Department of Water Resources, Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, NL 7500, AE, the Netherlands.
Faculty of Chemistry, Federal University of Pará, Belém 66075-110, Brazil.
Sci Total Environ. 2019 Feb 10;650(Pt 1):394-407. doi: 10.1016/j.scitotenv.2018.08.403. Epub 2018 Aug 29.
Hydroelectric power reservoirs are considered potential contributors to the greenhouse effect in the atmosphere through the emittance of methane and carbon dioxide. We combined in situ sampling and gas chromatography with geostatistical and remote sensing approaches to estimate greenhouse gas (GHG) emissions of a large hydropower reservoir. We used remote sensing data to estimate the water surface and geospatial interpolation to calculate total emissions as a function of reservoir surface area. The CH and CO gas concentrations were linearly correlated to sampling time, confirming the adequacy of the in situ sampling method to measure GHG diffusive fluxes from reservoir water surfaces. The combination of high purity (99.99%) ISO-norm gas standards with a gas chromatograph, enabled us to achieve low measurement detection limits of 0.16 and 0.60 μmol mol, respectively, for CH (using a flame ionization or FID detector) and CO (using a thermal conductivity or TCD detector). Our results show that CO emissions are significantly (an order of 5.10-10) higher than those of CH in both the spatial and temporal domain for this reservoir. The total diffusive GHG emissions over a year (June 2011 to May 2012) of the Tucuruí hydropower reservoir being in operation, in units of tons of carbon, added up to 6.82 × 10 for CH and 1.19 × 10 for CO. We show that in situ GHG sampling using small floating gas chambers and high precision gas chromatography can be combined with geospatial interpolation techniques and remote sensing data to obtain estimates of diffusive GHG emissions from large water bodies with fluctuating water surfaces such as hydropower reservoirs. We recommend that more measurements and observations on these emissions are pursued in order to support and better quantify the ongoing discussions on estimates and mitigation of GHG emissions from reservoirs in the Amazon region and elsewhere in the world.
水力发电水库被认为是大气中温室效应的潜在贡献者，因为它们会排放甲烷和二氧化碳。我们结合了原位采样和气相色谱技术，并结合了地质统计学和遥感方法，以估算大型水力发电水库的温室气体（GHG）排放量。我们使用遥感数据估算水面，并通过地理空间插值计算总排放量，作为水库表面积的函数。CH 和 CO 气体浓度与采样时间呈线性相关，证实了原位采样方法足以测量水库水面的 GHG 扩散通量。高纯度（99.99％）ISO 标准气体与气相色谱仪的结合，使我们能够分别实现 CH（使用火焰电离或 FID 检测器）和 CO（使用热导率或 TCD 检测器）的低测量检测限，分别为 0.16 和 0.60μmol/mol。我们的结果表明，在该水库的时空域中，CO 排放明显（数量级为 5.10-10）高于 CH。正在运行的图库鲁伊水电站一年（2011 年 6 月至 2012 年 5 月）的总扩散 GHG 排放量，以吨碳为单位，CH 为 6.82×10，CO 为 1.19×10。我们表明，使用小型浮动气室和高精度气相色谱仪进行原位 GHG 采样，可以与地理空间插值技术和遥感数据相结合，以估算具有波动水面的大型水体（如水力发电水库）的扩散 GHG 排放量。我们建议对这些排放物进行更多的测量和观察，以支持和更好地量化当前关于亚马逊地区和世界其他地区水库 GHG 排放估算和缓解的讨论。
