| 1. |
- Gilardoni, S., et al.
(författare)
-
Better constraints on sources of carbonaceous aerosols using a combined C-14 - macro tracer analysis in a European rural background site
- 2011
-
Ingår i: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7324. ; 11:12, s. 5685-5700
-
Tidskriftsartikel (refereegranskat)abstract
- The source contributions to carbonaceous PM2.5 aerosol were investigated at a European background site at the edge of the Po Valley, in Northern Italy, during the period January-December 2007. Carbonaceous aerosol was described as the sum of 8 source components: primary (1) and secondary (2) biomass burning organic carbon, biomass burning elemental carbon (3), primary (4) and secondary (5) fossil organic carbon, fossil fuel burning elemental carbon (6), primary (7) and secondary (8) biogenic organic carbon. The mass concentration of each component was quantified using a set of macro tracers (organic carbon OC, elemental carbon EC, and levoglucosan), micro tracers (arabitol and mannitol), and C-14 measurements. This was the first time that C-14 measurements covered a full annual cycle with daily resolution. This set of 6 tracers, together with assumed uncertainty ranges of the ratios of OC-to-EC, and the reference fraction of modern carbon in the 8 source categories, provides strong constraints to the source contributions to carbonaceous aerosol. The uncertainty of contributions was assessed with a Quasi-Monte Carlo (QMC) method accounting for the variability of OC and EC emission factors, the uncertainty of reference fractions of modern carbon, and the measurement uncertainty. During winter, biomass burning composed 64% (+/- 15%) of the total carbon (TC) concentration, while in summer secondary biogenic OC accounted for 50% (+/- 16%) of TC. The contribution of primary biogenic aerosol particles was negligible during the entire year. Moreover, aerosol associated with fossil sources represented 27% (+/- 16%) and 41% (+/- 26%) of TC in winter and summer, respectively. The contribution of secondary organic aerosol (SOA) to the organic mass (OM) was significant during the entire year. SOA accounted for 30% (+/- 16 %) and 85% (+/- 12 %) of OM during winter and summer, respectively. While the summer SOA was dominated by biogenic sources, winter SOA was mainly due to biomass burning and fossil sources. This indicates that the oxidation of semi-volatile and intermediate volatility organic compounds co-emitted with primary organics is a significant source of SOA, as suggested by recent model results and Aerosol Mass Spectrometer measurements. Comparison with previous global model simulations, indicates a strong underestimate of wintertime primary aerosol emissions in this region. The comparison of source apportionment results in different urban and rural areas showed that the sampling site was mainly affected by local aerosol sources during winter and regional air masses from the nearby Po Valley in summer. This observation was further confirmed by back-trajectory analysis applying the Potential Source Contribution Function method to identify potential source regions.
|
|
| 2. |
|
|
| 3. |
- Larsen, B. R., et al.
(författare)
-
Sources for PM air pollution in the Po Plain, Italy: II. Probabilistic uncertainty characterization and sensitivity analysis of secondary and primary sources
- 2012
-
Ingår i: Atmospheric Environment. - : Elsevier BV. - 1352-2310. ; 50, s. 203-213
-
Tidskriftsartikel (refereegranskat)abstract
- Very high levels of ambient particulate matter (PM) are frequently encountered in the north of Italy and air quality limits are regularly exceeded. To obtain quantitative information on the pollution sources and to gain understanding of the dynamics of pollution episodes in this populated area PM10 and/or PM2.5 samples were collected daily at nine urban to regional sites distributed over the central Po Plain and one site in the Valtelline Valley. In total, 23 five-week winter campaigns and one comparative summer/ autumn campaign (2007-2009) were organized. The PM was analyzed for 61 chemical constituents and a data-base was built up consisting of approx. 70000 records of the concentrations and their associated uncertainty. In addition C-14/C-12 ratios were determined in PM10 from four sites. Primary and secondary sources were quantified using macro-tracer methods in combination with chemical mass balance modelling and positive matrix factorization and the combined results were computed by probability-and sensitivity analysis. Monte Carlo simulations yielded probability distributions for seven source categories contributing to the carbonaceous fraction of PM and five major source categories contributing to the PM10 and PM2.5 mass. Despite large uncertainties in the combined source contribution estimates the paper demonstrates that secondary aerosol formed simultaneously over the Po Plain is the main responsible for the typical, rapid build-up of air pollution after clean-air episodes. Next to secondary sources, the most important sources are primary emissions from road transport followed by biomass burning (BB). In the Valtelline Valley, higher contributions from BB and lower contributions from secondary sources were observed. (C) 2012 Elsevier Ltd. All rights reserved.
|
|
| 4. |
- Saevarsdottir, S., et al.
(författare)
-
Multiomics analysis of rheumatoid arthritis yields sequence variants that have large effects on risk of the seropositive subset
- 2022
-
Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 81:8
-
Tidskriftsartikel (refereegranskat)abstract
- Objectives To find causal genes for rheumatoid arthritis (RA) and its seropositive (RF and/or ACPA positive) and seronegative subsets. Methods We performed a genome-wide association study (GWAS) of 31 313 RA cases (68% seropositive) and similar to 1 million controls from Northwestern Europe. We searched for causal genes outside the HLA-locus through effect on coding, mRNA expression in several tissues and/or levels of plasma proteins (SomaScan) and did network analysis (Qiagen). Results We found 25 sequence variants for RA overall, 33 for seropositive and 2 for seronegative RA, altogether 37 sequence variants at 34 non-HLA loci, of which 15 are novel. Genomic, transcriptomic and proteomic analysis of these yielded 25 causal genes in seropositive RA and additional two overall. Most encode proteins in the network of interferon-alpha/beta and IL-12/23 that signal through the JAK/STAT-pathway. Highlighting those with largest effect on seropositive RA, a rare missense variant in STAT4 (rs140675301-A) that is independent of reported non-coding STAT4-variants, increases the risk of seropositive RA 2.27-fold (p=2.1x10(-9)), more than the rs2476601-A missense variant in PTPN22 (OR=1.59, p=1.3x10(-160)). STAT4 rs140675301-A replaces hydrophilic glutamic acid with hydrophobic valine (Glu128Val) in a conserved, surface-exposed loop. A stop-mutation (rs76428106-C) in FLT3 increases seropositive RA risk (OR=1.35, p=6.6x10(-11)). Independent missense variants in TYK2 (rs34536443-C, rs12720356-C, rs35018800-A, latter two novel) associate with decreased risk of seropositive RA (ORs=0.63-0.87, p=10(-9)-10(-27)) and decreased plasma levels of interferon-alpha/beta receptor 1 that signals through TYK2/JAK1/STAT4. Conclusion Sequence variants pointing to causal genes in the JAK/STAT pathway have largest effect on seropositive RA, while associations with seronegative RA remain scarce.
|
|
