Carbon Dioxide (CO2) Concentrations and Emission in the Newly Constructed Belo Monte Hydropower Complex in the Xingu River, Amazonia
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Biogeosciences, 16, 3527–3542, 2019 https://doi.org/10.5194/bg-16-3527-2019 © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. Carbon dioxide (CO2) concentrations and emission in the newly constructed Belo Monte hydropower complex in the Xingu River, Amazonia Kleiton R. de Araújo1, Henrique O. Sawakuchi2,3,a, Dailson J. Bertassoli Jr.4, André O. Sawakuchi1,4, Karina D. da Silva1,5, Thiago B. Vieira1,5, Nicholas D. Ward6,7, and Tatiana S. Pereira1,5 1Programa de Pós Graduação em Biodiversidade e Conservação, Universidade Federal do Pará, Altamira, 68372 – 040, Brazil 2Centro de Energia Nuclear na Agricultura, Universidade de São Paulo, Piracicaba, Brazil 3Department of Ecology and Environmental Science, Umeå University, Umeå, 901 87, Sweden 4Departamento de Geologia Sedimentar e Ambiental, Instituto de Geociências, Universidade de São Paulo, São Paulo, Brazil 5Faculdade de Ciências Biológicas, Universidade Federal do Pará, Altamira, 68372 – 040, Brazil 6Marine Sciences Laboratory, Pacific Northwest National Laboratory, Sequim, Washington 98382, USA 7School of Oceanography, University of Washington, Seattle, Washington 98195-5351, USA anow at: Department of Thematic Studies, Environmental Change, Linköping University, Linköping, 581 83, Sweden Correspondence: Kleiton R. de Araújo ([email protected]) Received: 9 February 2019 – Discussion started: 18 February 2019 Revised: 14 August 2019 – Accepted: 17 August 2019 – Published: 18 September 2019 Abstract. The Belo Monte hydropower complex located in the same order of magnitude as previous observations in the Xingu River is the largest run-of-the-river (ROR) hydro- other Amazonian clearwater rivers unaffected by impound- electric system in the world and has one of the highest energy ment during the same season. In contrast, during the low- 2 −1 production capacities among dams. Its construction received water season F CO2 (0:69±0:28 and 7:32±4:07 µmol m d significant media attention due to its potential social and en- for XR and IR, respectively) and pCO2 (839 ± 646 and vironmental impacts. It is composed of two ROR reservoirs: 1797 ± 354 µatm for XR and IR, respectively) in IR were an the Xingu Reservoir (XR) in the Xingu’s main branch and order of magnitude higher than literature F CO2 observations the Intermediate Reservoir (IR), an artificial reservoir fed in clearwater rivers with naturally flowing waters. When CO2 by waters diverted from the Xingu River with longer water emissions are compared between reservoirs, IR emissions residence time compared to XR. We aimed to evaluate spa- were 90 % higher than values from the XR during low-water tiotemporal variations in CO2 partial pressure (pCO2) and season, reinforcing the clear influence of reservoir charac- CO2 fluxes (F CO2) during the first 2 years after the Xingu teristics on CO2 emissions. Based on our observations in the River impoundment under the hypothesis that each reser- Belo Monte hydropower complex, CO2 emissions from ROR voir has contrasting F CO2 and pCO2 as vegetation clear- reservoirs to the atmosphere are in the range of natural Ama- ing reduces flooded area emissions. Time of the year had a zonian rivers. However, the associated reservoir (IR) may ex- significant influence on pCO2 with the highest average val- ceed natural river emission rates due to the preimpounding ues observed during the high-water season. Spatial hetero- vegetation influence. Since many reservoirs are still planned geneity throughout the entire study area was observed for to be constructed in the Amazon and throughout the world, pCO2 during both low- and high-water seasons. F CO2, on it is critical to evaluate the implications of reservoir traits the other hand, only showed significant spatial heterogene- on F CO2 over their entire life cycle in order to improve esti- ity during the high-water period. F CO2 (0:90 ± 0:47 and mates of CO2 emissions per kilowatt for hydropower projects 1:08 ± 0:62 µmol m2 d−1 for XR and IR, respectively) and planned for tropical rivers. pCO2 (1647 ± 698 and 1676 ± 323 µatm for XR and IR, re- spectively) measured during the high-water season were on Published by Copernicus Publications on behalf of the European Geosciences Union. 3528 K. R. de Araújo et al.: CO2 emission in the Belo Monte complex, Amazon 1 Introduction These discussions lasted at least 20 years and resulted in a se- ries of changes and revisions to the initial project (Fearnside, Rivers and streams are no longer considered passive pipes 2006). Nevertheless, the Belo Monte hydropower complex where terrestrial organic matter (OM) travels unchanged had its reservoirs filled in 2015 (MME, 2011), amid strong from land to sea (Cole et al., 2007). The OM transported environmental controversies (Fearnside, 2017) including un- by inland waters may be converted to carbon dioxide (CO2) certainties in estimates of greenhouse gas (GHG) emissions or methane (CH4) and escape to the atmosphere as gaseous (Fearnside, 2002). As such, alterations in the natural carbon emissions (Battin et al., 2009; Ward et al., 2013). Inland wa- cycling in the aquatic environments under direct and indirect ters cover an approximate area of 4.6 to 5 ×106 km2 or about influence of the Belo Monte hydropower facilities may result 3 % of Earth’s land surface (Downing et al., 2006; Verpoorter in significant impacts on the regional carbon budget. This is et al., 2014). Roughly 5.1 Pg C yr−1 is mobilized into inland a critical question to evaluate the GHG emissions related to waters from the terrestrial biosphere (Drake et al., 2017), of hydroelectricity produced from impoundment of large tropi- which about 2.1 Pg C yr−1 is emitted to the atmosphere as cal rivers. CO2 (Raymond et al., 2013). Despite the relatively small area Hundreds of new hydropower reservoirs are currently un- covered by inland waters, their carbon emissions offset the der construction or planning stages in tropical South Amer- ocean’s carbon sink (1:42 ± 0:53 Pg C yr−1) (Landchützer et ica, Africa, and Asia (Winemiller et al., 2016), and many of al., 2014). them may be ROR reservoirs. However, to our knowledge, Channel impoundment promotes several changes in river estimates of GHG emissions from ROR reservoirs only in- properties such as surface wind shear, water temperature, dis- clude measurements performed several decades after the con- charge and turbulence, and organic and inorganic sediment struction of a small temperate reservoir in Switzerland or input (St. Louis et al., 2000). These changes alter the micro- obtained through modeling for tropical reservoirs in Brazil bial community structure and biogeochemical processes in (DelSontro et al., 2010; Faria et al., 2015). Therefore, most the water column and riverbed sediments, with consequent of the GHG emissions estimates available in the literature are impacts on the dissolved carbon load, production, and even- for storage reservoirs but also with measurements representa- tual release to the atmosphere as CO2 (Battin et al., 2008). tive of several years (> 10 years) after the construction of the The intense decomposition of OM contained in flooded soils, hydropower dams (Kemenes et al., 2011; Lima et al., 2002). in addition to the consumption of allochthonous OM de- Exceptions are a tropical storage reservoir (Abril et al., 2005) posited in the reservoir, may lead to an increase in the CO2 and a boreal storage reservoir (Teodoru et al., 2011) studied production, and outgassing, particularly during the first years since impoundment. These studies showed that CO2 emis- of channel impoundment (Guérin et al., 2006). Longer water sions were higher during the first years of impoundment. residence time and reduction in water flow velocity, on the Thus, estimates of GHG emissions immediately after river other hand, may increase light penetration depth due to the impoundment are critical for determining the overall carbon deposition of suspended sediments, possibly counterbalanc- balance of the hydroelectricity system lifetime. ing those emissions due to higher CO2 uptake by primary The Belo Monte hydropower plant has two reservoirs op- producers (Duarte and Prairie, 2005). Alternatively, this con- erating under ROR conditions. The Xingu Reservoir (XR) dition may stimulate OM decomposition via photooxidation was formed by the impoundment of the Xingu River channel, that is favored by increased light absorbance (Miller and which has waters diverted to feed the Intermediate Reservoir Zepp, 1995) and microbial priming effects driven by in- (IR), created by the impoundment of a valley artificially con- teractions between allochthonous and autochthonous carbon nected to the left margin of the Xingu River. Although both sources (Ward et al., 2016). reservoirs are considered to be ROR, they differ in water res- Some of the hydropower dam impacts may be minimized idence time and type of flooded vegetation and substrates. according to the dam design. Run-of-the-river (ROR) hy- Flooded areas in the XR correspond mainly to seasonally dropower systems maintain a similar flow to a natural river flooded forest, but upland forest in marginal areas was also (Csiki and Rhoads, 2010), which generates smaller reservoirs flooded locally. Vegetation was removed from most of the that operate according to seasonal variations in water lev- flooded areas, but a part of the flooded forest islands in the els (Egré and Milewski, 2002). The Belo Monte hydropower XR was not cleared. On the other hand, the IR flooded large complex in the lower Xingu River operates as a ROR dam, swaths of upland forest, and pasture areas and its water resi- and it is the largest hydropower plant in the Amazon. It ranks dence time is higher than in the XR. third in the world in terms of installed capacity (11 233 MW), The aim of this study is to evaluate CO2 emissions from but with high variation in energy production throughout the the Belo Monte hydropower complex during the first 2 years year due to the high seasonality of the water discharge of the post-impoundment by assessing the spatial and temporal Xingu River (EPE, 2009).