We present optimal quadratic estimators for the Fourier analysis of cosmological surveys that detect several different types of tracers of large-scale structure. Our estimators can be used to simultaneously fit the matter power spectrum and the biases of the tracers -as well as redshift-space distortions (RSDs), non-Gaussianities (NGs), or any other effects that are manifested through differences between the clusterings of distinct species of tracers. Our estimators reduce to the one by Feldman, Kaiser & Peacock (ApJ 1994, FKP) in the case of a survey consisting of a single species of tracer. We show that the multi-tracer estimators are unbiased, and that their covariance is given by the inverse of the multi-tracer Fisher matrix (Abramo, MNRAS 2013; Abramo & Leonard, MNRAS 2013). When the biases, RSDs and NGs are fixed to their fiducial values, and one is only interested in measuring the underlying power spectrum, our estimators are projected into the estimator found by Percival, Verde & Peacock (MNRAS 2003). We have tested our estimators on simple (lognormal) simulated galaxy maps, and we show that it performs as expected, being equivalent or superior to the FKP method in all cases we analyzed. Finally, we have shown how to extend the multi-tracer technique to include the 1-halo term of the power spectrum.

We constrain cosmological parameters by analysing the angular power spectra of the Baryon Oscillation Spectroscopic Survey DR12 galaxies, a spectroscopic follow-up of around 1.3 million SDSS galaxies over 9,376 deg 2 with an effective volume of ∼ 6.5 (Gpc h −1 ) 3 in the redshift range 0.15 ≤ z < 0.80. We split this sample into 13 tomographic bins (∆z = 0.05); angular power spectra were calculated using a Pseudo-C estimator, and covariance matrices were estimated using log-normal simulated maps. Cosmological constraints obtained from these data were combined with constraints from Planck CMB experiment as well as the JLA supernovae compilation. Considering a wCDM cosmological model measured on scales up to k max = 0.07h Mpc −1 , we constrain a constant dark energy equation-of-state with a ∼ 4% error at the 1σ level: w 0 = −0.993 +0.046 −0.043 , together with Ω m = 0.330 ± 0.012, Ω b = 0.0505 ± 0.002, S 8 ≡ σ 8 Ω m /0.3 = 0.863 ± 0.016, and h = 0.661 ± 0.012. For the same combination of datasets, but now considering a ΛCDM model with massive neutrinos and the same scale cut, we find: Ω m = 0.328 ± 0.009, Ω b = 0.05017 +0.0009 −0.0008 , S 8 = 0.862 ± 0.017, and h = 0.663 +0.006 −0.007 , and a 95% credible interval (CI) upper limit of m ν < 0.14 eV for a normal hierarchy. These results are competitive if not better than standard analyses with the same dataset, and demonstrate this should be a method of choice for future surveys, opening the door for their full exploitation in cross-correlations probes.

We investigate the impact of prior models on the upper bound of the sum of neutrino masses, mν . Using data from large scale structure of galaxies, cosmic microwave background, type Ia supernovae, and big bang nucleosynthesis, we argue that cosmological neutrino mass and hierarchy determination should be pursued using exact models, since approximations might lead to incorrect and nonphysical bounds. We compare constraints from physically motivated neutrino mass models (i.e., ones respecting oscillation experiments) to those from models using standard cosmological approximations. The former give a consistent upper bound of mν 0.26 eV (95% CI) and yield the first approximation-independent upper bound for the lightest neutrino mass species, m ν 0 < 0.086 eV (95% CI). By contrast, one of the approximations, which is inconsistent with the known lower bounds from oscillation experiments, yields an upper bound of mν 0.15 eV (95% CI); this differs substantially from the physically motivated upper bound.

Abstract. The quantification of sources of carbonaceous aerosol is important to understand their atmospheric concentrations and regulating processes and to study possible effects on climate and air quality, in addition to develop mitigation strategies.In the framework of the European Integrated Project on Aerosol Cloud Climate Interactions (EUCAARI) fine (D p < 2.5 µm) and coarse (2.5 µm < D p < 10 µm) aerosol particles were sampled from February to June (wet season) and from August to September (dry season) 2008 in the central Amazon basin. The mass of fine particles averaged 2.4 µg m −3 during the wet season and 4.2 µg m −3 during the dry season. The average coarse aerosol mass concentration during wet and dry periods was 7.9 and 7.6 µg m −3 , respectively. The overall chemical composition of fine and coarse mass did not show any seasonality with the largest fraction of fine and coarse aerosol mass explained by organic carbon (OC); the average OC to mass ratio was 0.4 and 0.6 in fine and coarse aerosol modes, respectively. The mass absorbing cross section of soot was determined by comparison of elemental carbon and light absorption coefficient measurements and it was equal to 4.7 m 2 g −1 at 637 nm. Carbon aerosol sources were identified by Positive Matrix Factorization (PMF) analysis of thermograms: 44% of fine total carbon mass was assigned to biomass burning, 43% to secondary organic aerosol (SOA), and 13% to volatile species that are difficult to apportion. In the coarse mode, primary biogenic aerosol particles (PBAP) dominated the carbonaceous aerosol mass. The results confirmed the importance of PBAP in forested areas.The source apportionment results were employed to evaluate the ability of global chemistry transport models to simulate carbonaceous aerosol sources in a regional tropical backCorrespondence to: E. Vignati (elisabetta.vignati@jrc.ec.europa.eu) ground site. The comparison showed an overestimation of elemental carbon (EC) by the TM5 model during the dry season and OC both during the dry and wet periods. The overestimation was likely due to the overestimation of biomass burning emission inventories and SOA production over tropical areas.

Elemental composition of aerosols is important to source apportionment studies and to understand atmospheric processes that influence aerosol composition. Energy dispersive X‐ray fluorescence spectroscopy was applied for measuring the elemental composition of Amazonian atmospheric aerosols. The instrument used was a spectrometer Epsilon 5, PANalytical B.V., with tridimensional geometry that reduces the background signal with a polarized X‐ray detection. The measurement conditions were optimized for low‐Z elements, e.g. Mg, Al, Si, that are present at very low concentrations in the Amazon. From Na to K, our detection limits are about 50% to 75% lower than previously published results for similar instrument. Calibration was performed using Micromatter standards, except for P whose standard was produced by nebulization of an aqueous solution of KH2PO4 at our laboratory. The multi‐element reference material National Institute of Standards and Technology–2783 (air particulate filter) was used for evaluating the accuracy of the calibration procedure of the 22 elements in our standard analysis routine, and the uncertainty associated with calibration procedures was evaluated. The overall performance of the instrument and validation of our measurements were assessed by comparison with results obtained from parallel analysis using particle‐induced X‐ray emission and another Epsilon 5 spectrometer. The elemental composition in 660 samples collected at a pristine site in the Amazon Basin and of 1416 samples collected at a site perturbed by land use change was determined. Our measurements show trace elements associated with biogenic aerosols, soil dust, biomass burning, and sea‐salt, even for the very low concentrations as observed in Amazonia. Copyright © 2014 John Wiley & Sons, Ltd.