Two greenhouse gases –methane (CH4) and nitrous oxide (N2O) - were monitored monthly during one year (2011) at the Eguzon Reservoir in France. The objective of the study was to quantify for the first ...time in a temperate area the total emissions of these gases through the main emission pathways (diffusion and bubbling from the reservoir, degassing and downstream diffusion). The reservoir was impounded in 1926 and had, in 2011, a eutrophic status promoting high organic matter degradation and nitrification-denitrification, all favouring CH4 and N2O production. CH4 and N2O emissions were dominated by diffusion from the reservoir surface (respectively 78.0% and 92.3%). Ebullition was only observed for CH4 and accounted for 14.0% of total CH4 emissions. Downstream degassing and diffusion represented 8.1% of the total CH4 emissions and 7.7% of the total N2O emissions.
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•An annual study on CH4 and N2O based on monthly campaigns is proposed.•This study will contribute to fill the gap of GHG data for temperate reservoirs.•CH4 and N2O emissions were dominated by the diffusion a the reservoir surface.•Expressed in CO2equivalent, CH4 emissions were about 3 times those of N2O.•The emission ratio of the reservoir is in the lower range of values for hydropower.
In the present study, we measured independently CH4 ebullition and diffusion in the footprint of an eddy covariance system (EC) measuring CH4 emissions in the Nam Theun 2 Reservoir, a recently ...impounded (2008) subtropical hydroelectric reservoir located in the Lao People's Democratic Republic (PDR), Southeast Asia. The EC fluxes were very consistent with the sum of the two terms measured independently (diffusive fluxes + ebullition = EC fluxes), indicating that the EC system picked up both diffusive fluxes and ebullition from the reservoir. We showed a diurnal bimodal pattern of CH4 emissions anti-correlated with atmospheric pressure. During daytime, a large atmospheric pressure drop triggers CH4 ebullition (up to 100 mmol m-2 d-1 ), whereas at night, a more moderate peak of CH4 emissions was recorded. As a consequence, fluxes during daytime were twice as high as during nighttime. Additionally, more than 4800 discrete measurements of CH4 ebullition were performed at a weekly/fortnightly frequency, covering water depths ranging from 0.4 to 16 m and various types of flooded ecosystems. Methane ebullition varies significantly seasonally and depends mostly on water level change during the warm dry season, whereas no relationship was observed during the cold dry season. On average, ebullition was 8.5 ± 10.5 mmol m-2 d-1 and ranged from 0 to 201.7 mmol m-2 d-1 . An artificial neural network (ANN) model could explain up to 46% of seasonal variability of ebullition by considering total static pressure (the sum of hydrostatic and atmospheric pressure), variations in the total static pressure, and bottom temperature as controlling factors. This model allowed extrapolation of CH4 ebullition on the reservoir scale and performance of gap filling over four years. Our results clearly showed a very high seasonality: 50% of the yearly CH4 ebullition occurs within four months of the warm dry season. Overall, ebullition contributed 60-80% of total emissions from the surface of the reservoir (disregarding downstream emissions), suggesting that ebullition is a major pathway in young hydroelectric reservoirs in the tropics.
We have incorporated a semi-mechanistic isoprene emission module into the JULES land-surface scheme, as a first step towards a modelling tool that can be applied for studies of vegetation – ...atmospheric chemistry interactions, including chemistry-climate feedbacks. Here, we evaluate the coupled model against local above-canopy isoprene emission flux measurements from six flux tower sites as well as satellite-derived estimates of isoprene emission over tropical South America and east and south Asia. The model simulates diurnal variability well: correlation coefficients are significant (at the 95 % level) for all flux tower sites. The model reproduces day-to-day variability with significant correlations (at the 95 % confidence level) at four of the six flux tower sites. At the UMBS site, a complete set of seasonal observations is available for two years (2000 and 2002). The model reproduces the seasonal pattern of emission during 2002, but does less well in the year 2000. The model overestimates observed emissions at all sites, which is partially because it does not include isoprene loss through the canopy. Comparison with the satellite-derived isoprene-emission estimates suggests that the model simulates the main spatial patterns, seasonal and inter-annual variability over tropical regions. The model yields a global annual isoprene emission of 535 ± 9 TgC yr−1 during the 1990s, 78 % of which from forested areas.
This work is an attempt to provide seasonal variation of biogenic NO emission fluxes in a Sahelian rangeland in Mali (Agoufou, 15.34° N, 1.48° W) for years 2004, 2005, 2006, 2007 and 2008. Indeed, NO ...is one of the most important precursors for tropospheric ozone, and previous studies have shown that arid areas potentially display significant NO emissions (due to both biotic and abiotic processes). Previous campaigns in the Sahel suggest that the contribution of this region in emitting NO is no longer considered as negligible. However, very few data are available in this region, therefore this study focuses on model development. The link between NO production in the soil and NO release to the atmosphere is investigated in this modelling study, by taking into account vegetation litter production and degradation, microbial processes in the soil, emission fluxes, and environmental variables influencing these processes, using a coupled vegetation–litter decomposition–emission model. This model includes the Sahelian Transpiration Evaporation and Productivity (STEP) model for the simulation of herbaceous, tree leaf and faecal masses, the GENDEC model (GENeral DEComposition) for the simulation of the buried litter decomposition and microbial dynamics, and the NO emission model (NOFlux) for the simulation of the NO release to the atmosphere. Physical parameters (soil moisture and temperature, wind speed, sand percentage) which affect substrate diffusion and oxygen supply in the soil and influence the microbial activity, and biogeochemical parameters (pH and fertilization rate related to N content) are necessary to simulate the NO flux. The reliability of the simulated parameters is checked, in order to assess the robustness of the simulated NO flux. Simulated yearly average of NO flux ranges from 2.09 to 3.04 ng(N) m−2 s−1 (0.66 to 0.96 kg(N) ha−1 yr−1), and wet season average ranges from 3.36 to 5.48 ng(N) m−2 s−1 (1.06 to 1.73 kg(N) ha−1 yr−1). These results are of the same order as previous measurements made in several sites where the vegetation and the soil are comparable to the ones in Agoufou. This coupled vegetation–litter decomposition–emission model could be generalized at the scale of the Sahel region, and provide information where few data are available.
The present work analyses the effect of dust aerosols on the surface and top of atmosphere radiative budget, surface temperature, sensible heat fluxes, atmospheric heating rate and convective ...activity over West Africa. The study is focused on the regional impact of a major dust event over the period of 7–14 March 2006 through numerical simulations performed with the mesoscale, nonhydrostatic atmospheric model MesoNH. Due to its importance on radiative budgets, a specific attention has been paid to the representation of dust single scattering albedo (SSA) in MesoNH by using inversions of the AErosol RObotic NETwork (AERONET). The radiative impacts are estimated using two parallel simulations, one including radiative effects of dust and the other without them. The simulations of dust aerosol impacts on the radiative budget indicate remarkable instantaneous (at midday) decrease of surface shortwave (SW) radiations over land, with regional (9°–17° N, 10° W–20° E) mean of −137 W/m2 during the 9 to 12 March period. The surface dimming resulting from the presence of dust is shown to cause important reduction of both surface temperature (up to 4°C) and sensible heat fluxes (up to 100 W/m2), which is consistent with experimental observations. At the top of the atmosphere, the SW cooling (regional mean of −12.0 W/m2) induced by mineral dust is shown to dominate the total net (shortwave + longwave) effect. The maximum SW heating occurs within the dusty layer with values comprised between 4 and 7° K by day and LW effect results in a cooling of −0.10/−0.20° K by day. Finally, the simulations suggest the decrease of the convective available potential energy (CAPE) over the region in the presence of mineral dust.
African biomass burning emission inventories for gaseous and particulate species have been constructed at a resolution of 1 km by 1km with daily coverage for the 2000-2007 period. These inventories ...are higher than the GFED2 inventories, which are currently widely in use. Evaluation specifically focusing on combustion aerosol has been carried out with the ORISAM-TM4 global chemistry transport model which includes a detailed aerosol module. This paper compares modeled results with measurements of surface BC concentrations and scattering coefficients from the AMMA Enhanced Observations period, aerosol optical depths and single scattering albedo from AERONET sunphotometers, LIDAR vertical distributions of extinction coefficients as well as satellite data. Aerosol seasonal and interannual evolutions over the 2004-2007 period observed at regional scale and more specifically at the Djougou (Benin) and Banizoumbou (Niger) AMMA/IDAF sites are well reproduced by our global model, indicating that our biomass burning emission inventory appears reasonable.
Surface emission and deposition fluxes of reactive nitrogen compounds have been studied in five sites of West Africa during the period 2002 to 2007. Measurements of N deposition fluxes have been ...performed in IDAF sites representative of main west and central African ecosystems, i.e., 3 stations in dry savanna ecosystems (from 15° N to 12° N), and 2 stations in wet savanna ecosystems (from 9° N to 6° N). Dry deposition fluxes are calculated from surface measurements of NO2, HNO3 and NH3 concentrations and simulated deposition velocities, and wet deposition fluxes are calculated from NH4+ and NO3− concentration in samples of rain. Emission fluxes are evaluated including simulated NO biogenic emission from soils, emissions of NOx and NH3 from biomass burning and domestic fires, and volatilization of NH3 from animal excreta. This paper is a tentative to understand the eventual impact of the monsoon variability from year to year, with the natural variability of local sources, on the emission and deposition N fluxes, and to compare these evolutions between dry and wet savanna ecosystems. In dry savanna ecosystems where the rain season lasts mainly from June to September, the occurence of rain correlates with the beginning of emission and deposition fluxes. This link is less obvious in wet savanna ecosystems (wet season mainly from May to October), where the surface is less submitted to drastic changes in terms of water content. Whatever the location, the natural variability of rain from year to year does not exceed 15 %, and the variability of emission and deposition magnitude ranges between 15 % and 28 %. While quasi providing the same total N budget, and due to the presence of different types of soils and vegetation, wet and dry savanna do not present the same distribution in emission and deposition fluxes contributions: in dry savanna, the emission is dominated by ammonia volatilization, and the deposition is dominated by the dry contribution. In wet savanna, emission is equally distributed between ammonia volatilization, emissions from biomass burning and natural NO emissions from soils, and wet and dry deposition are equivalent. Due to the scarcity of available data on the African continent, and despite the numerous uncertainties resulting from the different calculations and assumptions, this work is a combination of data from different origins (surface measurements, satellite and modelling) to document the atmospheric Nitrogen cycle in tropical regions.
•Eddy covariance, and automated and static chamber methodologies are compared.•N2O fluxes measured at different scales agree in temporal dynamics.•Methods agree in magnitude dynamics in the highest ...and lowest ranges of N2O fluxes.•EC methodology still needs to be enhanced to reduce the high variability and uncertainty in the near background N2O fluxes.•Chamber-related environment perturbation biased the measured N2O fluxes.
This paper presents the NitroCOSMES campaign, aimed at testing and evaluating the performance of three methods for monitoring N2O fluxes over an agricultural field. The experiment was conducted from May to August 2012 at a site located in the south-west of France. N2O fluxes from a 24 ha irrigated maize field were measured using eddy covariance (EC), automated chamber (AC) and static chamber (SC) methodologies. Uncertainties were calculated according to the specificities of each set-up. Measurements were performed over a large range of water-filled pore spaces (WFPS), soil temperatures, and mineral nitrogen availability, and offered the opportunity to compare methodologies over a wide range of N2O emission intensities. The average N2O fluxes were compared among the three methodologies during the same periods of measurement and for different intensities of emissions (low, moderate and high). Periods of comparison were determined according to the AC results. On average, the three methods gave comparable results for the low (SC: 14.7 ± 2.2, EC: 15.7 ± 10.1, AC: 17.5 ± 1.6 ng N2O-N m−² s−1) and the high (SC: 131.7 ± 22.1, EC: 125.3 ± 8, AC: 125.1 ± 8.9 ng N2O-N m−² s−1) N2O emission ranges. For the moderate N2O emission range, AC measurements gave higher emissions (57.2 ± 3.9 ng N2O-N m−² s−1) on average than both the SC (41.6 ± 6.6 ng N2O-N m−² s−1) and EC (33.8 ± 3.9 ng N2O-N m−² s−1) methods, which agreed better with each other. The relative standard deviation coefficient (RSD) indicated that EC methodology gave highly variable values during periods of low N2O emissions, from -52.2 ± 88.1 to 62.2 ± 50.7 ng N2O-N m−² s−1, with a mean RSD of 151%. Water vapour effects (dilution and spectroscopic cross-sensitivity) were discussed in an attempt to explain the high variability in low N2O emission measurements. Even after applying the Webb term correction, there could still be a spectroscopic cross-sensitivity effect of water vapour on the N2O trace gas signal because of the layout of the analysers, which was not determined during the experiment. This study underlined that EC methodology is a promising way to estimate and refine N2O budgets at the field scale and to analyse the effects of different agricultural practices more finely with continuous flux monitoring. It also highlighted the need to continue the effort to assess and develop chambers and EC methodologies, especially for the low N2O emission measurement range, for which values and systematic uncertainties remain high and highly variable.
NO soil emissions are directly influenced by soil environmental (temperature, humidity), chemical (pH, N content, C content…) and physical (soil content, texture) variables. All these parameters ...exert linear or non linear influences that fluctuate in threshold and intensity between sites. Because of the lack of field experiments and to the high variability in time (diurnal and seasonal cycle) and space (regions, soil and vegetation type) of the environmental parameters influencing NO emissions, estimates of NO emissions worldwide still remain highly uncertain. In this study we developed nonlinear regressions to describe NO flux emission from soil in dependency with relevant environmental parameters for a forest site in a temperate region (Höglwald, South Germany, 1994–1997) using an Artificial Neural Network (ANN). The resulting algorithm links NO fluxes with air, surface and depth temperatures, surface WFPS (Water Field Pore Space) and humus pH. All these parameters were evaluated and selected as relevant and non redundant. Network performances are evaluated for different numbers of hidden neurons. Resulting equations linking NO fluxes from soils and variables are obtained, and show to perform well with measurements (R2 = 0.81). Average NO fluxes values of 14.6 gN ha−1 d−1 are obtained for calculated and measured fluxes. In a second part, 2002–2003 NO soil fluxes are estimated from the ANN equation obtained from 1994–1997 flux measurements performed at the same site. Overall, simulated results give a good estimation of NO fluxes, with a mean value of 15.3 gN ha d−1 close to the 21.7 gN ha d−1 measured mean for the 2002–2003 period. ANN algorithm gives also a good representation of low frequency (seasonal) variations. On the basis of our results, we suggest that ANN is a good alternative between detailed biogeochemical models and large scale models, and may be the appropriate tool for estimating NO emissions at a regional scale.
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