Dominique Serça

Gross CO2 and CH4 emissions from the Nam Ngum and Nam Leuk sub-tropical reservoirs in Lao PDR.

Gross CO2 and CH4 emissions (degassing and diffusion from the reservoir) and the carbon balance were assessed in 2009-2010 in two Southeast Asian sub-tropical reservoirs: the Nam Ngum and Nam Leuk Reservoirs (Lao PDR). These two reservoirs are within the same climatic area but differ mainly in age, size, residence time and initial biomass stock. The Nam Leuk Reservoir was impounded in 1999 after partial vegetation clearance and burning. However, GHG emissions are still significant 10 years after impoundment. CH4 diffusive flux ranged from 0.8 (January 2010) to 11.9 mmol m(-2) d(-1) (April 2009) and CO2 diffusive flux ranged from -10.6 (October 2009) to 38.2 mmol m(-2) d(-1) (April 2009). These values are comparable to other tropical reservoirs. Moreover, degassing fluxes at the outlet of the powerhouse downstream of the turbines were very low. The tentative annual carbon balance calculation indicates that this reservoir was a carbon source with an annual carbon export (atmosphere+downstream river) of about 2.2±1.0 GgC yr(-1). The Nam Ngum Reservoir was impounded in 1971 without any significant biomass removal. Diffusive and degassing CO2 and CH4 fluxes were lower than for other tropical reservoirs. Particularly, CO2 diffusive fluxes were always negative with values ranging from -21.2 (April 2009) to -2.7 mmol m(-2) d(-1) (January 2010). CH4 diffusive flux ranged from 0.1 (October 2009) to 0.6 mmol m(-2) d(-1) (April 2009) and no degassing downstream of the turbines was measured. As a consequence of these low values, the reservoir was a carbon sink with an estimated annual uptake of - 53±35 GgC yr(-1).

Soil NO emissions modelling using artificial neural network

Soils are considered as an important source for NO emissions, but the uncertainty in quantifying these emissionsa worldwide remains large due to the lack of field experiments and high variability in time and space of environmental parameters influencingNOemissions. In this study, the development of a relationship forNOflux emission from soil with pertinent environmental parameters is proposed. An Artificial Neural Network (ANN) is used to find the best non-linear regression between NO fluxes and seven environmental variables, introduced step by step: soil surface temperature, surface water filled pore space, soil temperature at depth (20.30 cm), fertilisation rate, sand percentage in the soil, pH and wind speed. The network performance is evaluated each time a new variable is introduced in the network, i.e. each variable is justified and evaluated in improving the network performance. A resulting equation linking NO flux from soil and the seven variables is proposed, and shows to perform well with measurements (R2 = 0.71), whereas other regression models give a poor correlation coefficient between calculation and measurements (R2 ≤ 0.12 for known algorithms used at regional or global scales). ANN algorithm is shown to be a good alternative between biogeochemical and large-scale models, for future application at regional scale.

Greenhouse Gas Emissions from Freshwater Reservoirs: What Does the Atmosphere See?

Freshwater reservoirs are a known source of greenhouse gas (GHG) to the atmosphere, but their quantitative significance is still only loosely constrained. Although part of this uncertainty can be attributed to the difficulties in measuring highly variable fluxes, it is also the result of a lack of a clear accounting methodology, particularly about what constitutes new emissions and potential new sinks. In this paper, we review the main processes involved in the generation of GHG in reservoir systems and propose a simple approach to quantify the reservoir GHG footprint in terms of the net changes in GHG fluxes to the atmosphere induced by damming, that is, ‘what the atmosphere sees.’ The approach takes into account the pre-impoundment GHG balance of the landscape, the temporal evolution of reservoir GHG emission profile as well as the natural emissions that are displaced to or away from the reservoir site resulting from hydrological and other changes. It also clarifies the portion of the reservoir carbon burial that can potentially be considered an offset to GHG emissions.

Livestock induces strong spatial heterogeneity of soil CO2, N2O and CH4 emissions within a semi-arid sylvo-pastoral landscape in West Africa

Greenhouse gas (GHG) emissions from the surface soils and surface water receiving animal excreta may be important components of the GHG balance of terrestrial ecosystems, but the associated processes are poorly documented in tropical environments, especially in tropical arid and semi-arid areas. A typical sylvo-pastoral landscape in the semi-arid zone of Senegal, West Africa, was investigated in this study. The study area (706 km² of managed pastoral land) was a circular zone with a radius of 15 km centered on a borehole used to water livestock. The landscape supports a stocking rate ranging from 0.11 to 0.39 tropical livestock units per hectare depending on the seasonal movements of the livestock. Six landscape units were investigated (land in the vicinity of the borehole, natural ponds, natural rangelands, forest plantations, settlements, and enclosed plots). Carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4) fluxes were measured with static chambers set up at 13 sites covering the six landscape units, and the 13 sites are assumed to be representative of the spatial heterogeneity of the emissions. A total of 216 fluxes were measured during the one-year study period (May 2014 to April 2015). At the landscape level, soils and surface water emitted an average 19.8 t C-CO2 eq/(hm²•a) (CO2: 82%, N2O: 15%, and CH4: 3%), but detailed results revealed notable spatial heterogeneity of GHG emissions. CO2 fluxes ranged from 1148.2 (±91.6) mg/(m²•d) in rangelands to 97,980.2 (±14,861.7) mg/(m²•d) in surface water in the vicinity of the borehole. N2O fluxes ranged from 0.6 (±0.1) mg/(m²•d) in forest plantations to 22.6 (±10.8) mg/(m²•d) in the vicinity of the borehole. CH4 fluxes ranged from–3.2 (±0.3) mg/(m²•d) in forest plantations to 8788.5 (±2295.9) mg/(m²•d) from surface water in the vicinity of the borehole. This study identified GHG emission “hot spots” in the landscape. Emissions from the surface soils were significantly higher in the landscape units most frequently used by the animals, i.e., in the vicinity of the borehole and settlements; and emissions measured from surface water in the vicinity of the borehole and from natural ponds were on average about 10 times higher than soil emissions.