dataesr/scientific-paragraphs-categorization huggingface dataset:
By combining the analysis conducted on these archives, we build a new composite record of atmospheric  [CO]  in the SH for the last three millennia. This new dataset is compared with [CO] data previously published  (Wang et al. , 2010 , Haan et al. , 1996; 1998)  which suggest an increase of about 100% in biomass burning by the late 1800s, as well as with other biomass burning proxies. We focus on interpreting the pre-industrial trends in atmospheric  [CO]  largely related to biomass burning and BVOC oxidation sources. Climate-chemistry models and/or Earth System Models can produce simulated atmospheric  [CO]  at ground level in Antarctica, from the PI era to present-day. Such models are evaluated presently within the Aerosol Chemistry Model Intercomparison Project (AerChemMIP)  (Collins et al.
, 2012 , Petrenko et al. , 2013). The IGE-GIPSA inverse firn model cannot reconstruct the CO seasonality  (Wang et al. , 2012) , therefore CO measurements above a depth ranging 30-40 m depending on the site investigated were excluded from the model input. Modeling several firn sites simultaneously to reconstruct a single atmospheric trend provides a much stronger constraint than a single firn site and allows evaluation of the consistency of the firn datasets. Best constraints are obtained when simultaneously modeling firn sites with very different physical characteristics (temperature, snow accumulation rate, etc. ) and drilling dates, which is the case for our five sites. The model can use data from firn air pumping and ice core analysis simultaneously, and here we link our reconstruction based on the firn measurements to the end of the ice core record.
Trace gas records in ice are affected by an additional smoothing process compared to firn air: bubbles in an ice sample close at a range of times. This process is less well constrained than trace gas transport in firn (e. g. Fourteau et al. , 2020)   The CSIRO inverse model used here is based on the Bayesian synthesis inversion described in  Trudinger et al. (2002 Trudinger et al. ( , 2016) )  but formulated to infer annual mixing ratios rather than annual sources. As with the IGE-GIPSA inverse model, the CSIRO inverse model infers a single atmospheric trend from multiple firn datasets modeled simultaneously. Both inverse models use Green's functions, which represent gas age distributions, to relate the mixing ratio of a trace gas at the measurement depths to atmospheric mixing ratio of that gas over a range of times  (Rommelaere et al.
Ice core samples Five ice cores extracted from Antarctica were investigated in this study (Fig. S1 ). The DC12, ABN, and Taldice (TD) ice cores (Table  2 ) were used to investigate the past atmospheric history of carbon monoxide over the late Holocene. Two additional Antarctic ice cores, EDML-B40 and Solarice (Fig. S1 ), which provided complementary and short datasets supporting paleoatmospheric interpretations, are described in Supplementary information (SI) (Table  S3  and SI Sect. 2. 6 and 2. 7). High resolution CO mixing ratios (See Sect. 2. 6) were measured continuously along with those of methane. DC12 ice core. This shallow ice core was drilled in 2012 at Concordia Station (Dome C) and fully analyzed for CO mixing ratio. The continuous methane record for this shallow Dome C ice core has been reported previously  (Fourteau et al.
Precision of continuous CO analyses We apply the Allan-Werle statistical method  (Allan, 1966 , Werle 1993)  to the calibration loop datasets to evaluate Internal precision and stability of gas-CFA measurements. Observed optimal integration time (i. e. , time of lowest Allan-Werle deviation) was determined for each analytical campaign, and is larger than 500 s for DRI, and 1000 s for IGE CFA setups (Fig. S2 ). Gas data were all averaged over a 10 sec integration time (IT). Such IT allowed full resolution of the variability of the Antarctic CO records. Internal precision, defined as twice the Allan-Werle deviation at chosen integration time, was 0. 7 and 1. 0 ppbv for the IGE (i. e. , DC12 and TD) and DRI (i. e. , ABN) analytical campaigns (Table  S2 ). External precision of the continuous CO measurements (i.
Continuous [CO] records along Antarctic ice cores The [CO] new records available from the DC12, ABN, and TD ice cores are reported in Fig. 2  and plotted for a period spanning -835 to 1897 CE (gas age, see Table  S1 ). The high resolution datasets represent the CFA output calibrated (WMO-X2014 scale, Sect. 2. 6. 3. and SI), vetted for lab air infiltrations (Sect. 2. 6. 5), with an integration time of 10 s. Splines based on the high resolution signals can be used to produce an average CO history for each site. The envelopes report 2σ uncertainties, and combine uncertainties evaluated specifically for each analytical setup on CO blanks, solubility calibration factors, and external precision of CO CFA measurements (see SI and previous sections). The high resolution DC12 CO record exhibits a 6 m gap, for gas ages spanning -114 to -209 CE, because samples were damaged during transport.
To infer the [CO] trend in this missing data interval, we analyzed a section of the Solarice core, which was drilled at Concordia Station in January 2016, 2 km away from the DC12 borehole. Solarice measurements reveal a smooth evolution of CO mixing ratio for the missing period in the DC12 records and we consequently extract a continuous spline from the DC12 dataset (SI Sect. 2. 7, Fig. S15 ). None of the Antarctic records revealed high and variable concentrations that were previously observed in Greenland ice cores and interpreted as in situ CO production  (Faïn et al. , 2014; 2022). The DC12, ABN, and TD records exhibit stable and low MAD (median absolute deviation) values, with mean MAD values over the entire datasets ranging from 1. 1 to 2. 4 ppbv, depending on the records. These values are much lower than the MAD values reported for Greenland [CO] records impacted by in situ production, which ranged from 10 to 80 ppbv  (Faïn et al.
A reconstruction spanning 1897 to 1992 CE from firn air data We applied the inverse IGE-GIPSA and CSIRO firn and inverse models (Sect. 2. 4) to reconstruct from [CO] firn depth profiles (Fig. 1a  and 1b ) the temporal evolutions of  [CO]  in the Antarctic atmosphere. The IGE-GIPSA reconstruction extends to 2016 CE, and is constrained in 1862-1889 CE by five synthetic data points in BKN ice with mean ages and CO mixing ratios consistent with the ice core composite presented in Sect. 3. 3. 2. Simulations performed with and without this ice constraint provide consistent results (within uncertainty limits of one another, for more details, see Sect. 2. 4 and SI Sect. 2. 3. 2). The CSIRO firn reconstruction extends to 1992 CE, after which the atmospheric history follows the atmospheric dataset collected at Mawson station, as described in Sect.
1a  and 1b ). Due to mixing by diffusion, CO mixing ratio profiles in firn are smoothed and the model interprets the CO variability between adjacent depth levels as noise, reflected in the uncertainty envelope. The detailed site by site comparisons of model results with firn data (Fig. S7  and S11 ), do not show site-specific systematic shifts that would be indicative of inconsistencies between the datasets. The IGE-GIPSA atmospheric [CO] history based on firn air samples (Fig. 1e ) reveals the following patterns: In this study, we use the two independent models as a way to incorporate firn model uncertainty. Over the period spanning 1920 to 1992, we average the IGE-GIPSA and CSIRO records' annual values to produce a multimodel firn air CO reconstruction. For the 1897-1920 CE period, a polynomial weight was introduced in the annual averaging of the two firn records.
3. 3. 1) than prior to the industrial times (i. e. , prior to 1850 CE). (Haan et al. , 1996; Wang et al. , 2010) , and South Pole (SP,  Wang et al. , 2010). Error bars on the VST, D47, and SP represent 2σ uncertainties. The VST [CO]  (Haan et al. , 1998)    There are substantial differences between our new record and the published D47/VST/SP dataset. First, the D47/VST/SP dataset exhibits about 10 ppbv higher [CO] than our record prior to 1500 CE, and in the early 1900s (Fig. 4 ). This difference is larger than our 2σ uncertainty envelope and therefore significant. Such disagreement is puzzling: the published datasets of D47, Vostok, and South Pole agree with each other although they were measured 15 years apart in different laboratories with different analytical methods. On the other hand, our new ice record is internally consistent between the four Antarctic sites (including Solarice core, SI Sect.
2. 7). Our new record also includes firn air datasets measured in three different laboratories (IGE, CSIRO, and MPI for the BKN firn air data,  Assonov et al. , 2007)  with different methods, and unlike the earlier records, are contiguous with modern [CO] atmospheric monitoring (Fig. 4 ). We showed in Section 3. 1 that atmospheric CO is relatively uniform over Antarctica, so these differences cannot be explained by spatial gradients between the different ice core sites.
Comparison with previous ice core CO records Haan's studies report [CO] on the CSIRO94 calibration scale which is 3% lower than the CSIRO2020 scale. Wang et al. (2010)  calibrated their dataset using a single 141 ppbv gas cylinder certified on the WMO-X2004 scale. The WMO-X2014 scale gives higher values by around 1 ppbv for mixing ratios lower than 200 ppbv compared to WMO-X2004 scale, including for the  [CO]  range reported by  Wang et al. (2010). In this study, consistent calibrations (WMO-X2014 and CSIRO2020) have been applied to all new firn air and ice core datasets. Consequently, a direct comparison of our new record with previously published CO datasets reported in Fig. 4  is possible. Second, our [CO] record and the South Pole dataset  (Wang et al. , 2010)  both exhibit a minimum during the LIA, but the exact timing of this minimum is different, with our record showing a minimum 100 yrs later than at South Pole (i.
, 2022). Thus the ABN record is not expected to be more affected by smoothing than the South Pole record during the LIA. Furthermore, we estimate that the smoothing effect from gas transport in firn and from progressive trapping in ice on the ABN or TD CO ice records is likely insignificant (SI Sect. 2. 8, Fig. S16  and S17 ). Overall, the lack of consistency between our new record and the published D47/VST/SP dataset is reminiscent of a previous study where we were not able to reconcile the Greenland [CO] Eurocore dataset of  Haan and Raynaud (1998)  and  Haan et al. (1996)  with multiple new Greenland ice core CO measurements made using both discrete and continuous analytical methods, including the PLACE ice core drilled 1km away from the Eurocore site  (Faïn et al. , 2022). Similarly, our Antarctic CO results call into question the accuracy of the CO values reported for the D47/VST/SP ice core.
We could speculate as a possible explanation for the difference that the quantification of CO contamination through the different discrete methods used for the D47/VST/SP ice cores significantly underestimated the true analytical bias introduced by these methods. An early Law Dome record of [CO] spanning 200-1600 CE was reported by  Ferretti et al. (2005). The general pattern of the Law Dome CO record differs from both our study and the D47/VST/SP  (Haan et al. , 1996 , Wang et al. , 2010)  dataset. Notably, Law Dome [CO] exhibits higher mixing ratios in the 50-90 ppbv range, with no significant decrease in [CO] during the 1400s. The Law Dome [CO] data were a by-product of the methane isotopic measurements by  Ferretti et al. (2005)  and had significantly higher measurement uncertainty and blank corrections than the dedicated [CO] measurements reported here.
Implications for pre-industrial SH fire history In this study, we report an atmospheric history for [CO] in the SH for the last three millennia (Fig. 3 ). Temporal variations in atmospheric [CO] could, in theory, result from changing emissions of CO and/or changing oxidation of CO during its transport from source areas to Antarctica. Oxidation by OH is the dominant sink of CO but past levels and variations of OH are notoriously difficult to quantify. Based on their ice core isotopic CO dataset (δ 13 C of CO),  Wang et al. (2010)  argued that the PI [CO] variability they observed (Fig. 4 ) was driven by changes in emissions rather than OH. Earth system models including atmospheric chemistry schemes suggest a stable global average OH-budget from pre-industrial times to 1980 CE  (Stevenson et al.
, 2016b). Considering the limited variation in atmospheric CO2, forest coverage and natural landscape prior to 1000 CE, it is unlikely that BVOC emissions have experienced significant changes over the last 3000 yrs. Evaluating the contribution of BVOC-oxidation to the Antarctic  [CO]  in PI times requires CO isotope datasets (e. g. ,  Wang et al. , 2010)  or a 3D chemistry transport model constrained with BVOC emission inventories (e. g. ,  Rowlinson et al. , 2021; Sect. 3. 5. 4). Decrease in BVOC emissions over the last millennia  (Acosta et al. , 2014)   (Acosta et al. , 2014). However, because such a decrease in BVOC emissions is likely limited, we conclude that atmospheric CO in the SH has not experienced large fluctuation driven by the BVOC oxidation source in PI times.
Evolution of the CO fire source prior to the LIA Our atmospheric history for  [CO]  in the SH for the last three millennia reported in Fig. 3  exhibit stable mixing ratios prior to 1500 CE, i. e. the onset of the LIA. Although some variations in [CO] exist, they are not significant within the 2σ uncertainty envelope. The VST  [CO]  dataset  (Haan and Raynaud, 1998 ) also exhibit stable CO mixing ratios for the period spanning from -200 to 1400 CE  (Fig. 4 and Sect. 3. 4). The ethane, acetylene and black carbon records retrieved from Antarctica's ice cores exhibit a similar stable pattern from 1000 to 1500 CE  (McConnell et al. , 2021; Nicewonger et al. , 2018) , suggesting stable biomass burning emissions during this period. Regional charcoal indexes are available from the Global Paleofire Database (https://database.
paleofire. org). In this study, we extract from this database unpublished regional charcoal indexes for two specific areas: the 30-60°S America and the 30-60°S Oceania latitudinal bands (Fig. S18 ). Here, we do not consider the Africa charcoal dataset, because southern Africa reaches 33 °S and the density and quality of charcoal records in the African latitudinal band 30-33°S is very low. Furthermore, combining the Global Fire Emissions Database (GFED3;  Giglio et al. , 2010; van der Werf et al. , 2010)    Overall, prior to the LIA, charcoal and ice core proxies (black carbon, ethane, acetylene) indicate stable biomass burning levels in the SH. Our atmospheric history of Antarctic [CO] supports this finding -considering the small changes in the methane and BVOC oxidation CO sources (Sect. 3.
acetylene) datasets  (Nicewonger et al. , 2018 (Nicewonger et al. , , 2020a)). The minimum in the SP [CO] dataset  (Wang et al. , 2010)  was attributed to a decrease in fire emission, using isotopic CO measurements. Charcoal indexes from South America and Oceania areas do not exhibit decreasing trends during the LIA (Fig. 5 ). However, charcoal signals can be influenced by local and small fires (e. g. caused by human activities) that can mask a regional decrease in biomass burning (e. g. , driven by climatic factors). The limited number of charcoal records available also limits the interpretation of charcoal indexes as regional proxies.
Did biomass burning peak at the onset of the industrial period? The CO records (mixing and isotopic ratios) from  Wang et al. (2010)  suggest that biomass burning emissions increased rapidly during the 1700s and 1800s and peaked during the late 19th century at rates roughly 3 times modern levels (defined as the 1997-2016 CE period of global satellite records of biomass burning). On the other hand there is no evidence in the three ice core hydrocarbon records  (Mishler et al. , 2009; Sapart et al. , 2012; Nicewonger et al. , 2018; 2020a) , as well as in the BC Antarctic dataset  (Liu et al. , 2021) , for such a large peak in fire emissions/activity in the late 1800s. The Southern America and Oceania charcoal datasets exhibit opposite patterns at the onset of the industrial period, with increasing fires in Australia, and decreasing biomass burning in Southern America (Fig.
They established a "low PI fire" scenario by scaling the LPJ-LMfire total dry matter consumed to match emissions implied by the charcoal accumulation rates from the Global Charcoal Database  (Power et al. , 2008 (Power et al. , , 2010;; van der Werf et al. , 2010). Such a "low-fire" scenario yields 35 ppbv surface total [CO] at the South Pole in 1770 CE. This value is significantly lower than the SP [CO] of 47±4 ppbv  (Wang et al. , 2010) , but compares well with the 33. 5±5. 0 ppbv reconstructed in this study (Fig. 3 ). More recently,  Rowlinson et al. (2021)  simulated PI [CO] levels using the TOMCAT chemical transport model (which include BVOC chemistry) with CMIP6 fire emission inventory (van der  Marle et al. , 2017). Simulated Antarctic CO concentration using PI CMIP6 emissions in 1750 CE is 37 ppbv, also substantially lower than the  Wang et al.
Acknowledgements. We thank the following for firn air sampling: the late  J. -M. Barnola  ( LGGE ) at  Law Dome  in 1993,  A. Smith  ( ANSTO ) and the late  A. Elcheick  ( Australian Antarctic Division ) at  Law Dome  in 1998,  D. Ferretti  ( NIWA, New Zealand ) at  Law Dome  in 2004,  M. Battle  ( Bowdoin University ),  J. Bastide  ( Bowdoin University ),  J. Butler  ( NOAA ), and  A. Clarke  ( NOAA ) at  South Pole  in 2001, and  D. Spencer  and  P. Krummel  for measurements at  CSIRO GASLAB. Grateful thanks go to  Olivia Maselli ,  Larry Layman ,  Daniel Pasteris ,  Michael Sigl , and other members of the  DRI  team who assisted with the measurement campaigns. We thank  Sophie Szopa  for useful discussions. The French-Italian project SolarIce ( IPEV1145 ,  PNRA16_00008 ) benefited from logistical support from the  French and Italian Polar Agencies, IPEV and PNRA , and the  F2G  for drilling activities at  Concordia Station.
Supplement. A supplement related to this article is available Author contributions. This scientific project was designed by XF, JC, DME, EJB, TB, and MAJC. The high-resolution ice core carbon monoxide measurements were carried out by XF, KF and RHR with support from RG, NJC, and JRM. The firn air [CO] analyses were carried out by RLL, XF, AL and WTS. XF, GT, DME, JC and JF participated in ice core drilling or firn air sampling. The firn air models were developed and implemented by PM and CMT. The codes for data processing were developed by KF, JRM, RLL, PM and XF. Charcoal datasets were processed by BV. All authors contributed to the interpretation of the data. The paper was written by XF with help from all co-authors. Specific methodological sections were written by CMT, PM, and RLL.
https://doi. org/10. 5194/cp-2023-9 Preprint. Discussion started: 21 April 2023 c Author(s) 2023. CC BY 4. 0 License. reproduce methane preferential dissolution, it should also reproduce CO losses related to dissolution. In the case of methane, discrete datasets allow for an external validation of this CFA internal calibration. In this study, we extracted calibration factors for CO from calibration loop experiments for each CFA setup (SI).
, 2013) and averaged over three latitudinal bands: 30-90°S, 45-90°S, and 70-90°S. The 70-90°S latitudinal band encompasses the Antarctic ice sheet. Average [CO] over the 45-90°S, and 70-90°S areas are similar, with levels of 51. 9 and 51. 0 ppbv, respectively. An atmospheric [CO] of 54. 1 ppbv is simulated for the 30-90°S latitudinal band, i. e. about 5% higher than [CO] simulated over Antarctica. These modeling results are in agreement with observations: the annual mean [CO] difference in CSIRO measurements between Kennaook/Cape Grim (at 40. 7° S in Tasmania; Langenfelds et al. , 2023) and Mawson and Casey Stations since 2000 CE is only 2. 2 ppbv, the coastal Antarctic Stations being lower. These results suggest that the absolute CO concentrations derived from our datasets not only are representative of Antarctica, but more widely of the mid-high latitude Southern Hemisphere (45-90°S) atmosphere.
Firn [CO] measurements in the upper 30 m also agree well with the CSIRO model simulations (Fig. 1b) which https://doi. org/10. 5194/cp-2023-9 Preprint. Discussion started: 21 April 2023 c Author(s) 2023. CC BY 4. 0 License. at this depth range are driven by atmospheric observations at Mawson. From this we conclude that the firn and ice samples are not significantly affected by photochemical [CO] production, presumably due to low CO production in Antarctic snow and/or ventilation of produced CO away from the surface snow layer. Finally, annual mean values of the CSIRO atmospheric [CO] record from Mawson Station since 1992 CE are also displayed in Fig. 1e and 1f. These direct measurements of atmospheric [CO] in the Antarctic atmosphere, which use the CSIRO2020 calibration scale, exhibit good agreement with firn air datasets.
in the Antarctic atmosphere in 1350 CE, i. e. a contribution larger than modern fire emissions estimated at 7 ppbv (van der Werf et al. , 2013). The lower [CO] levels revealed by our new CO record are thus in better agreement with the paleofire modeling of van der Werf et al. ( 2013), for the period prior to 1400 CE. https://doi. org/10. 5194/cp-2023-9 Preprint. Discussion started: 21 April 2023 c Author(s) 2023. CC BY 4. 0 License. 3. 5. 3. Evolution of the CO fire source during the LIA Combined continuous CO measurements conducted along the ABN and TD ice cores (supported by the EDML-B40 CO dataset, Sect. SI 2. 4) reveal a decrease in [CO] in the Antarctic atmosphere during the LIA, with a minimum around ~1700 CE. Such a decrease is unique over the last three millennia. A slight decrease in BVOC emissions during the LIA (Acosta et al.
General update In order to update the available evidence on respiratory health effects of outdoor air pollution after the 2017 ERS/ATS statement,  5  it was decided to focus on systematic reviews that also performed a meta-analysis to provide quantitative estimates of the associated public health impact. From an online literature search of PubMed and Embase databases from 2018 to June 2021 using the following search terms 'outdoor air pollution' and 'respiratory health' and 'metaanalysis', 16 articles were retrieved. [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25]  The English language was also an inclusion criterion. After the articles' full-text screening, one study was discarded because it evaluated a non-respiratory outcome,  10  one for considering indoor air exposure only,  16  one for not being a systematic review,  15  and three for not reporting meta-analytic estimates for respiratory health effects.
32, 49  More recently, the study has been enlarged to include data on 25 cities (EPIAIR2) during the period 2006-2010. An immediate effect of PM 10 on natural mortality was found. More relevant and prolonged effects (lag 0-5) were found for PM 2. 5 and NO 2. Increases in cardiac mortality were associated with PM 10 and PM 2. 5 , while exposure to NO 2 as well as PM 10 had an important role in respiratory mortality. 50  Furthermore, the study has analyzed 2,246,448 urgent hospital admissions for non-accidental diseases in 25 Italian cities during the period 2006-2010. A relationship to an increment of 10 mg/m 3 of air pollutants was estimated. Increases in cardiac and respiratory hospitalizations were associated with PM 10 and NO 2. 51  Notably, pollution reduction actions as prescribed by the European Union legislation, i.