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Nitrous oxide (N2O) is the third most important long-lived GHG and an important stratospheric ozone depleting substance. Agricultural practices and the use of N-fertilizers have greatly enhanced emissions of N2O. Here, we present estimates of N2O emissions determined from three global atmospheric inversion frameworks during the period 1998–2016. We find that global N2O emissions increased substantially from 2009 and at a faster rate than estimated by the IPCC emission factor approach. The regions of East Asia and South America made the largest contributions to the global increase. From the inversion-based emissions, we estimate a global emission factor of 2.3 ± 0.6%, which is significantly larger than the IPCC Tier-1 default for combined direct and indirect emissions of 1.375%. The larger emission factor and accelerating emission increase found from the inversions suggest that N2O emission may have a nonlinear response at global and regional scales with high levels of N-input.

Simulations of carbon fluxes with terrestrial biosphere models still exhibit significant uncertainties, in part due to the uncertainty in model parameter values. With the advent of satellite measurements of solar induced chlorophyll fluorescence (SIF), there exists a novel pathway for constraining simulated carbon fluxes and parameter values. We investigate the utility of SIF in constraining gross primary productivity (GPP). As a first test we assess whether SIF simulations are sensitive to important parameters in a biosphere model. SIF measurements at the wavelength of 755 nm are simulated by the Carbon-Cycle Data Assimilation System (CCDAS) which has been augmented by the fluorescence component of the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model. Idealized sensitivity tests of the SCOPE model stand-alone indicate strong sensitivity of GPP to the carboxylation capacity (Vcmax) and of SIF to the chlorophyll AB content (Cab) and incoming short wave radiation. Low sensitivity is found for SIF to Vcmax, however the relationship is subtle, with increased sensitivity under high radiation conditions and lower Vcmax ranges. CCDAS simulates well the patterns of satellite-measured SIF suggesting the combined model is capable of ingesting the data. CCDAS supports the idealized sensitivity tests of SCOPE, with SIF exhibiting sensitivity to Cab and incoming radiation, both of which are treated as perfectly known in previous CCDAS versions. These results demonstrate the need for careful consideration of Cab and incoming radiation when interpreting SIF and the limitations of utilizing SIF to constrain Vcmax in the present set-up in the CCDAS system.

This paper combines an atmospheric transport model and a terrestrial ecosystem model to estimate gross primary productivity (GPP) and net ecosystem productivity (NEP) of the land biosphere. Using atmospheric CO2observations in a Carbon Cycle Data Assimilation System (CCDAS) we estimate a terrestrial global GPP of 146 ± 19 GtC/yr. However, the current observing network cannot distinguish this best estimate from a different assimilation experiment yielding a terrestrial global GPP of 117 GtC/yr. Spatial estimates of GPP agree with data‐driven estimates in the extratropics but are overestimated in the poorly observed tropics. The uncertainty analysis of previous studies was extended by using two atmospheric transport models and different CO2 observing networks. We find that estimates of GPP and NEP are less sensitive to these choices than the form of the prior probability for model parameters. NEP is also found to be significantly sensitive to the transport model and this sensitivity is not greatly reduced compared to direct atmospheric transport inversions, which optimize NEP directly. Key Points Biosphere fluxes inferred from atmospheric measures using assimilation methods Pattern and magnitude of gross primary productivity and net ecosystem flux Uncertainties in biospheric fluxes from assimilation methods

Objective: This study aimed to itemize the causes for the failure of direct coronal restorations (DCRs) according to the practitioners of Côte d'Ivoire in order to provide recommendations for good practice. Materials and Methods: A descriptive, self-reporting, prospective survey was carried out among 109 dental surgeons (DSs) in the town of Abidjan based on 587 randomly selected practitioners supplied by the National Board of the Order. Results: The results show that 98.10% of the surveyed DSs had previously encountered cases of failure. Fracturing of the restoration, which is the basis for the hiatus, is the main cause of failure according to 51.40% of the surveyed practitioners, followed by pain “under the restoration” cited by 26.20% of them. Failure occurs within 6 months (30.85% of those surveyed), after 5 years (9.6% of those surveyed) for restorations with composite or glass ionomer cement (GIC), while for DCRs with amalgam, failure occurs within 6 months (28.70%), after 5 years (16%) and beyond 10 years (3.20%). Conclusion: The practitioners often encountered failures of DCRs, with fracture of the restoration as the cause. Dental amalgam appears to have a greater longevity than adhesive restorations. Faced with a failure, they more often opted for a replacement of the DCRs rather than a repair.

We describe a system for constraining the spatial distribution of fossil fuel emissions of CO2. The system is based on a modified Kaya identity which expresses emissions as a product of areal population density, per capita economic activity, energy intensity of the economy, and carbon intensity of energy. We apply the methodology of data assimilation to constrain such a model with various observations, notably, the statistics of national emissions and data on the distribution of nightlights and population. We hence produce a global, annual emission field at 0.25° resolution. Our distribution of emissions is smoother than that of the population downscaling traditionally used to describe emissions. Comparison with the Vulcan inventory suggests that the assimilated product performs better than downscaling for distributions of either population or nightlights alone for describing the spatial structure of emissions over the United States. We describe the complex structure of uncertainty that arises from combining pointwise and area‐integrated constraints. Uncertainties can be as high as 50% at the pixel level and are not spatially independent. We describe the use of 14CO2 measurements to further constrain national emissions. Their value is greatest over large countries with heterogeneous emissions. Generated fields may be found online (http://ffdas.org/).

The sensitivity of the process parameters of the Biosphere Energy Transfer HYdrology (BETHY) model to choices of atmospheric concentration network, high frequency terrestrial fluxes, and the choice of flux measurement network is investigated by using a carbon cycle data assimilation system. We use BETHY-generated fluxes as a proxy of flux measurements. Results show that monthly mean or low-frequency observations of CO2 concentration provide strong constraints on parameters relevant for net flux (NEP) but only weak constraints for parameters controlling gross fluxes. The use of high-frequency CO2 concentration observations, which has led to great refinement of spatial scales in inversions of net flux, adds little to the observing system in the Carbon Cycle Data Assimilation System (CCDAS) case. This unexpected result is explained by the fact that the stations of the CO2 concentration network we use are not well placed to measure such high frequency signals. Indeed, CO2 concentration sensitivities relevant for such high frequency fluxes are found to be largely confined in the vicinity of the corresponding fluxes, and are therefore not well observed by background monitoring stations. In contrast, our results clearly show the potential of flux measurements to better constrain the model parameters relevant for gross primary productivity (GPP) and net primary productivity (NPP). Given uncertainties in the spatial description of ecosystem functions, we recommend a combined observing strategy.

Monovalent rotavirus vaccine (RV1) was introduced in the immunization schedule of Togo in June 2014. We evaluated the impact of rotavirus vaccines on acute gastroenteritis (AGE) and rotavirus-associated hospitalizations in Togolese children. Sentinel surveillance for AGE (defined as ≥3 liquid or semi-liquid stools/24 h lasting <7 days) hospitalizations among children <5 years of age was conducted in two sites in the capital city, Lome. ELISA was used for diagnosis of rotavirus infection in children with AGE. Additionally, review of hospitalization registers was performed at five hospitals to assess trends in AGE hospitalizations among children aged <5 years. For the vaccine impact assessment, pre-rotavirus vaccine introduction (July 2010-June 2014) and post-rotavirus vaccine introduction (July 2014-June 2016) periods were compared for annual changes in proportions of hospitalizations associated with AGE and rotavirus. During the pre-vaccine period, sentinel surveillance showed that 1017 patients were enrolled and 57% (range, 53–62%) tested positive for rotavirus, declining to 42% (23% reduction) in the first post-vaccine year and to 26% (53% reduction) in the second post-vaccine year; declines were most marked among infants. The patient register review showed that, compared with pre-vaccine rotavirus seasons, declines in hospitalizations due to all-cause AGE during post-vaccine rotavirus seasons were 48% among <1 year age-group in both first and second years following vaccine introduction. Among 1–4 year olds no reduction was noted in the first year and a 19% decline occurred in the second year. We report rapid and marked reduction in the number of AGE hospitalizations and the proportion of AGE hospitalizations attributable to rotavirus in the first two years post- RV1 implementation in Togo. It is necessary to monitor long-term vaccine impact on rotavirus disease burden through continued surveillance.

We evaluate the capability of the global atmospheric transport model TM5 to simulate the boundary layer dynamics and associated variability of trace gases close to the surface, using radon (222Rn). Focusing on the European scale, we compare the boundary layer height (BLH) in the TM5 model with observations from the National Oceanic and Atmospheric Admnistration (NOAA) Integrated Global Radiosonde Archive (IGRA) and also with ceilometer and lidar (light detection and ranging) BLH retrievals at two stations. Furthermore, we compare TM5 simulations of 222Rn activity concentrations, using a novel, process-based 222Rn flux map over Europe (Karstens et al., 2015), with harmonised 222Rn measurements at 10 stations. The TM5 model reproduces relatively well the daytime BLH (within 10-20 % for most of the stations), except for coastal sites, for which differences are usually larger due to model representation errors. During night, however, TM5 overestimates the shallow nocturnal BLHs, especially for the very low observed BLHs (< 100 m) during summer. The 222Rn activity concentration simulations based on the new 222Rn flux map show significant improvements especially regarding the average seasonal variability, compared to simulations using constant 222Rn fluxes. Nevertheless, the (relative) differences between simulated and observed daytime minimum 222Rn activity concentrations are larger for several stations (on the order of 50 %) than the (relative) differences between simulated and observed BLH at noon. Although the nocturnal BLH is often higher in the model than observed, simulated 222Rn nighttime maxima are actually larger at several continental stations. This counterintuitive behaviour points to potential deficiencies of TM5 to correctly simulate the vertical gradients within the nocturnal boundary layer, limitations of the 222Rn flux map, or issues related to the definition of the nocturnal BLH. At several stations the simulated decrease of 222Rn activity concentrations in the morning is faster than observed. In addition, simulated vertical 222Rn activity concentration gradients at Cabauw decrease faster than observations during the morning transition period, and are in general lower than observed gradients during daytime. Although these effects may be partially due to the slow response time of the radon detectors, they clearly point to too fast vertical mixing in the TM5 boundary layer during daytime. Furthermore, the capability of the TM5 model to simulate the diurnal BLH cycle is limited by the current coarse temporal resolution (3 h/6 h) of the TM5 input meteorology.

This paper investigates the relationship between the heterogeneity of the terrestrial carbon cycle and the optimal design of observing networks to constrain it. We combine the methods of quantitative network design and carbon-cycle data assimilation to a hierarchy of increasingly heterogeneous descriptions of the European terrestrial biosphere as indicated by increasing diversity of plant functional types. We employ three types of observations, flask measurements of CO2 concentrations, continuous measurements of CO2 and pointwise measurements of CO2 flux. We show that flux measurements are extremely efficient for relatively homogeneous situations but not robust against increasing or unknown complexity. Here a hybrid approach is necessary, and we recommend its use in the development of integrated carbon observing systems.

An indirect solar dryer was designed and manufactured in Yamoussoukro, Côte d’Ivoire. It is equipped with three parameters including two air intake ports, a fan and a removable hot air recovery system. Vacuum CFD simulations were performed in order to observe the influence of these parameters on the effectiveness of the device. The fan switched off speeds of 9 m/s and made the air distribution uniform in the drying cabin. The natural convection operation made it possible to reach 62°C in the drying chamber compared to 55°C for the forced convection operation. The unique opening of the low air intake port in operation accentuates the temperature variations in the cabin compartments with differences of + 5°C from one level to another. The hot air return system has a positive impact on temperature trends because it allows values of 65°C to be reached inside the chamber, ideal for drying agri-food products. However, this recovery reduces the air velocity in the cabin, which is a disadvantage for the performance during products. This problem could be solved by increasing the fan power.