Implementation of a Markov Chain Monte Carlo method to inorganic aerosol modeling of observations from the MCMA-2003 campaign ? Part I: Model description and application to the La Merced site

International audienceThe equilibrium inorganic aerosol model ISORROPIA was embedded in a Markov Chain Monte Carlo algorithm to develop a powerful tool to analyze aerosol data and predict gas phase concentrations where these are unavailable. The method directly incorporates measurement uncertainty, prior knowledge, and provides a formal framework to combine measurements of different quality. The method was applied to particle- and gas-phase precursor observations taken at La Merced during the Mexico City Metropolitan Area (MCMA) 2003 Field Campaign and served to discriminate between diverging gas-phase observations of ammonia and predict gas-phase concentrations of hydrochloric acid. The model reproduced observations of particle-phase ammonium, nitrate, and sulfate well. The most likely concentrations of ammonia were found to vary between 4 and 26 ppbv, while the range for nitric acid was 0.1 to 55 ppbv. During periods where the aerosol chloride observations were consistently above the detection limit, the model was able to reproduce the aerosol chloride observations well and predicted the most likely gas-phase hydrochloric acid concentration varied between 0.4 and 5 ppbv. Despite the high ammonia concentrations observed and predicted by the model, when the aerosols were assumed to be in the efflorescence branch they are predicted to be acidic (pH~3)

Implementation of a Markov Chain Monte Carlo method to inorganic aerosol modeling of observations from the MCMA-2003 campaign ? Part II: Model application to the CENICA, Pedregal and Santa Ana sites

International audienceA Markov Chain Monte Carlo model for integrating the observations of inorganic species with a thermodynamic equilibrium model was presented in Part I of this series. Using observations taken at three ground sites, i.e. a residential, industrial and rural site, during the MCMA-2003 campaign in Mexico City, the model is used to analyze the inorganic particle and ammonia data and to predict gas phase concentrations of nitric and hydrochloric acid. In general, the model is able to accurately predict the observed inorganic particle concentrations at all three sites. The agreement between the predicted and observed gas phase ammonia concentration is excellent. The NOz concentration calculated from the NOy, NO and NO2 observations is of limited use in constraining the gas phase nitric acid concentration given the large uncertainties in this measure of nitric acid and additional reactive nitrogen species. Focusing on the acidic period of 9?11 April identified by Salcedo et al. (2006), the model accurately predicts the particle phase observations during this period with the exception of the nitrate predictions after 10:00 a.m. (Central Daylight Time, CDT) on 9 April, where the model underpredicts the observations by, on average, 20%. This period had a low planetary boundary layer, very high particle concentrations, and higher than expected nitrogen dioxide concentrations. For periods when the particle chloride observations are consistently above the detection limit, the model is able to both accurately predict the particle chloride mass concentrations and provide well-constrained HCl (g) concentrations. The availability of gas-phase ammonia observations helps constrain the predicted HCl (g) concentrations. When the particles are aqueous, the most likely concentrations of HCl (g) are in the sub-ppbv range. The most likely predicted concentration of HCl (g) was found to reach concentrations of order 10 ppbv if the particles are dry. Finally, the atmospheric relevance of HCl (g) is discussed in terms of its indicator properties for the possible influence of chlorine-mediated photochemistry in Mexico City

Effect of the Aerosol-Phase State on Secondary Organic Aerosol Formation from the Reactive Uptake of Isoprene-Derived Epoxydiols (IEPOX)

Acid-catalyzed reactions between gas- and particle-phase constituents are critical to atmospheric secondary organic aerosol (SOA) formation. The aerosol-phase state is thought to influence the reactive uptake of gas-phase precursors to aerosol particles by altering diffusion rates within particles. However, few experimental studies have explored the precise role of the aerosol-phase state on reactive uptake processes. This laboratory study systematically examines the reactive uptake coefficient (γ) of trans-β-isoprene epoxydiol (trans-β-IEPOX), the predominant IEPOX isomer, on acidic sulfate particles coated with SOA derived from α-pinene ozonolysis. γIEPOX is obtained for core-shell particles, the morphology of which was confirmed by microscopy, as a function of SOA coating thickness and relative humidity. γIEPOX is reduced, in some cases by half of the original value, when SOA coatings are present prior to uptake, especially when coating thicknesses are > 15 nm. The diurnal trend of IEPOX lost to acid-catalyzed reactive uptake yielding SOA compared with other known atmospheric sinks (gas-phase oxidation or deposition) is derived by modeling the experimental coating effect with field data from the southeastern United States. IEPOX-derived SOA is estimated to be reduced by 16-27% due to preexisting organic coatings during the afternoon (12:00 to 7:00 p.m., local time), corresponding to the period with the highest level of production

ACTRIS ACSM intercomparison - Part 2: Intercomparison of ME-2 organic source apportionment results from 15 individual, co-located aerosol mass spectrometers

Chemically resolved atmospheric aerosol data sets from the largest intercomparison of the Aerodyne aerosol chemical speciation monitors (ACSMs) performed to date were collected at the French atmospheric supersite SIRTA. In total 13 quadrupole ACSMs (Q-ACSM) from the European ACTRIS ACSM network, one time-of-flight ACSM (ToF-ACSM), and one high-resolution ToF aerosol mass spectrometer (AMS) were operated in parallel for about 3 weeks in November and December~2013. Part 1 of this study reports on the accuracy and precision of the instruments for all the measured species. In this work we report on the intercomparison of organic components and the results from factor analysis source apportionment by positive matrix factorisation (PMF) utilising the multilinear engine 2 (ME-2). Except for the organic contribution of mass-to-charge ratio m/z 44 to the total organics (f44), which varied by factors between 0.6 and 1.3 compared to the mean, the peaks in the organic mass spectra were similar among instruments. The m/z 44 differences in the spectra resulted in a variable f44 in the source profiles extracted by ME-2, but had only a minor influence on the extracted mass contributions of the sources. The presented source apportionment yielded four factors for all 15 instruments: hydrocarbon-like organic aerosol (HOA), cooking-related organic aerosol (COA), biomass burning-related organic aerosol (BBOA) and secondary oxygenated organic aerosol (OOA). ME-2 boundary conditions (profile constraints) were optimised individually by means of correlation to external data in order to achieve equivalent / comparable solutions for all ACSM instruments and the results are discussed together with the investigation of the influence of alternative anchors (reference profiles). A comparison of the ME-2 source apportionment output of all 15 instruments resulted in relative standard deviations (SD) from the mean between 13.7 and 22.7 % of the source's average mass contribution depending on the factors (HOA: 14.3 ± 2.2 %, COA: 15.0 ± 3.4 %, OOA: 41.5 ± 5.7 %, BBOA: 29.3 ± 5.0 %). Factors which tend to be subject to minor factor mixing (in this case COA) have higher relative uncertainties than factors which are recognised more readily like the OOA. Averaged over all factors and instruments the relative first SD from the mean of a source extracted with ME-2 was 17.2 %

Field intercomparison of the gas/particle partitioning of oxygenated organics during the Southern Oxidant and Aerosol Study (SOAS) in 2013

We present results of the first intercomparison of real-time instruments for gas/particle partitioning of organic species. Four recently-developed instruments that directly measure gas/particle partitioning in near-real time were deployed in Centreville, Alabama during the Southern Oxidant Aerosol Study (SOAS) in 2013. Two instruments were filter inlet for gases and aerosols high-resolution chemical ionization mass spectrometers (FIGAERO-HRToF-CIMS) with acetate (A-CIMS) and iodide (I-CIMS) ionization sources, respectively; the third was a semi-volatile thermal desorption aerosol GC-MS (SV-TAG); and the fourth was a high-resolution thermal desorption proton-transfer reaction mass spectrometer (HR-TD-PTRMS). Signals from these instruments corresponding to several organic acids were chosen for comparison. The campaign average partitioning fractions show good correlation. A similar level of agreement with partitioning theory is observed. Thus the intercomparison exercise shows promise for these new measurements, as well as some confidence on the measurement of low versus high particle-phase fractions. However, detailed comparison show several systematic differences that lie beyond estimated measurement errors. These differences may be due to at least eight different effects: (1) underestimation of uncertainties under low signal-to-noise; (2) inlet and/or instrument adsorption/desorption of gases; (3) differences in particle size ranges sampled; (4) differences in the methods used to quantify instrument backgrounds; (5) errors in high-resolution fitting of overlapping ion groups; (6) differences in the species included in each measurement due to different instrument sensitivities; and differences in (7) negative or (8) positive thermal decomposition (or ion fragmentation) artifacts. The available data are insufficient to conclusively identify the reasons, but evidence from these instruments and available data from an ion mobility spectrometer shows the particular importance of effects 6–8 in several cases. This comparison highlights the difficulty of this measurement and its interpretation in a complex ambient environment, and the need for further improvements in measurement methodologies, including isomer separation, and detailed study of the possible factors leading to the observed differences. Further intercomparisons under controlled laboratory and field conditions are strongly recommended

The Genome of the Netherlands: Design, and project goals

Within the Netherlands a national network of biobanks has been established (Biobanking and Biomolecular Research Infrastructure-Netherlands (BBMRI-NL)) as a national node of the European BBMRI. One of the aims of BBMRI-NL is to enrich biobanks with different types of molecular and phenotype data. Here, we describe the Genome of the Netherlands (GoNL), one of the projects within BBMRI-NL. GoNL is a whole-genome-sequencing project in a representative sample consisting of 250 trio-families from all provinces in the Netherlands, which aims to characterize DNA sequence variation in the Dutch population. The parent-offspring trios include adult individuals ranging in age from 19 to 87 years (mean=53 years; SD=16 years) from birth cohorts 1910-1994. Sequencing was done on blood-derived DNA from uncultured cells and accomplished coverage was 14-15x. The family-based design represents a unique resource to assess the frequency of regional variants, accurately reconstruct haplotypes by family-based phasing, characterize short indels and complex structural variants, and establish the rate of de novo mutational events. GoNL will also serve as a reference panel for imputation in the available genome-wide association studies in Dutch and other cohorts to refine association signals and uncover population-specific variants. GoNL will create a catalog of human genetic variation in this sample that is uniquely characterized with respect to micro-geographic location and a wide range of phenotypes. The resource will be made available to the research and medical community to guide the interpretation of sequencing projects. The present paper summarizes the global characteristics of the project

A high-quality human reference panel reveals the complexity and distribution of genomic structural variants

Structural variation (SV) represents a major source of differences between individual human genomes and has been linked to disease phenotypes. However, the majority of studies provide neither a global view of the full spectrum of these variants nor integrate them into reference panels of genetic variation. Here, we analyse whole genome sequencing data of 769 individuals from 250 Dutch families, and provide a haplotype-resolved map of 1.9 million genome variants across 9 different variant classes, including novel forms of complex indels, and retrotransposition-mediated insertions of mobile elements and processed RNAs. A large proportion are previously under reported variants sized between 21 and 100 bp. We detect 4 megabases of novel sequence, encoding 11 new transcripts. Finally, we show 191 known, trait-associated SNPs to be in strong linkage disequilibrium with SVs and demonstrate that our panel facilitates accurate imputation of SVs in unrelated individuals

WGS-based telomere length analysis in Dutch family trios implicates stronger maternal inheritance and a role for RRM1 gene

Telomere length (TL) regulation is an important factor in ageing, reproduction and cancer development. Genetic, hereditary and environmental factors regulating TL are currently widely investigated, however, their relative contribution to TL variability is still understudied. We have used whole genome sequencing data of 250 family trios from the Genome of the Netherlands project to perform computational measurement of TL and a series of regression and genome-wide association analyses to reveal TL inheritance patterns and associated genetic factors. Our results confirm that TL is a largely heritable trait, primarily with mother’s, and, to a lesser extent, with father’s TL having the strongest influence on the offspring. In this cohort, mother’s, but not father’s age at conception was positively linked to offspring TL. Age-related TL attrition of 40 bp/year had relatively small influence on TL variability. Finally, we have identified TL-associated variations in ribonuclease reductase catalytic subunit M1 (RRM1 gene), which is known to regulate telomere maintenance in yeast. We also highlight the importance of multivariate approach and the limitations of existing tools for the analysis of TL as a polygenic heritable quantitative trait

Skewed X-inactivation is common in the general female population

X-inactivation is a well-established dosage compensation mechanism ensuring that X-chromosomal genes are expressed at comparable levels in males and females. Skewed X-inactivation is often explained by negative selection of one of the alleles. We demonstrate that imbalanced expression of the paternal and maternal X-chromosomes is common in the general population and that the random nature of the X-inactivation mechanism can be sufficient to explain the imbalance. To this end, we analyzed blood-derived RNA and whole-genome sequencing data from 79 female children and their parents from the Genome of the Netherlands project. We calculated the median ratio of the paternal over total counts at all X-chromosomal heterozygous single-nucleotide variants with coverage ≥10. We identified two individuals where the same X-chromosome was inactivated in all cells. Imbalanced expression of the two X-chromosomes (ratios ≤0.35 or ≥0.65) was observed in nearly 50% of the population. The empirically observed skewing is explained by a theoretical model where X-inactivation takes place in an embryonic stage in which eight cells give rise to the hematopoietic compartment. Genes escaping X-inactivation are expressed from both alleles and therefore demonstrate less skewing than inactivated genes. Using this characteristic, we identified three novel escapee genes (SSR4, REPS2, and SEPT6), but did not find support for many previously reported escapee genes in blood. Our collective data suggest that skewed X-inactivation is common in the general population. This may contribute to manifestation of symptoms in carriers of recessive X-linked disorders. We recommend that X-inactivation results should not be used lightly in the interpretation of X-linked variants