Using carbon-14 and carbon-13 measurements for source attribution of atmospheric methane in the Athabasca oil sands region

The rapidly expanding and energy-intensive production from the Canadian oil sands, one of the largest oil reserves globally, accounts for almost 12&thinsp;% of Canada's greenhouse gas emissions according to inventories. Developing approaches for evaluating reported methane (CH4) emission is crucial for developing effective mitigation policies, but only one study has characterized CH4 sources in the Athabasca oil sands region (AOSR). We tested the use of 14C and 13C carbon isotope measurements in ambient CH4 from the AOSR to estimate source contributions from key regional CH4 sources: (1)&nbsp;tailings ponds, (2)&nbsp;surface mines and processing facilities, and (3)&nbsp;wetlands. The isotopic signatures of ambient CH4 indicate that the CH4 enrichments measured at the site were mainly influenced by fossil CH4 emissions from surface mining and processing facilities (56&thinsp;&plusmn;&thinsp;18&thinsp;%), followed by fossil CH4 emissions from tailings ponds (34&thinsp;&plusmn;&thinsp;18&thinsp;%) and to a lesser extent modern CH4 emissions from wetlands (10&thinsp;&plusmn;&thinsp;&lt;1&thinsp;%). Our results confirm the importance of tailings ponds in regional CH4 emissions and show that this method can successfully distinguish wetland CH4 emissions. In the future, the isotopic characterization of CH4 sources and measurements from different seasons and wind directions are needed to provide a better source attribution in the AOSR. &nbsp;</p

Statistical atmospheric inversion of local gas emissions by coupling the tracer release technique and local-scale transport modelling: a test case with controlled methane emissions

International audienceThis study presents a new concept for estimating the pollutant emission rates of a site and its main facilities using a series of atmospheric measurements across the pollutant plumes. This concept combines the tracer release method, local-scale atmospheric transport modelling and a statistical atmospheric inversion approach. The conversion between the controlled emission and the measured atmospheric concentrations of the released tracer across the plume places valuable constraints on the atmospheric transport. This is used to optimise the configuration of the transport model parameters and the model uncertainty statistics in the inversion system. The emission rates of all sources are then inverted to optimise the match between the concentrations simulated with the transport model and the pollutants' measured atmospheric concentrations, accounting for the transport model uncertainty. In principle, by using atmospheric transport modelling, this concept does not strongly rely on the good colocation between the tracer and pollutant sources and can be used to monitor multiple sources within a single site, unlike the classical tracer release technique. The statistical inversion framework and the use of the tracer data for the configuration of the transport and inversion modelling systems should ensure that the transport modelling errors are correctly handled in the source estimation. The potential of this new concept is evaluated with a relatively simple practical implementation based on a Gaussian plume model and a series of inversions of controlled methane point sources using acetylene as a tracer gas. The experimental conditions are chosen so that they are suitable for the use of a Gaussian plume model to simulate the atmospheric transport. In these experiments, different configurations of methane and acetylene point source locations are tested to assess the efficiency of the method in comparison to the classic tracer release technique in coping with the distances between the different methane and acetylene sources. The results from these controlled experiments demonstrate that, when the targeted and tracer gases are not well collocated, this new approach provides a better estimate of the emission rates than the tracer release technique. As an example, the relative error between the estimated and actual emission rates is reduced from 32 % with the tracer release technique to 16 % with the combined approach in the case of a tracer located 60 m upwind of a single methane source. Further studies and more complex implementations with more advanced transport models and more advanced optimisations of their configuration will be required to generalise the applicability of the approach and strengthen its robustness

Unravelling the genetic basis of variable clinical expression in neurofibromatosis 1

Neurofibromatosis type 1 (NF1) is a common autosomal dominant disorder which displays considerable inter- and intra-familial variability in phenotypic expression. To evaluate the genetic component of variable expressivity in NF1, we examined the phenotypic correlations between affected relatives in 750 NF1 patients from 275 multiplex families collected through the NF-France Network. Twelve NF1-related clinical features, including five quantitative traits (number of café-au-lait spots of small size and of large size, and number of cutaneous, subcutaneous and plexiform neurofibromas) and seven binary ones, were scored. All clinical features studied, with the exception of neoplasms, showed significant familial aggregation after adjusting for age and sex. For most of them, patterns of familial correlations indicated a strong genetic component with no apparent influence of the constitutional NF1 mutation. Heritability estimates of the five quantitative traits ranged from 0.26 to 0.62. Moreover, we investigated for the first time the role of the normal NF1 allele in the variable expression of NF1 through a family-based association study. Nine tag SNPs in NF1 were genotyped in 1132 individuals from 313 NF1 families. No significant deviations of transmission of any of the NF1 variants to affected offspring was found for any of the 12 clinical features examined, based on single marker or haplotype analysis. Taken together, our results provided evidence that genetic modifiers, unlinked to the NF1 locus, contribute to the variable expressivity of the disease