figure 1).  In addition, there are small reservoirs at Boa Esperança in Maranhão (filled prior to 1989), Jatapu in Roraima (1994),  Paredão or Coarcy Nunes in Amapá (1975), and Pitinga in Amazonas (1982).


     The scale of hydroelectric development contemplated for Amazonia makes this a potentially significant source of emissions of greenhouse gases in the future.  Existing and planned dams are shown in Figure 2 and listed in Table I.  Brazil's financial difficulties have repeatedly forced the national power authority (ELETROBRÁS) and the power monopoly in northern Brazil (ELETRONORTE) to postpone dam building plans.  However, the overall scale of the plans, as distinguished from the expected date of completion of each dam, remains unchanged and consequently an important consideration for the future.


              (Figures 1 and 2 and Table I here)


     Little basis exists for calculating emissions from reservoirs.  However, existing information can be organized in such a way as to draw the best possible conclusions given the limitations of our knowledge.  The present paper assesses the amounts, types, and vertical distribution of biomass in areas flooded by reservoirs.  Rough inferences are drawn as to emissions resulting from decay of this biomass, but the certainty that can be attached to them is low due to poor understanding of the rates and pathways of decay for flooded biomass.  Hydroelectric emissions are the least well-understood of greenhouse gas emissions from Amazonian deforestation (hydroelectric flooding is considered to be a form of deforestation (cf. Fearnside, 1993).


     The ultimate contribution of hydroelectric flooding to atmospheric carbon is much easier to calculate than the impact of this flooding on the annual balance of emissions, which requires knowledge of the rates of decay and of the proportions of carbon emitted as carbon dioxide (CO2) and methane (CH4); the latter of these is much more effective than the former in greenhouse warming per unit of weight.  The ultimate contribution of dams to carbon emissions is the difference between the carbon stock in the forest prior to flooding and that in the reservoir once the forest has decayed and an equilibrium is reached.  Reservoirs in tropical forest areas have a much greater potential for greenhouse gas emissions than do reservoirs in low biomass landscapes that characterize most of the world's existing hydroelectric dams.  The amount of power generated also strongly affects the comparative impacts of hydroelectric versus fossil fuel generation.


     In Amazonia, dams are frequently worse than petroleum from the point of view of the ultimate total of greenhouse gas emissions.  The worst case is the Balbina Dam.  Junk & Nunes de Mello (1987) calculated that it would take 114 years of fossil fuel burning to equal the carbon emissions of the forest flooded in Balbina.  The calculation made by these authors considered Balbina's installed capacity of 250 megawatts (MW) and an area of 1650 km2.


     The installed capacity of a dam represents what would be generated if all turbines were to operate year-round.  Because the flow of the Uatumã River at Balbina is only sufficient to run all turbines for a fraction of the year, output at the dam averages 112 MW, and losses in transmission to Manaus reduce the average delivered to 109 MW (Brazil, ELETRONORTE/MONASA/ENGE-RIO, 1976).  The area of the reservoir used by Junk & Nunes de Mello (1987) was apparently chosen from preliminary estimates that foresaw an area considerably smaller than do more recent estimates.  Considering the average power delivered to Manaus and the 'official' reservoir area of 2360 km2 at the normal maximum operating level of 50-m elevation above mean sea level, Fearnside (1989) amended to 250 years Junk & Nunes de Mello's estimate of the time that petroleum would need to be burned to equal Balbina's ultimate emissions of carbon.


     While useful as an illustration, calculation of the ultimate contribution to carbon emissions tells us little about the contribution to the annual balance of emissions.  The United Nations Framework Convention on Climate Change (UN-FCCC), signed at the United Nations Conference on Environment and Development (UNCED) in Rio de Janeiro in June 1992 by 155 countries plus the European Union, stipulates that each nation must make an inventory of carbon stocks and fluxes of greenhouse gases.  This implies that the annual balance of greenhouse gas fluxes will be the criterion adopted for assigning responsibility among nations for global warming.  Because forest biomass in Amazonian reservoirs decays exceedingly slowly, the contribution to the annual balance is very different from the ultimate potential for emitting carbon.


     In addition to the timing of emissions, the amount that is emitted as methane rather than carbon dioxide strongly influences the global warming impact of reservoirs.  Per ton of carbon, methane is much more potent than carbon dioxide in provoking the greenhouse effect.  The average lifetime of methane in the atmosphere is much shorter than that of carbon dioxide: 10.5 years versus 120 years, given a constant composition atmosphere as assumed by the Intergovernmental Panel for Climate Change (IPCC) (Isaksen et al., 1992: 56).  Different methods of calculating global warming equivalence of the various greenhouse gases result in widely varying values for the importance of methane; those methods that consider indirect effects and those that give emphasis to impacts in the near future assign substantially more weight to methane.


     The IPCC's preferred method of calculation in its 1992 Supplementary Report considers a 100-year time horizon without discounting and only considers direct effects (Isaksen et al., 1992: 56).  This assigns each ton of methane gas a weight 11 times greater than each ton of carbon dioxide.  If indirect effects are considered using the same time horizon, as was done in the IPCC's 1990 report (Shine et al., 1990: 60), the weight given to methane relative to CO2 (the global warming potential) is 21.  Because much of methane's global warming impact is through indirect effects, the current state of disagreement over an appropriate global warming potential for methane is likely to be resolved in favor of higher values, thereby increasing the relative importance of impacts from Amazonian hydroelectric reservoirs.


     The Amazonian várzea (white water floodplain) has been identified as one of the world's major sources of atmospheric methane (Mooney et al., 1987).  The várzea occupies about 2% of the 5 X 106 km2 Legal Amazon, the same percentage that would be flooded if all of the 100,000 km2 of reservoirs planned for the region are created (Brazil, ELETROBRÁS, 1987: 150).  Virtually all planned hydroelectric dams are in the forested portion of the region, of which they would represent approximately 2.5-2.9%.  Were these reservoirs to contribute an output of methane per km2 on the same order as that produced by the várzea, they would together represent a significant contribution to the greenhouse effect.  This methane source would be a virtually permanent addition to greenhouse gas fluxes, rather than a one-time input like the CO2 releases from forest decay.




     In order to calculate emissions from hydroelectric reservoirs one must know the amounts of biomass present and the likely paths by which it will decay.  The trees left standing in the reservoir are obviously an important component.  The portion of the tree projecting out of the water can be assumed to decay through processes similar to those affecting trees in clearings for agriculture and ranching, with part of the biomass being ingested by termites (which emit a small amount of methane), and part decomposing through other forms of decay which, in the aerobic environment above the water, produce only CO2.  The biomass above the water level eventually falls into the water, thereby being transferred to the anoxic environments where decay is much slower--but also more likely to yield methane.  The leaves and vines fall off the trees very quickly, and the branches and trunks fall at a much slower rate.


     The reservoir can be divided into different zones, where aerobic and anoxic conditions will have different relative importance (Fig. 3).  Part of the reservoir is alternately exposed and flooded as water levels fluctuate between the minimum and maximum normal operating levels.  All biomass components in this zone, including litter and below-ground biomass, will be exposed to aerobic conditions at some time during the year.  The portion of standing trunks in the permanently flooded zone that are located between the minimum and maximum normal operating levels will also be exposed to aerobic conditions.


              (Figure 3 here)


     For underwater biomass, a part of the biomass near the surface will be in an environment that has some oxygen.  The anoxic zone does not correspond directly to the hypolimnion, and for purposes of decay is even closer to the water surface.  At Balbina, for example, although a very small amount of oxygen is measurable as deep as 5-m (G. V. Peña, personal communication, 1993), persons interested in commercial exploitation of flooded timber consider any wood below 1-m to be unaffected by decay (E. V. C. Monteiro de Paula, personal communication, 1993).


     Decay in the anoxic water zone is exceedingly slow, even for leaves that are generally believed to decay rapidly.  ELETRONORTE commissioned the Delft Hydraulics Laboratory in Delft, The Netherlands, to produce a model for water quality in Balbina, (Brazil, ELETRONORTE, 1987: 261).  The model, known as OXY-STRATIF, assumes that all leaves, litter and fine branches will decay within ten years.  However, over five years after filling Balbina, much of this material is still present (although no quantitative information is available).  The very slow nature of decay in the anoxic zone is illustrated by bundles of leaves that were placed at 5-m depth for studies of insects and other organisms in Balbina: after ten months the visual appearance of the leaves remained as green as the day when they were placed in the water.  No macroscopic organisms colonized the leaves, and not even the slime that typically forms on decaying material was present (G. V. Peña, personal communication, 1993).


     In shallow areas of the reservoirs, methane bubbling is easily observed.  At both Balbina and Tucuruí, bubbles can be seen everywhere, even when no pressure is exerted, as by stepping on the bottom.  The nature of the environment--devoid of oxygen, with relatively high temperatures and high levels of nutrients--makes it ideal for methane-producing decay processes.


     Emissions from decaying forest biomass will be supplemented from decay of organic matter that enters the reservoir from rivers and streams that feed it, from soil organic matter, and from macrophytes that grow in the reservoir.  The production of methane from these sources must be considered, although carbon dioxide need not be considered as a net addition (with the exception of any soil organic matter oxidized).  Data on methane production from these sources, which may be loosely described as production from the water itself, are not available for any Amazonian reservoir, the closest available surrogate being natural lakes in the várzea.


     Methane production from decomposition is not strictly identical to methane emission to the atmosphere, as some of the methane dissolved in the water column will instead by oxidized to CO2 before entering the atmosphere.  Because of the limited amount of mixing through the thermocline, high concentrations of methane in the water in the hypolimnion will only enter the atmosphere as the water passes through the turbines; at this point great quantities of methane can be expected to be released due to the abrupt reduction in pressure.  This occurs, for example, in water passing through turbines in reservoirs in Canada (M. Lucotte, personal communication, 1993).  However, not all methane will be exposed to the atmosphere in the reservoir and at the turbines, and some will occur downstream of the dam.  The dissolved concentration of CH4 in the water released from the turbines or over the spillway is an important measurement that needs to be made, but not all CH4 present in these water flows can be considered as methane emissions--some CH4 may be oxidized to CO2 in the river (Rosa, 1992).


     Methane-rich water from the hypolimnion is occasionally released in reservoirs in central and western Amazonia (Balbina and Samuel) when a cold wave (friagem) reduces surface temperature and causes dissolution of the thermocline (the barrier created by thermal stratification of the water column that prevents vertical mixing), resulting in a turnover in the water.  Many fish die during these events, for example, in April 1993 at Balbina.  These events are more frequent in the western part of Amazonia, and are not a factor in the eastern part of the region, where most planned reservoirs would be located.





Parameters for Emissions Calculations


     Estimating emissions from reservoirs first requires estimates of the area of forest flooded in each impoundment.  The riverbed area within each reservoir must be estimated and subtracted from the water surface area.  Riverbed areas are calculated in Table II from estimates of the length and average width of the rivers.  The surface areas of the reservoirs were measured from LANDSAT-TM 1:250,000 scale images (Fearnside et al., nd).  Previously deforested areas and riverbed areas are deducted when forest loss is calculated (Table III).


          (Tables II and III here)


     Vertical distribution of biomass, and classification into trunks, leaves and other components, is important for determining what portion of the biomass will decay above the water and what will decay underwater in the permanently flooded and seasonally flooded zones.  The only existing biomass study that assigns the biomass to vertical strata is that of Klinge & Rodrigues (1973), done at INPA's Reserva Egler, 64 km east of Manaus.  The approximate dry weights are given in Table IV.  The forest at the Reserva Egler has a maximum height of 38.1 m, which must be assumed to apply to the forests in the four existing large reservoirs.


                   (Table IV here)


     Biomass estimates specific for each reservoir are available for all except Curuá-Una (Table V).  Fortunately, the forest flooded at Curuá-Una has an area of only 65 km2, representing only 1.3% of the total 4824 km2 of forest flooded by 1990 in the region (Table V).  Biomass for Curuá-Una is assumed to be the average estimated for all areas deforested in the 1989-1990 period (Fearnside, nd-a).  Based on the proportion in vertical strata (Table IV), the water depths at minimum and maximum operating levels (Table V), and the areas in each zone (Table V), the biomass is calculated for each reservoir in the following categories: above-water zone wood, surface water zone wood, anoxic water zone leaves and other non-wood (all assumed to fall to the bottom of the reservoir), and below-ground wood (Table V).  The amounts of wood removed by logging prior to filling and after filling (through 1990) are also roughly estimated (Table V).  After these calculations, the progression of biomass values is calculated for each year for each reservoir, zone and biomass component.  This is done using rates of decay in each zone and rates of biomass falling from the above-water to the below-water zones; these rates and other parameters for emission calculations are given in Table VI.  The resulting biomass distributions in 1990 are given in Table VII.


              (Tables V, VI and VII here)


     The decay rates for underwater biomass are known to be exceedingly slow, but actual measurements are completely lacking.  The average lifetimes assumed here are: 50 years for wood in the surface water zone, 200 years for leaves in the anoxic water zone, 500 years for wood in the anoxic water zone, 500 years for below-ground biomass in the permanently flooded zone, and 50 years for below-ground biomass in the seasonally flooded zone (Table VI).


     Methane is also produced from ongoing biological processes that are independent of the stock of original forest biomass.  These include decomposition of organic matter entering the reservoir from the river, and from decay of macrophytes that grow on a portion of the reservoir surface.  These rates are assumed to be equal to those that have been found for open water and for macrophyte beds in studies of natural várzea lakes (Table VIII).  Only methane is considered from these sources, as the carbon dioxide that they also generate is recycled when the macrophytes and other plants regrow.  Chemical characteristics of water in the Balbina reservoir, for example, (located on a black water river) differ in a number of ways from white water várzea lakes, making clear the importance of direct measurements of methane production in reservoirs.


              (Table VIII here)


Simulation of Emissions over Time


     The greenhouse gas fluxes by process in 1990 are presented in Table IX.  While information on emissions from all sources at a given time, such as 1990, is needed as a baseline for assessing changes in greenhouse gas emissions, the evolution of emissions over time is important for evaluating potential impacts of planned projects.  The timing of emissions is also very important in any system of emissions evaluation that gives differential weight to short-term and long-term impacts, as by discounting.


              (Table IX here)


     The emissions of CO2 and CH4 from Balbina are simulated for 50 years after closing in Figure 4.  Methane emissions are fairly constant over the entire period, but carbon dioxide emissions are concentrated in a tremendous pulse in the first decade after closing.  As of 1994, approximately half of the total CO2 emission from Balbina had taken place, according to the simulation reported here.


              (Figure 4 here)


     The global warming impact of emissions can be converted to CO2-equivalent carbon using global warming potentials adopted by the Intergovernmental Panel on Climate Change (IPCC) for direct effects only, over a 100-year time horizon without discounting (Isaksen et al., 1992).  This is an underestimate of the true impact of reservoirs, as at least half of the global warming provoked by methane is through indirect rather than direct effects.  In Figure 5 the CO2-equivalent carbon of the emissions is simulated for 50 years for the four existing large reservoirs in Brazilian Amazonia.


              (Figure 5 here)


Comparison with Fossil Fuel Emissions


     Comparisons of emissions from hydroelectric projects with the avoided emissions from generating the same amount of power from fossil fuels are important because of the frequency with which hydroelectric projects have been promoted as offering a 'clean' alternative to thermoelectric generation.  The examples of Balbina and Tucuruí are given in Table X.  The mix of diesel and fuel oil burned at thermoelectric plants in Manaus (the city served by Balbina) is assumed to also apply to avoided emissions from Tucuruí.  Emissions factors for these fuels applying to thermoelectric plants in Canada are assumed to apply to Brazil (probably an optimistic assumption).  Power from Balbina substitutes for approximately 1.3 million t of CO2-equivalent carbon (Table X, part F), far less than the emission of 6.9 million t from decaying biomass in the reservoir (Table XI).  Table XI also compares 1990 emissions of Balbina and Tucuruí with emissions from other sources.


     These Amazonian reservoirs compare poorly with two reservoirs in Canada that have been identified as sources of greenhouse gases (Rudd et al., 1993).  The comparative impact of Balbina and Tucuruí is even worse than these emissions estimates indicate because the Canadian study used a global warming potential (GWP) for calculating the CO2 equivalent of methane, which was over five times higher than the IPCC GWP used in the present paper.  By converting emissions to CO2 carbon equivalents using the same IPCC GWPs used in the current calculation, Rosa and Schaeffer (1994) have shown that the Canadian reservoirs studied by Rudd et al. (1993) have less global warming impact than would generating the same amount of energy from fossil fuel.


              (Tables X and XI here)


     In Figure 6 the emissions of Balbina are simulated over 50 years, in comparison to the emissions that would be produced by supplying the same energy to Manaus from fossil fuels.  The tremendous disadvantage of hydroelectric generation in the initial years is evident.  In the case of Balbina (which has a very large area per unit of electricity generated), even after 50 years (and probably for an indefinite period), the emissions will continue to exceed those from fossil fuels.  These results call into question the image of Amazonian hydroelectric dams as helping to reduce global warming.


              (Figure 6 here)




     Hydroelectric reservoirs in Brazilian Amazonia emitted very approximately 0.26 million tons of CH4 gas and 38 million tons of CO2 gas in 1990.  Of the CH4, approximately 0.11 million tons were emitted from open water, 0.04 from macrophyte beds, < 0.01 from above-water decay of forest biomass, and 0.11 from underwater decay of forest biomass.  The underwater decay rates are the least reliable of these estimates.  No net carbon dioxide emissions come from open water or macrophytes.  Above-water decay contributed approximately 99% of the estimated 38 million tons of CO2 emitted.  Using 1992 IPCC global warming potentials, these emissions are equivalent to approximately 11 million tons of CO2-equivalent carbon.


     The total area of planned reservoirs in Brazilian Amazonia is approximately 20 times the area present in 1990, implying a potential annual emission rate of about 5.2 million tons of methane.  While the methane emission represents an essentially permanent addition to gas fluxes, the carbon dioxide is released in a tremendous pulse during the first decade after closure.  These CO2 emissions greatly exceed the avoided emissions from fossil fuel combustion.




     I thank Summer V. Wilson, Bruce R. Forsberg and Gladys V. Peña for comments on the manuscript.



     Existing hydroelectric dams in Brazilian Amazonia emitted about 0.26 million tons of methane and 38 million tons of carbon dioxide in 1990.  The methane emissions represent an essentially permanent addition to gas fluxes from the region, rather than a one-time release.  The total area of reservoirs planned in the region is about 20 times the area existing in 1990, implying a potential annual methane release of about 5.2 million tons.  About 40% of this estimated release is from underwater decay of forest biomass, which is the most uncertain of the components in the calculation.  Methane is also released in reservoirs from open water, macrophyte beds, and above-water decay of forest biomass.


     Hydroelectric dams release a large pulse of carbon dioxide from above-water decay of trees left standing in the reservoirs, especially during the first decade after closing.  This elevates the global warming impact of the dams to levels much higher than would occur by generating the same power from fossil fuels.  In 1990, the impoundment behind the Balbina Dam (closed in 1987) had over 20 times more impact on global warming than would generating the same power from fossil fuels, while the Tucuruí Dam (closed in 1984) had 0.4 times the impact of fossil fuels.  Because of the large area flooded per unit of electricity generated at Balbina, greenhouse gas emissions are expected to exceed avoided fossil fuel emissions indefinitely.



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MARTINELLI, L. A., VICTORIA, R. L., MOREIRA, M. Z., ARRUDA JR., G., BROWN, I. F., FERREIRA, C. A. C., COELHO, L. F., LIMA, R. P. & THOMAS, W. W. (1988). Implantação de parcelas para monitoreamento de dinâmica florestal na área de proteção ambiental, UHE Samuel, Rondônia: Relatório preliminar. Centro de Energia Nuclear na Agricultura (CENA), Piracicaba, São Paulo, Brazil. (Unpublished report: 72 pp).


MARTIUS, C., FEARNSIDE, P. M., WASSMANN, R. & BANDEIRA, A. G. (nd). Deforestation and methane release from termites in Amazonia. (In preparation).


MARTIUS, C., WASSMANN, R., THEIN, U., BANDEIRA, A.G.,  RENNENBERG, H., JUNK, W. & SEILER, W. (1993). Methane emission from wood-feeding termites in Amazonia. Chemosphere 26 (1-4), pp. 623-632.


MOONEY, H. A., VITOUSEK, P. M. & MATSON, P. A. (1987). Exchange of materials between terrestrial ecosystems and the atmosphere. Science, 238, pp. 926-32.


PAIVA, M. P. (1977). The Environmental Impact of Man‑Made Lakes in the Amazonian Region of Brazil. Centrais Elétricas Brasileiras, S.A. (ELETROBRÁS), Diretoria de Coordenação, Rio de Janeiro, Brazil: 69 pp.


REVILLA CARDENAS, J. D. (1986). Estudos de ecologia e controle ambiental na região do reservatório da UHE de Samuel. Convênio: ELN/MCT/CNPQ/INPA de 01.07.82. Relatório Setorial, Segmento: Estimativa da Fitomassa. Período julho-dezembro 1986. Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Amazonas, Brazil: 194 pp.


REVILLA CARDENAS, J. D. (1987). Relatório: Levantamento e Análise da Fitomassa da UHE de Kararaô, Rio Xingú. Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Amazonas, Brazil: 181 pp., illustr.


REVILLA CARDENAS, J. D. (1988). Relatório: Levantamento e Análise da Fitomassa da UHE de Babaquara, Rio Xingú. Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Amazonas, Brazil: 277 pp., illustr.


REVILLA CARDENAS, J. D. & DO AMARAL, I. L. (1986). Estudos de Ecologia e Controle Ambiental na Região do Reservatório da UHE de Samuel: Convênio ELN/CNPq/INPA, de 01.07.82. Relatório Setorial, Segmento Minhocucus, Período janeiro/junho 1986. Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Amazonas, Brazil: 5 pp.


REVILLA CARDENAS, J. D., KAHN, F. L. & GUILLAMET, J. L. (1982). Estimativa da fitomassa do reservatório da UHE de Tucuruí. Pp. 1-11 in Projeto Tucuruí, Relatório Semestral, Período janeiro/junho 1982, Vol. 2: Limnologia, Macrófitas, Fitomassa, Degradação da Fitomassa, Doenças Endêmicas, Solos. Brazil, Centrais Elétricas do Norte do Brasil, S.A. (ELETRONORTE) & Instituto Nacional de Pesquisas da Amazônia (INPA). INPA, Manaus, Amazonas, Brazil: 32 pp.


ROBERTSON, B.A. (1980). Composição, Abundância e Distribuição de Cladocera (Crustacea) na Região de Água Livre da Represa de Curuá‑Una, Pará. Masters Thesis, Fundação Universidade do Amazonas (FUA) & Instituto Nacional de Pesquisas da Amazônia (INPA). INPA, Manaus, Amazonas, Brazil: 105 pp.


ROSA, L.P. (1992). Untitled presentation at the INPE/OECD Workshop on Inventories of Net Anthropogenic Emissions of Greenhouse Gases, São José dos Campos, São Paulo, Brazil, 9-10 March 1992.


ROSA, L.P. & SCHAEFFER, R. (1994). Greenhouse gas emissions from hydroelectric reservoirs.  Ambio 23(2), pp. 164-165.


RUDD, J. W. M., HARRIS, R., KELLY, C. A. & HECKY, R. E. (1993). Are hydroelectric reservoirs significant sources of greenhouse gases? Ambio, 22 (4), pp. 246-8, 1 fig.


SEVA, O. (1990). Works on the Great Bend of the Xingu--A Historic Trauma? Pp. 19-35 in Hydroelectric Dams on Brazil's Xingu River and Indigenous Peoples. (Ed. L. A. de O. Santos & L. M. M. de Andrade). Cultural Survival Report 30. Cultural Survival, Cambridge, Massachusetts, USA: 192 pp., illustr.


SHINE, K. P., DERWENT, R. G., WUEBBLES, D. J. & MORCRETTE, J-J. (1990). Radiative forcing of climate. Pp. 41-68 in Climate Change: The IPCC Scientific Assessment. (Ed. J. T. Houghton, G. J. Jenkins & J. J. Ephraums). Cambridge University Press, Cambridge, UK: 365 pp.


WASSMANN, R. & THEIN, U. G. (1989). Spatial and seasonal variation of methane emission from an Amazon floodplain lake.  Paper presented at the Workshop on 'Cycling of Reduced Gases in the Hydrosphere,' SIL Congress, Munich, Germany, 17 August 1989. (Manuscript, 8 pp.)



Figure 1:Brazil's Legal Amazon region with the four existing large dams.


Figure 2:Seventy-nine planned and existing dams in Brazilian Amazonia. Only dams in the ELETRONORTE system are included, not those planed by State Governments or private firms.  Redrawn from Seva (1990), who based the map on Brazil, ELETROBRÁS (1986) and Brazil, ELETRONORTE (1985c).


Figure 3:Zones for distribution of biomass in reservoirs.


Figure 4:Balbina: CO2 and CH4 emissions (million t of gas).


Figure 5:Hydroelectric greenhouse gas emissions (CO2-equivalent carbon).


Figure 6:Balbina: Greenhouse gas emissions (CO2-equivalent carbon).




Dam    Dam name                River       Projected

No.                            Valley      Installed




1    São Gabriel             Uaupés/Negro  2,000


2.   Santa Isabel            Uaupés/Negro  2,000


3.   Caracaraí-Mucajaí       Branco        1,000


4.   Maracá                  Uraricoera      500


5.   Surumu                  Cotingo         100


6.   Bacarão                 Cotingo         200


7.   Santo Antônio           Cotingo         200


8.   Endimari                Ituxi           200


9.   Madeira/Caripiana       Mamoré/Madeira 3,800


10.  Samuel                  Jamarí          200


11.  Tabajara-JP-3           Ji-Paraná       400


12.  Jaru-JP-16              Ji-Paraná       300


13.  Ji-Paraná-JP-28         Ji-Paraná       100


14.  Preto RV-6              Roosevelt       300


15.  Muiraquitã RV-27        Roosevelt       200


16.  Roosevelt RV-38         Roosevelt       100


17.  Vila do Carmo AN-26     Aripuanã        700


18.  Jacaretinga AN-18       Aripuanã        200


19.  Aripuanã AN-26          Aripuanã        300


20.  Umiris SR-6             Sucunduri       100


21.  Itaituba                Tapajós       13,000


22.  Barra São Manuel        Tapajós       6,000


23.  Santo Augusto           Juruena       2,000


24.  Barra do Madeira        Juruena        1,000


25.  Barra do Apiacás        Teles Pires   2,000


26.  Talama (Novo Horizonte) Teles Pires   1,000


27.  Curuá-Una               Curuá-Una       100


28.  Belo Monte (Cararaô)    Xingu         8,400


29.  Babaquara               Xingu         6,300


30.  Ipixuna                 Xingu         2,300


31.  Kokraimoro              Xingu         1,900


32.  Jarina                  Xingu           600


33.  Iriri                   Iriri           900


34.  Balbina                 Uatumã          300


35.  Fumaça                  Uatumã          100


36.  Onça                    Jatapu          300


37.  Katuema                 Jatapu          300


38.  Nhamundá/Mapuera        Nhamundá        200


39.  Cachoeira Porteira      Trombetas     1,400


40.  Tajá                    Trombetas       300


41.  Maria José              Trombetas       200


42.  Treze Quedas            Trombetas       200


43.  Carona                  (Trombetas)     300


44.  Carapanã                Erepecuru       600


45.  Mel                     Erepecuru       500


46.  Armazém                 Erepecuru       400


47.  Paciência               Erepecuru       300


48.  Curuá                   Curuá           100


49.  Maecuru                 Maecuru         100


50.  Paru III                Paru            200


51.  Paru II                 Paru            200


52.  Paru I                  Paru            100


53.  Jari IV                 Jari             300


54.  Jari III                Jari            500


55.  Jari II                 Jari            200


56.  Jari I                  Jari            100


57.  F. Gomes                Araguari        100


58.  Paredão                 Araguari        200


59.  Caldeirão               Araguari        200


60.  Arrependido             Araguari        200


61.  Santo Antônio           Araguari        100


62.  Tucuruí                 Tocantins     6,600


63.  Marabá                  Tocantins     3,900


64.  Santo Antônio           Tocantins     1,400


65.  Carolina                Tocantins     1,200


66.  Lajeado                 Tocantins       800


67.  Ipueiras                Tocantins       500


68.  São Félix               Tocantins     1,200


69.  Sono II                 Sono            200


70.  Sono I                  Sono            100


71.  Balsas I                Balsas          100


72.  Itacaiúnas II           Itacaiúnas      200


73.  Itacaiúnas I            Itacaiúnas      100


74.  Santa Isabel            Araguaia      2,200


75.  Barra do Caiapó         Araguaia        200


76.  Torixoréu               Araguaia        200


77.  Barra do Peixe          Araguaia        300


78.  Couto de Magalhães      Araguaia        200


79.  Noidori                 Mortes          100


                             Total:        85,900


a  Based on list derived from ELETRONORTE sources by Seva (1990: 26-27).   Dam numbers correspond to numbering in Figure 2.




Reservoir River         Length    Average   Riverbed  Source

                        in        width     area

                        reservoir (m)b      (km2)



Balbina    Uatumã         210        139         29

           Pitinga        100         99         10

                               Balbina total:   39                  c


Curuá‑     Curuá-Una         80       69          6

Una        Muju              40       35          1

           Mojui dos Campos  20       15          0

                             Curuá-Una total:    7                  d


Samuel     Jamari            255     116         29                  e


Tucuruí    Tocantins         170    1891        321                  f



TOTAL                                          397


a  Lengths of Balbina and Tucuruí from Juras (1988).

b  River widths measured at approximately 5-km intervals using the following maps or images indicated under Source at the following scales: Balbina: 1:100,000; Samuel: 1:40,000; Tucuruí: 1:250,000.  Widths of Curuá‑Una and tributaries are based on 6 direct measurements by Robertson (1980).

c  Brazil, ELETRONORTE, 1985a.

d  Robertson, 1980.

e  Brazil, ELETRONORTE, nd-a.

f  Brazil, Projeto RADAMBRASIL, 1981.




Dam              State             Dates of filling







1                2                 3



Balbina          Amazonas          1 Oct. 1987 ‑ 15 July 1989


Curuá‑Una        Pará              Jan. 1977 ‑ May 1977


Samuel           Rondônia          Oct. 1988‑ July 1989


Tucuruí          Pará              6 Sept. 1984 ‑ 30 Mar. 1985





a  Balbina riverbed area estimated from ELETRONORTE (1985a) 1:100,000 scale map; Curuá‑Una riverbed area calculated from map and river width measurements of Robertson (1980); Samuel riverbed area estimated from length; Tucuruí riverbed area from Brazil, Projeto RADAMBRASIL, 1981.


b  Official areas for comparison only.  Sources: Balbina: Brazil, ELETRONORTE, 1987; Curuá‑Una: Robertson, 1980: 9; Samuel: Revilla Cardenas, 1986; Tucuruí: Brazil, ELETRONORTE, nd [1987]: 24‑25.


c  Three small dams outside the ELETRONORTE system are: Pitinga (filled in 1982 and raised in 1993; 1989 LANDSAT-measured area = 62 km2) near Balbina in Amazonas, Boa Esperança (filled prior to 1989; LANDSAT-measured area = 24 km2) in Maranhão, and Jatapu (filled in 1994; official area = 45 km2) in Roraima.  All of the area flooded by these dams represents forest loss.  The two dams filled prior to 1989 would bring the LANDSAT-measured total area to 6017 km2 and the estimated forest loss to 5620 km2.


d  LANDSAT‑measured water surface includes riverbed and previous deforestation.  To avoid double counting, estimated forest loss does not include previous deforestation: Column 8 = Column 7 ‑ Column 5. (Source: Fearnside et al., nd).


e  Balbina 1988‑1989 rate is an overestimate due to lack of a 1988 image (230/61) covering approximately 10‑20% of the reservoir area nearest the dam.  If unimaged area represented 10% of the measured 1988 area, then Balbina loss rate in 1988‑1989 was 348 km2 yr-1 (a decrease of 34%); if 20%, then loss rate was 162 km2 yr-1 (a 70% decrease).


f  Area measured by Robertson (1980) from Centrais Elétricas do Para (CELPA) map.  Paiva (1977) gives the official area as 86 km2.


g  Area cleared by ELETRONORTE only (Brazil, ELETRONORTE, nd[1987].

[Table III part 2]



Previous    River‑   Official   LANDSAT‑   Estimated   1988‑1989

defores‑    bed      area       measured   forest      forest

tation in   area     of         water      loss        loss

flooded     (km2)a    water      surface    (km2)d      rate

area                surface    area in               (km2 yr-1)

(km2)                (km2)b     1989 (km2)c


  4          5          6          7          8           9



   55         39      2,360      3,147     3,108         693e


    0          7        102         72        65f          0


   91         29        645        465       436         436


  400g       321      2,430      2,247     1,926           0



  546        397      5,537      5,931     5,534       1,129




Stratum   Mean height     Approximate dry weight biomass (t ha-1)

           (m)b            ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑---------------

-----‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑     Leaves    Stems    Branches

       Midpoint  Range



A       29.6     5.9         1.1      66.1       23.1


B       21.1     4.4         3.4     127.9       58.5


C1      11.5     3.1         1.9      22.5       12.4


C2       4.8     1.2         1.0       4.8        1.7


D        2.4     0.7         1.0       0.9        0.3


E        0.6     0.5         0.3       0.4        0.0


                            8.6     222.5       96.0


Vines                      21.9


Epiphytes                   0.1


Totals for non-wood,       30.6

wood and all live

above-ground biomass


Fine litterc               10.9


Downed dead woodd


Standing dead woodd


Totals for non-wood,       41.5

wood and all

above-ground biomass



a  Data for fresh weights from Klinge & Rodrigues (1973), converted to dry weights using a constant correction factor of 0.475 derived for these data by the same authors (Klinge et al., 1975).


b  Maximum height of the stand was 38.1 m.  The stand is located 64 km east of Manaus at INPA's Reserva Egler.


c  Average of 5 measurements at hydroelectric dam sites at Samuel, Belo Monte and Babaquara (Revilla Cardenas, 1987, 1988; Martinelli et al., 1988).


d  Klinge, 1973: 179.

[Table IV, part 2]




                 Percent of total above-ground biomass

‑‑‑‑‑‑‑‑‑‑‑‑‑‑-- ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑----------

Total   Total     Leaves  Stems   Branches      Total    Total

live    live                                   live     live

wood    biomass                                wood      biomass

‑‑‑‑‑‑‑‑‑‑‑‑‑‑-- ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-------------

89.3    90.3      0.28    17.15    6.00         23.14     23.43


186.4   189.8      0.87    33.17   15.16         48.33     49.21


34.9    36.7      0.48     5.83    3.21          9.04      9.52


  6.5     7.4      0.25     1.23    0.44          1.68      1.92


  1.2     2.2      0.27     0.22    0.09          0.31      0.58


  0.4     0.7      0.07     0.10    0.00          0.10      0.17


318.5   327.1      2.23    57.69   24.91         82.60     84.83






318.5   349.1      7.92                         82.60     90.52






18.02                                           4.67


7.6                                             1.97


344.2   385.6     10.76                         89.24    100.00







Dam       Year     Water      Forest     Forest

          filled   surface    flooded    flooded

                  area at    at oper-   at

                  operating  ating      minimum

                  level      level      level

                  (ha)       (ha)       (ha)


Balbina    1987   314,700    310,840    206,829


Curuá-Una  1977     7,200      6,480      5,500


Samuel     1988    46,500     43,551     30,901


Tucuruí    1984   224,700    192,553    106,787


TOTALS            593,100    553,424    350,017



a  Brazil, ELETRONORTE, 1987; forest flooded at minimum level is adjusted by ratio of LANDSAT‑measured area to official area at the operating level.


b  Paiva, 1977: 17 (value for average depth at maximum operating level).


c  Revilla Cardenas & do Amaral, 1986; forest area flooded at minimum water level taken as proportional to water volumes at these two levels from Brazil, ELETRONORTE, nd [1992]b: 5.


d  Revilla Cardenas et al., 1982.


e  Uses 58.0 m above mean sea level as minimum normal operating level (Brazil, ELETRONORTE, nd [ca. 1983].  A minimum operating level of 51.6 m (Brazil, ELETRONORTE, nd‑b: p. 2‑1; Brazil ELETRONORTE, nd [1992]a) implies drawdown depth of only 3.3 m.  Forest area flooded at minimum water level is taken as proportional to water volumes at these two levels from Brazil, ELETRONORTE, nd [ca. 1983], p. 6).


f  Brazil, ELETRONORTE, nd [1992]a.


g  Brazil, ELETRONORTE, nd [1992]b.

[Table V, part 2]




Approx-   Above‑   Biomass   Average    Depth

imate     ground   source    depth at   source

total     biomass           minimum

biomass   (t ha-1)           level

(t ha-1)                     (m)


441       336      a, pp.      6.2     a, p. 14


428       327      Fearnside,  6.2     b


557       425      c, p. 4     5.3     b


517       394      d, p. 90    9.7     e




[Table V, part 3]



Dam     Initial biomass by zone (t dry matter ha-1)


        Above-   Surface Anoxic     Anoxic    Below-       Total

        water    water   water      water     ground

        wood     wood    wood       leaves    wood

                        and other



Balbina   264.69  4.55    31.44      35.70    104.74     441.12


Curuá-Una 257.11  4.42    30.54      34.68    101.74     428.50


Samuel    339.59  5.74    34.56      45.11    132.34     557.34


Tucuruí   291.40  5.33    55.47      41.82    122.69     516.71


[Table V, part 4]



Dam   Logging removals   Fraction  Fraction    Years of post-

      of biomass         of above- of original filling logging

      (t ha-1of           ground    anoxic      activity     

      reservoir area)    wood      zone       ‑‑‑---------------

      ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑--  removed wood        Begin  End

        Before   After   before  removed

        filling  filling filling after


‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑Balbina      0               0         0.5       1993    2000


Curuá-Una   0        0    0          0


Samuel                    0.2        0


Tucuruí                   0.01       0.5      1988    2000


[Table V, part 5]



Area cleared prior           Draw-  Draw-

to filling (ha)              down   down

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ depth  depth

Season-   Perma-    Total     (m)    source

ally      nently

flooded   flooded

zone      zone


    0     5,000     5,000       4


                               4.5  guess


                               7    f, p. 5


2,000    8,000    10,000      14    g, p. 5





Parameter                                              Value



Above-ground fraction                                    0.773

Average depth of surface water zone                      1

Leaf decay rate in seasonally inundated zone            -0.5

Above-water decay rate (0-4 yrs)                        -0.1691

Above-water decay rate (5-7 yrs)                        -0.1841

Above-water decay rate (8-10 yrs)                       -0.0848

Above-water decay rate (>10 yrs)                        -0.0987

Fraction of above-water decay via termites               0.0844

Wood decay rate in surface water zone                   -0.0139

Leaf decay rate in anoxic water zone                    -0.0035

Wood decay rate in anoxic water zone                    -0.0014

Below-ground decay rate in permanently flooded zone     -0.0014

Below-ground decay rate in seasonally flooded zone      -0.0139

Fraction of C released as CH4 in termite decay           0.002

Fraction of C released as CH4 in termite decay (high     0.0079

    trace gas scenario)

Fraction of C released as CH4 in surface water zone decay 0


Fraction of C released as CH4 in anoxic water zone decay 1

Fraction of C released as CH4 in below-ground decay      1

Fraction of water covered by macrophytes                 0.1

Methane release from macrophyte beds                   174.67

Methane release from open water                         53.93

Carbon content of wood                                   0.50

Carbon content of leaves and fine litter                 0.45

Carbon content of vines and epiphytes                    0.45

Rate of wood fall from above-water zone                  0.1155

Fraction of CH4 oxidized in water                        0

Leaf aerobic decay, first year                           0.025




Leaf aerobic decay, after first year                     0.0085





Biomass of components in unlogged original forests


Average total biomass of forest                        428

Average water depth at minimum level                    10

Initial biomass present: leaves                       7.30

Initial biomass present: fine litter                  8.75

Initial biomass present: vines and epiphytes         18.64

Initial biomass present: wood above water           240.33

Initial biomass present: wood in surface zone         4.42

Initial biomass present: wood in anoxic zone         47.32

Initial biomass present: below-ground               101.74

[Table VI, part 2]



Units         Source

‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑--


             Fearnside, nd-a

meter        Assumption, based on commercial timber spoilage      

Fraction yr-1 Assumption

Fraction yr-1Assumed same as felled forest (Fearnside, nd-b)       

Fraction yr-1Assumed same as felled forest (Fearnside, nd-b)       

Fraction yr-1 Assumed same as felled forest (Fearnside, nd-b)      

Fraction yr-1 Assumed same as felled forest (Fearnside, nd-b)      

Fraction     Assumed same as felled forest (Martius et al., nd)        

Fraction yr-1 Assumption: average lifetime = 50 years

Fraction yr-1 Assumption: average lifetime = 200 years

Fraction yr-1 Assumption: average lifetime = 500 years

Fraction yr-1 Assumption: average lifetime = 500 years

Fraction yr-1 Assumption: average lifetime = 50 years

             Calculated from measurement by Martius et al., 1993

             for Nasutitermes macrocephalus (a várzea species)

             Calculated from measurement by Martius et al., 1993

             for Nasutitermes macrocephalus (a várzea species)





µg m-2 day-1   Table VIII

µg m-2 day-1   Table VIII

             Fearnside et al., 1993



Fraction yr-1 Assumption: average lifetime = 6 years


Fraction of  Calculated from Brazil, ELETRONORTE, 1987: 261

original     (OXY-STRATIF model parameter for Balbina).  Value

leaf biomass divided by 10 (as a guess at the exaggeration in

lost annually OXY-STRATIF)

Fraction of  Calculated from Brazil, ELETRONORTE, 1987: 261.

original     Value divided by 10 (as a guess at the exaggeration

leaf biomass  in OXY-STRATIF)

lost annually

‑‑‑‑‑‑‑‑‑‑‑‑ -‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑---



t ha-1

meters       Assumption


t ha-1        Calculated from total biomass and Table IV.

t ha-1        Calculated from total biomass and Table IV.

t ha-1        Calculated from total biomass and Table IV.

t ha-1        Calculated from total biomass and Table IV.

t ha-1        Calculated from total biomass and Table IV.

t ha-1        Calculated from total biomass and Table IV.

t ha-1        Calculated from total biomass and Table IV.


(106 t of biomass)



PERMANENTLY FLOODED ZONE (at minimum operating water level)


                    Above-   Surface  Anoxic     Anoxic

                    water    water    water      water

                    wood     wood     wood       leaves

                                                and other



Balbina             28.85    0.89     20.50      7.09


Curuá-Una           0.04     0.02     0.84       0.15


Samuel              6.17     0.11     2.17       1.07


Tucuruí             6.00     0.41     13.01      3.52

‑‑‑‑‑‑‑‑‑‑          ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑--------‑‑‑‑‑‑‑‑‑------

TOTALS              41.06    1.44     36.52      11.84

‑‑‑‑‑‑‑‑‑‑          ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑--------------


SEASONALLY FLOODED ZONE (at maximum normal operating water level)


                   Above-    Leaves    Under-    Below-

                   water     and       water     ground

                   wood      other     wood      wood


‑‑‑‑‑‑‑‑‑‑         ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑--------‑‑‑‑‑‑‑‑‑-------

Balbina             19.61      2.02     2.41      10.11


Curuá-Una            0.04      0.00     0.01       0.08


Samuel               2.77      0.42     0.46       1.57


Tucuruí              7.47      0.78     6.35       9.54

-----------        -------‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-----

TOTALS              29.88      3.22     9.23      21.30

‑-‑‑‑‑‑----        -------‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑------------

[Table VII, part 2]






Below-    Total





  27.19   84.52


   0.51    1.56


   3.04   12.57


  10.46   33.41


  41.20  132.05






















Habitat                   Methane flux

                          (mg CH4 m-2 day-1

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

                          Low         High        Eight

                          water       water       lakes

                          CAMREX      CAMREX      near

                          cruise 11   cruise 9    Manaus


                          (1)         (1)         (1)

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

Lakes, open water         40          88          58

                        (±12)       (±30)       (±16)


Lakes, macrophyte beds   131         390         251

                        (±47)      (±109)       (±58)


Lakes, flooded forest      7.1        74          55

                         (±3.4)     (±19)       (±13)

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-   ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑


(1) Devol et al., 1990.

(2) Wassmann & Thein, 1989.

(3) Bartlett et al., 1990.

(4) For comparison, Aselmann & Crutzen (1990: 446) estimate the average for lakes of the world to be 43 mg CH4 m-2 day-1.

[Table VIII, part 2]





Lago da Machantaria       NASA/   Value

(near Manaus)             ABLE    assumed for

‑‑‑‑‑‑‑‑‑‑‑‑‑‑----------- rising  Amazonian

Low       Rising  High     water   reservoirs

water     water   water

(2)       (2)     (2)      (3)     (4)


50-100    5-50    5-25     74      53.9



dry       0-50    0-100    201     174.7



dry       0‑200   0‑200    126








            Area     Above‑water decay           Underwater decay

            of       ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑----------

            perma-   Termites         Other     Wood in surface

            nently   ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑          water zone

            inunda-  CH4       CO2     CO2       ‑‑‑‑‑‑‑‑‑-------

            ted zone (106      (106    (106      CH4

            (ha)     t gas)    t gas)  t gas)    (106

                                               t gas)

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑------------

Balbina    206,829    0.00     0.28      8.61      0.00


Curuá-Una    5,500    0.00     0.00      0.01      0.00


Samuel      30,901    0.00     0.06      1.84      0.00


Tucuruí    106,787    0.00     0.06      1.98      0.00

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑----------

TOTALS     350,017    0.00     0.41     12.43      0.00

-------------------- ----------------------------- --------------

[Table IX, part 2]






                                             Below-ground decay

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑--

        Wood in anoxic       Leaves and other

        water zone           non-wood biomass

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-- CH4      CO2

CO2      CH4      CO2         CH4      CO2        (106     (106

(106     (106     (106        (106     (106       t gas)    t gas)

t gas)   t gas)   t gas)      t gas)   t gas)

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑--

0.02     0.02     0.00        0.01     0.10       0.03     0.00


0.00     0.00     0.00        0.00     0.00       0.00     0.00


0.00     0.00     0.00        0.00     0.05       0.00     0.00


0.01     0.01     0.00        0.01     0.05       0.01     0.00

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑‑----

0.04     0.03     0.00        0.02     0.20       0.04     0.00

---------------------------------------------- ------------------




[Table IX, part 3]



          Area      Above‑water decay

          of        ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

          season‑   Termites           Other

          ally      ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

          inunda-   CH4       CO2       CO2

          ted zone  (106      (106      (106

          (ha)      t gas)    t gas)    t gas)


‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-

Balbina  104,011    0.0004   0.46      14.22


Curuá-Una    980    0.0000   0.00       0.03


Samuel    12,650    0.0001   0.07       2.16


Tucuruí   85,766    0.0002   0.23       7.06

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-

TOTALS   203,407    0.0006   0.77      23.47

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-

[Table IX, part 4]



Underwater decay                                          Below‑ground decay


Wood                 Leaves and other      ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

                     non-wood biomass

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-‑‑‑‑‑‑‑‑‑‑‑‑‑‑---- CH4      CO2

CH4        CO2        CH4        CO2      (106     (106

(106       (106       (106       (106     t gas)   t gas)

t gas)     t gas)     t gas)     t gas)

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑------

0.002      0.000      0.005      0.05     0.00007  0.00


0.000      0.000      0.000      0.00     0.00000  0.00


0.000      0.000      0.001      0.02     0.00001  0.00


0.006      0.000      0.002      0.05     0.00006  0.00

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑----‑‑‑

0.009      0.000      0.007      0.13     0.00014  0.00

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ ‑‑‑‑‑‑‑‑‑‑‑‑‑----

[Table IX, part 5]




           Area of     Open     Macro-     Total from above-

           reser-      water    phyte      water decay

           voir                beds       ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-----

           at oper-

           ating       CH4      CH4        CH4        CO2

           level       (106     (106       (106       (106

           (ha)        t gas)   t gas)     t gas)     t gas)


Balbina   314,700      0.06      0.02      0.00      23.58


Curuá-Una   7,200      0.00      0.00      0.00       0.03


Samuel     46,500      0.01      0.00      0.00       4.13


Tucuruí   224,700      0.04      0.01      0.00       9.34


TOTALS    593,100      0.11      0.04      0.00      37.07


a  These results use the "low trace gas scenario" emission factor for termites (Table VI).  Using the "high" value (based on Goreau and Mello, 1987) increases the total emission only marginally from 0.259 to 0.260 X 106 t of methane gas.

[Table IX, part 6]



Total from           Total    Total     CO2-equivalent carbon

underwater           CH4      CO2

decay                                  (100-yr, zero discount;

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑                     direct effects)

CH4      CO2

(106     (106         (106     (106      (106 t carbon)

t gas)   t gas)       t gas)   t gas)



  0.07     0.18        0.14     23.75        6.91


  0.00     0.00        0.00      0.03        0.02


  0.01     0.07        0.02      4.20        1.21


  0.04     0.11        0.09      9.45        2.85


  0.12     0.36        0.26     37.44       10.99







                           Balbina  Tucuruí  Sources

                    Units  (1993)   (1991)   ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

                                             Balbina  Tucuruí


Installed capacity  MW       250      4000

Installed capacity  TWh yr-1   2.19     35.06

Average generation  MW       110.3    2057       a

Average generation  TWh yr-1   0.97     18.03          b

Percent of capacity (%)       44.1      51.4



                             Units     Amounts   Source



Power consumption in 1986    TWh       0.94


Projected substitution

for 1993:


              Diesel        106 l 316

              Diesel        GWh       791

              Fuel oil      103 t 113

              Fuel oil      GWh       333

              Total:        TWh       1.12          c





Fuel          Emission factor (t gas per 106 l)d


              CO2             CH4           N2O


Diesel        2,730         0.12                0.16

                           (0.06-0.25)   (0.13-0.4)


Light oil     2,830         0.02          0.16

                           (0.01-0.21)   (0.13-0.4)


Heavy oil     3,090         0.13          0.16

                           (0.03-0.12)   (0.13-0.4)


D.) BALBINA FOSSIL FUEL SUBSTITUTION (official projection for 1993)


Fuel      Million   Density   Million   Avoided emissions (t gas)

          liters    (t m-3)e   tons      ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

                                      CO2        CH4      N2O


Diesel    316       0.87     275     862,680      38       51

Fuel oilf  122       0.93     113     375,452      15       20

TOTAL                        388   1,238,132      53       71






                            CO2       CH4        N2O


Global warming potentialg   1         11         270





Fuel          CO2-gas equivalent (t)


            CO2             CH4        N2O       Total


Diesel      862,680         417      13,865       876,962

Fuel oil    375,452         167       5,331       380,950

TOTAL     1,238,132         584      19,196     1,257,911





a  Brazil, ELETRONORTE, 1985b.  Note: Brazil, ELETRONORTE/ MONASA/ENGE-RIO, 1976 gives average generation as 109 MW (= 0.96 TWh yr-1).

b  Brazil, ELETRONORTE, nd [1992]a: 3.

c  Brazil, ELETRONORTE, 1985b: Quadro 3.7.

d  Jaques, 1992.

e  Jaques, 1992: 48.

f  Assumed to be heavy fuel oil.

g  Radiative forcing relative, per t of gas, relative to 1 t of CO2, over a 100-yr time horizon without discounting (Isaksen et al. 1992: 56).




Emission      Hydro.      Hydro./   Emission/generation    Note

source        annual      fossil    ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

              emission    fuel      106 t     106 t

              (CO2-C      emission  CO2-      CO2-

              equiv.)     ratio     equiv./   equiv. C/

              (t)                  TWh       TWh


Balbina     6,908,399       20.1    26.20      7.14

Tucuruí     2,852,731        0.4     0.58      0.16         a



Manaus fossil fuel                  1.30      0.35

Coal-fired                          0.4       0.11         b, c

Natural gas                         1.0       0.27         b



Churchill/Nelson Dam (Canada)       0.04-0.06 0.01         b

Grand Rapids Dam (Canada)           0.30-0.5  0.11         b, c

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑---a  Assumes fossil fuel mix substituted by Tucuruí

is the same as that used in Manaus.


b  Comparisons from Rudd et al., 1993 (N.B.: these authors use a value of 60 for the global warming potential of methane, much higher than the IPCC value of 11 used for Balbina and Tucuruí).

c  Uses midpoint.

Fig. 3.


Fig. 4




Fig 6