dataesr/scientific-paragraphs-categorization huggingface dataset:
Trace elements The full trace element glass dataset of the tephra samples can be found in Supplementary Dataset-2 (SD-2). Phonolite tephra layers TF-107 and TF-111 (CG2) display relatively heterogeneous, yet largely overlapping trace element concentrations. For instance, Th contents range from 67-91 ppm and 66-95 ppm, respectively (Fig. 7a ). Despite the variability in absolute incompatible trace element concentrations, ratios of High Field Vico α trace element glass compositions are extremely heterogeneous (75-194 ppm Th; 1303-87 ppm Sr; 248-955 ppm Rb), consistent with their major element variability ranging from phonolite-trachytes to rhyolites  (Pereira et al. , 2020). The less evolved phonolite-trachyte glasses are more enriched in Sr, Ba and Eu relative to the rhyoltic end-member glasses, where these elements clearly behave compatibly during K-feldspar Only two successful analyses were obtained from the phonolitic Riano R-1 tephra, but the compositions are internally consistent for most incompatible elements, with the noticeable exception being the variable Nb content leading to a Nb/Th ratio of 0.
39-0. 48. Levels of incompatible trace element enrichement in the R-1 glasses (of unknown source area) appear more akin to those of Vulsini (e. g. , Castel Broco), rather than Vico (Fig. 7b ). Unfortunately, available trace element data for Sabatini are scant and cannot be considered here for comparison. Ratios of HFSE to Th are seemingly useful when evaluating the origin of the five tephra layers characterised here in the context of peri-Tyrrhenian potassic volcanism, particularly given the limited trace element glass data available for some regional volcanic sources, and thus a reliance on whole-rock datasets, which are not always directly comparable to volcanic glass data (e. g. ,  Tomlinson et al. , 2012). The Nb/Th ratios of the five Fucino layers analysed (TF-107, TF-111, TF-116, TF-125 and TF-126) clearly preclude an origin from the Neapolitan volcanic zone (e.
g. , Campi Flegrei, Ischia, Vesuvius), where Nb values are far higher at overlapping Th content, and Nb/Th ratios are typically > 1. 5 (glass datasets; Fig. 7a ). TF-107, TF-111, TF-116, TF-125 and TF-126 all have incompatible trace element concentrations and ratios of HFSE to Th compatible with the published analyses of the Latium and Roccamonfina volcanics (Fig. 7a ). However, Roccamonfina appears an unlikely source of the five Fucino tephra layers owing to its typically higher Ta/Th ratios (Fig. 7b ). In the investigated timespan, Colli Albani exclusively erupted K-foidites (CG-1) and can easily be discounted as the possible volcanic source of these Fucino layers, thus leaving the remaining Latium (Vulsini, Sabatini and Vico) volcanoes as the most obvious candidates. Indeed, ratios of HFSE to Th observed in TF-107, TF-111, TF-116, TF-125 and TF-126 are broadly consistent with those from published whole-rock (e.
e. , those with 52 < SiO2 wt% < 67 -CG-2 Fucino tephra (Fig. 7c-I ). Furthermore, the trace element compositions of all the phonolite and trachyte glass shards from the CG-2 (and CG-3) tephra layers also clearly precludes the Neapolitan volcanoes as possible eruptive sources (Fig. 7a-b ). Vulsini is the most probable source of these tephra layers. More detailed, individual tephra correlations are discussed below (see section 5. 2. 3. 3. ) and fully support this volcanic source attribution. Finally, despite the paucity of the proximal reference dataset, 87 Sr/ 86 Sr ratios also support a Vulsini origin for these two tephra layers (Fig. 8 ), while the trace elements confirm an origin from northern Latium (Vulsini or Vico) volcanoes (Fig. 7b ).
Tephra from Vico (CG-3). TF-125 -This tephra occurs in the lowermost portion of the F4-F5 record, ~50 cm upsection from TF-126 that was directly dated at 424. 3 ± 3. 2 ka  (Giaccio et al. , 2019). TF-125 is characterized by a heterogeneous phonolite-trachyte to rhyolite composition, with a silica content ranging from 59 to 77 wt% and an alkali content   Using this updated geochemical dataset for the Vico Period I products, we found that TF-125 major element composition matches that of Vico α of Pereira et al. (  2020 ) and of Tuscania-San Pietro TSP-1 (this study; Fig. 10b ), and this correlation is further strengthened by the similarities in the trace element glass compositions obtained here for Vico α and TF-125 (Fig. 11a ). Considering this geochemical affinity and its stratigraphic position between TF-126 (424.
Therefore, to take a conservative approach, while retaining a preferential attribution of TF-111 and TF-126 to the Vulsini district, we cannot fully exclude a Vico source for TF-111/TSP-3 and TF-126/pre-Vico α. Indeed, the unambiguous solution of this issue requires a statistically representative trace element dataset for both Vulsini and Vico products, which is not available yet. TF-107 shares a similar lithology and major element geochemistry with Riano R-1 tephra (Fig. 13a ), here tentatively attributed to the activity of the Vulsini volcanic district (Fig. 7c-II ) and dated at 404. 7 ± 5. 0 ka  (Marra et al. , 2018). While a correlation is further supported by very similar 87 Sr/ 86 Sr values (Fig. 8 ; Table  4 ), preliminary trace element glass analyses reveal some inconsistency (Fig.
g. ,  Sagnotti et al. , 2014). Furthermore, the Sulmona Basin tephra record spans discontinuously the MIS 15-MIS 10 period (e. g. ,  Giaccio et al. , 2013b , Giaccio et al. , 2014; Regattieri et al. , 2016) , but a comprehensive tephra study for this interval is still pending. Specifically, among several tephra spanning the MIS 11 period (Fig. 16 ), currently only one has been geochemically characterized  (Regattieri et al. , 2016). Based on its trachyte-rhyolite composition  Regattieri et al. (2016)  correlated it to Vico α, but according to the upgraded geochemical dataset obtained by  Pereira et al. (2020)  for the Vico Period I units, this tephra could be either attributed to Vico α or Vico β  (Pereira et al. , 2020). The rich tephra record of the river-lagoon stacked aggradational successions of the Tiber River delta, in central Italy  (Figs.
, , 2019 (Vakhrameeva et al. , , 2021)). None of the MIS 11 tephra from Tenaghi Philippon or ODP-964 are found in the Fucino record. In conclusion, the general tephrostratigrapic framework for MIS 11 is far from being satisfactorily developed for a reliable application to Quaternary sciences and volcanology. In this regard, the Fucino MIS 11 record arises as one of the fundamental reference geochemical and chronological datasets for the future development and application of the tephrochronology in the Mediterranean Region, especially for the areas closer to the highly productive tephra sources of peri-Tyrrhenian potassic volcanoes, i. e. , that have the potential of capturing part of the activity recorded at Fucino and thus to benefit from its rich tephrochronological record.
Nevertheless, due to its privileged location, we demonstrate that the Fucino paleolake captured most of the known major eruptions and many other unknown explosive events of the peri-Tyrrhenian potassic volcanoes. Therefore, reconstructing the explosive history of the peri-Tyrrhenian potassic volcanoes during the MIS 11 period using the Fucino record alone is fully justified and supported by the data gathered which illustrates that Fucino provides an extremely detailed eruptions record. Data source: Fucino:  Giaccio et al. (2017 Giaccio et al. ( , 2019)) ,  Mannella et al (2019) , This study; Sulmona:  Giaccio et al. (2013a Giaccio et al. ( , 2013b Giaccio et al. ( , 2014 Giaccio et al. ( , 2015a)) ,  Sagnotti et al. (2014) ,  Regattieri et al. (2015 Regattieri et al. ( , 2019)) ; Tiber River:  Florindo et al (2007) ,  Villa et al.
15 and 17b). Finally, the Fucino record allows us to refine the timing of the early Vico activity, indicating an age of ~377-379 ka for the emplacement of at least two additional, previously unknown, pyroclastic units (Figs. 15  and 17b ). Regarding the Sabatini volcanic district, the Fucino dataset improves the knowledge on the history and chronology of the activity, by providing a modelled age of 410. 0 ± 2. 0 ka for the CC-2 pumice fall  (Pereira et al. , 2020). Furthermore, Fucino records a cluster of four tephra (TF-102/TF-106) at ~397-400 ka, which may represent the equivalent of the Bag Tephra marker(s) of the Middle Pleistocene Hungarian loess, thus providing the first reliable age and climatostratigraphic position for this stratigraphic marker(s). If confirmed by future investigations, the recognition of this eruption cluster may shed new light on the Sabatini eruption frequency.
Indeed, during the whole eruptive history (589 ± 4 ka to 70 ± 3 ka) of the district, the longest dormancy of ~90 kyr has been so far documented in the time span 438 ± 1 to 329 ± 4 ka  (Marra et al. , 2020b). The Fucino dataset, showing a previously undetected eruption cluster at 398. 9 + 2. 6/2. 9 ka -397. 5 + 2. 8/-3. 1 ka, allows us to estimate a maximum quiescence of 68. 5 ± 4. 1 kyr in the district (i. e. , same as the time lapse since the last documented eruption), with implications for hazard assessment in the Roman area. However, at present we cannot exclude that this cluster of eruptions could originate by the Volsci volcanic field (Fig. 15 ), which documents activity in a comparable timespan (Table  6 ). With respect to the known stratigraphic and chronological framework of Colli Albani volcano  (Marra et al.
, 2003 (Marra et al. , , 2009 (Marra et al. , , 2016b;; Freda et al. , 2006; Giaccio et al. , 2009; Gaeta et al. , 2011 Gaeta et al. , , 2016)) , the Fucino dataset integrates the chronology of the post-caldera phase that followed the major Pozzolane Nere eruption. Specifically, the last documented eruption of this phase (i. e. , Centogocce succession; Fig. 15 ) occurs at 396. 4 ± 5 ka in the Fucino record, which confirms the 30. 6 ± 6. 4 kyr-long dormancy preceding the onset of the Villa Senni eruption cycle (365. 8 ± 1. 4 ka), as previously suggested  (Gaeta et al. , 2016). Such dormancies have relevance in understanding the relationships between the geodynamic/tectonic and magmatic processes  (Marra et al. , 2004) , stress-field and eruptive activity  (Marra et al. , 2009) , as well as in assessing the volcanic hazard in the Roman area  (Marra et al.
Nevertheless, the MIS 11 Fucino dataset improves the chronology, both in term of accuracy and precision, of the post-Rio Rava/pre-Brown Leucitic Tuff stage of the Roccamonfina activity, through the identification of a possible distal equivalent of the Mt. Ofelio-Mt. Capitolo parasitic centers  (Rouchon et al. , 2008). Overall, based on the updated chronological data for both proximal volcanic areas and Fucino succession, we obtained the probability density functions for the explosive activity of the peri-Tyrrhenian potassic volcanism during the MIS 11 period (Fig. 17c ). By comparing these statistical expressions of the regional explosive volcanism, the proximal record would seem to show a single, monotonous increase of the eruptive frequency between ~410 ka and ~395 ka, followed by a quite homogenous activity during the following 395-365 ka interval.
The resulting dataset allowed us to detect the volcanic sources of most of the newly investigated tephra layers and, in many cases, to recognise the specific equivalent eruption or eruptive phase. A Bayesian age-depth model, based on nine, either directly or geochemically correlated, 40 Ar/ 39 Ar dated tephra layers yielded a continuously dated record for the Fucino MIS 11 tephra. A synopsis of all the investigated tephra, along with their volcanic sources, corresponding eruptions and related ages is shown in Figure  15. By combining the updated stratigraphic, geochemical, and chronological datasets, we provide an overview of the MIS 11 tephrochronology for the central Mediterranean area (Fig. 16 ) and even beyond, as shown here by the discovering of a possible equivalent of the Hungarian Bag tephra.
Furthermore, regardless of the limitations of using a single location distal tephra archive to reconstruct past volcanism, the Fucino record clearly documents the eruptive history of the peri-Tyrrhenian explosive volcanoes of central Italy with unprecedented detail and at a higher chronological resolution with respect to available datasets from proximal areas. The improved knowledge of the activity histories of Vulsini, Vico, Sabatini, Colli Albani and Roccamonfina volcanoes, in many cases providing new evidence for previously unidentified eruptions and substantially improving the chronology of the known ones, sets the ground for refining the eruption timing and frequency as well as duration of intervening quiescence periods. This has key implications for hazard assessment as well as for identifying cyclic behaviour of the explosive activity (Fig.
Acknowledgments This article is a contribution of project " FUcino Tephrochronology Unites Quaternary Records (FUTURE) ", supported by the  Italian Ministry of Education, University and Research  ( MIUR , grant PRIN No. 20177TKBXZ_003 ;  G. Zanchetta , coordinator). The  Fucino  project is co-funded by  DFG  ( German Research Foundation ) grant  WA 2109/16. 40Ar/ 39 Ar dating also received complementary contribution from the  CNRS  INSU-LEFE 2018-2020 action to S. Nomade. P. G. Albert is supported by a  UKRI   Future Leaders Fellowship  ( MR/S035478/1 ). INGV, OV laboratories have been also financially supported by the  EPOS Research Infrastructure  through the contribution of the  Italian Ministry of University and Research (MUR). An earlier version of the manuscript benefited from useful comments from  Roberto Sulpizio  and an anonymous reviewer.
Other nadir-viewing, TIR satellite CO measurements To assess the consistency of the hemispheric temporal variability of CO in Section 3. 3, we compare data from a number of different nadirviewing satellite instruments that make measurements in the TIR band of CO. All these instruments are onboard satellites with sun-synchronous orbits and, besides AIRS, use optimal estimation approaches to retrieve CO columns from measured radiances. Northern Hemisphere (NH) and Southern Hemisphere (SH) monthly averages are collated from each instrument. A summary of instrument specific details are given in Table  1.
, 2012) , aircraft data  (Pommier et al. , 2010; Klonecki et al. , 2012)  and other satellite measurements  (George et al. , 2009). Comparison between MOPITT and IASI CO records found that, while a priori was the dominant source of between-instrument bias, timing and vertical sensitivity differences also contribute to CO differences  (George et al. , 2015). While the IASI-A record is long enough to determine trends, it is worth noting that this CO record is not currently retrieved using homogeneous temperature, humidity and cloud information. This causes a few discontinuities in the IASI-A CO record, which could affect the long-term trend and it is therefore not suited for trend studies at this time. Different versions of these IASI auxiliary parameters (distributed by Eumetsat) have been improved over time  (from V5 to V6 in Sept.
2014, and from V6 to V6. 1 in Sept. 2015). Reprocessing of these data with homogeneous auxiliary data is in progress at Eumetsat but they are not yet available at the time of this analysis (Oct. 2019). Despite this, IASI data are still useful for confirming the hemispheric CO seasonality and interannual variability observed by the other satellites. NH and SH monthly average values for daytime (SZA < 80), were computed after filtering for Super Quality Flag (SQF) = 0 (see https://iasi. aeris-data. fr/CO_readme/), CO total column < 20 × 10 18 molecules/cm 2 , Root Mean Square (RMS) ≤ 2. 7e - W/(cm 2 sr cm -1 ) and -0. 15e -9 ≤ bias ≤ 0. 25e -9 W/(cm 2 sr cm -1 ).
TES The Tropospheric Emission Spectrometer (TES) was launched on the NASA/Aura satellite in 2004 and crosses the equator at 13:40 LST, minutes after the NASA/Aqua satellite. TES measures radiance spectra of Earth's surface and atmosphere, with relatively fine spectral resolution (0. 10 cm -1 at nadir, apodized)  (Beer, 2006) , and retrieves trace gases, temperature  (Bowman et al. , 2006)  as well as cloud top pressure and cloud optical depth  (Kulawik et al. , 2006). TES CO profiles and total column amounts have been validated with respect to in situ measurements  (Luo et al. , 2007 (Luo et al. , , 2015)). For this study, we use V007 Level 2 data and select daytime retrievals filtered with master quality flag = 1 (good) that accounts for variations in retrieval performance, e. g. , residual radiance mismatch, and the degrees of freedom for signal (DFS)⩾0.
Trend analysis methodology In order to compare total column CO timeseries from different satellite instruments, we convert to column average VMR (X CO ) by dividing by the reported dry air column for each retrieval. Trends are reported as relative trends (% per year) by dividing by the dataset mean value. Relative trends in XCO are equivalent to relative trends in total column CO, but using X CO removes the dependence on surface topography that varies for the different instruments with different horizontal footprints. The first step in trend determination is to remove the seasonal variability, which can obscure any linear trend. For the global map plots of column CO and AOD trends (Section 3. 2), we remove seasonal variations using a 12-month running average prior to computing the linear trend.
The endpoints are truncated, effectively removing the first and last 6 months for all the time series. This determines our bounds for the long-term trend as July 2002 -June 2018. For hemispheric and regional time series analysis (Section 3. 3. and 3. 4), we remove the seasonal variations in X CO and AOD by subtracting the dataset mean annual cycle (with monthly resolution) to produce an anomaly time series. Trend analysis on deseasonalized data proceeds by calculating the slope of a line for the linear equation: y = mt + b + ε(t) (1) where y is the dependent variable (e. g. CO amounts), t is time in Master QF = 1; DFS > 0. 9 SQF = 0; COTC < 20 × 10 18 molec. /cm 2 ; RMS ≤ 2. 7e -9 W/(cm 2 sr cm -1 );-0. 15e -  ≤ bias ≤0. 25e -9 W/ (cm 2 sr cm -1 ) Master fractional years, m is the slope (or linear trend), b is a constant and ϵ(t) is the noise, or residual.
The Theil-Sen trend estimates in Section 4. 2 do not require compensation for autocorrelation in the noise, because consecutive values are separated by a year and CO has about a 2 month atmopsheric lifetime, meaning persistence is not significant. For example, the residuals for January trend analysis in the NH region show no significant autocorrelation (Fig. A5 ), even though the NH full timeseries showed the largest autocorrelation coefficient (ϕ = 0. 83) of all datasets. Similarly, no significant autocorrelation in the residuals was found in other regions when trend analysis is completed in months across different years. Table  A4. 1 Summary of uncertainties in the 2002-2018 trend analysis compared with WLS standard error in the slope. All values are shown in percent per year. Green backgrounds are significant.
Acknowledgements The  National Center for Atmospheric Research (NCAR)  is sponsored by the  National Science Foundation. The  NCAR MOPITT  project is supported by the  National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) Program. The MOPITT team also acknowledges support from the  Canadian Space Agency (CSA) , the  Natural Sciences and Engineering Research Council (NSERC)  and  Environment Canada , and the contributions of COMDEV (the prime contractor) and  ABB BOMEM. This work was funded by  NASA ROSES TASNPP , contract  80NSSC18K0687. Part of this research was carried out at the  Jet Propulsion Laboratory, California Institute of Technology , under a contract with  NASA. TES data are available from the  NASA Langley Research Center Atmospheric Science Data Center.
IASI is a joint mission of  EUMETSAT  and the  Centre National D'Etudes Spatiales (CNES, France). The  IASI L1  and  L2  input data are distributed in near real time by  EUMETSAT  through the EUMETCast system distribution. The IASI team also acknowledges the French Aeris atmospheric database (https://iasi. aeris-data. fr/)for providing the IASI L1C data and L2 data disseminated via EUMETCast, as well as  CNES  and  CNRS  for financial support. This work is also part of the  EUMETSAT/AC SAF  project. The research on IASI was also supported by the  Belgian Science Policy Office (BELSPO)  and the  European Space Agency (ESA)  (Prodex arrangement IASI. Flow). MODIS is a sensor aboard  NASA 's Terra and Aqua satellite missions. Native resolution L1B, L2 aerosol retrievals, and the gridded L3 atmospheric product used here (MOD08_M3) are all distributed via the LAADS DAAC (https://ladsweb.
Design and study population This was a cross-sectional, multi-centre, observational study. The detailed description of the study protocol has been described elsewhere  [23]. The study was approved by the French Data Protection Authority and the Ethics Committee in accordance with the Declaration of Helsinki and registered under N°I D RCB: 2017-A00812-51. The study focused on all hospital staff and students above 18 years of age registered with Nice university and Lenval hospitals from July 13, 2016, until the date of the study (conducted between June and October 2017). Overall, 10,100 subjects were registered on the Human Resources Departments' lists of both hospitals in June 2017. These subjects were offered to complete a web questionnaire with the help of the institutions' Human Resources Departments.
Data collection Web-based questionnaire Cross-functional working groups were involved in developing the web questionnaire to adapt its contents to the situation in Nice healthcare institutions and take staff members' experience and suggestions into account. Once the web questionnaire was available online, staff members could read the information describing the survey and obtain an access code via their mobile phone if they chose to participate and therefore provide their phone number. For each person who connected, the eligibility was verified via the online inclusion questionnaire. In the following part of the web questionnaire, informed consent was obtained from all participants. Each respondent then accessed the rest of the survey: according to the various types of exposure experienced, filter questions guided respondents towards the corresponding paths.
Acknowledgements The authors sincerely thank all those who accepted to be involved in this study:  Santé Publique France , for their expertise and contribution, and in particular  Dr. P. PIRARD ,  Y. MOTREFF ,  Dr. S. VANDENTORREN ;  Pr T. BAUBET , Scientific advisor from the  Centre National de Ressources et de Résilience  ( CN2R );  Mr. C. GUEPRATTE , managing director of  Nice University Hospital ;  Mr. A. POUILLART , managing director of the Fondation Lenval;  Mr. T. ARRII , Deputy director-general of  Nice University Hospital ; the members of the scientific committee:  Mrs. K. HAMELA  (Human Resources director),  Pr M. BENOIT  ( Psychiatry, Nice CHU ),  Dr. J. H. PLANCHARD  ( Occupational medicine, Nice CHU ); our colleagues from the  Nice University Public Health Department :  Dr. B.
Funding This study was supported by the  Regional Health Agency for Provence-Alpes-Côte d'Azur (Agence Régionale de la Santé ) who provided  Nice University Hospital  with financial support to identify and retribute a psychologist specialized in psychological trauma to care for exposed hospital staff, and by the  Fondation de France :  « Ensemble  face au terrorisme » (Together against terrorism) Committee who funded the data collection and management tool ( N°Engt 00079140 ).