scholarly journals Evaluating global emission inventories of biogenic bromocarbons

2013 ◽  
Vol 13 (5) ◽  
pp. 12485-12539 ◽  
Author(s):  
R. Hossaini ◽  
H. Mantle ◽  
M. P. Chipperfield ◽  
S. A. Montzka ◽  
P. Hamer ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Emission Inventories ◽  
Chemical Transport Model ◽  
Absolute Deviation ◽  
Global Emission ◽  
Aircraft Observations ◽  
The Tropics

Abstract. Emissions of halogenated very short-lived substances (VSLS) are poorly constrained. However, their inclusion in global models is required to simulate a realistic inorganic bromine (Bry) loading in both the troposphere, where bromine chemistry perturbs global oxidizing capacity, and in the stratosphere, where it is a major sink for ozone (O3). We have performed simulations using a 3-D chemical transport model (CTM) including three top-down and a single bottom-up derived emission inventory of the major brominated VSLS bromoform (CHBr3) and dibromomethane (CH2Br2). We perform the first concerted evaluation of these inventories, comparing both the magnitude and spatial distribution of emissions. For a quantitative evaluation of each inventory, model output is compared with independent long-term observations at National Oceanic and Atmospheric Administration (NOAA) ground-based stations and with aircraft observations made during the NSF HIAPER Pole-to-Pole Observations (HIPPO) project. For CHBr3, the mean absolute deviation between model and surface observation ranges from 0.22 (38%) to 0.78 (115%) parts per trillion (ppt) in the tropics, depending on emission inventory. For CH2Br2, the range is 0.17 (24%) to 1.25 (167%) ppt. We also use aircraft observations made during the 2011 "Stratospheric Ozone: Halogen Impacts in a Varying Atmosphere" (SHIVA) campaign, in the tropical West Pacific. Here, the performance of the various inventories also varies significantly, but overall the CTM is able to reproduce observed CHBr3 well in the free troposphere using an inventory based on observed sea-to-air fluxes. Finally, we identify the range of uncertainty associated with these VSLS emission inventories on stratospheric bromine loading due to VSLS (BryVSLS). Our simulations show BryVSLS ranges from ~ 4.0 to 8.0 ppt depending on the inventory. We report an optimised estimate at the lower end of this range (~ 4 ppt) based on combining the CHBr3 and CH2Br2 inventories which give best agreement with the compilation of observations in the tropics.

scholarly journals Evaluating global emission inventories of biogenic bromocarbons

2013 ◽  
Vol 13 (23) ◽  
pp. 11819-11838 ◽  
Author(s):  
R. Hossaini ◽  
H. Mantle ◽  
M. P. Chipperfield ◽  
S. A. Montzka ◽  
P. Hamer ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Emission Inventories ◽  
Chemical Transport Model ◽  
Absolute Deviation ◽  
Global Emission ◽  
Aircraft Observations ◽  
The Tropics

Abstract. Emissions of halogenated very short-lived substances (VSLS) are poorly constrained. However, their inclusion in global models is required to simulate a realistic inorganic bromine (Bry) loading in both the troposphere, where bromine chemistry perturbs global oxidising capacity, and in the stratosphere, where it is a major sink for ozone (O3). We have performed simulations using a 3-D chemical transport model (CTM) including three top-down and a single bottom-up derived emission inventory of the major brominated VSLS bromoform (CHBr3) and dibromomethane (CH2Br2). We perform the first concerted evaluation of these inventories, comparing both the magnitude and spatial distribution of emissions. For a quantitative evaluation of each inventory, model output is compared with independent long-term observations at National Oceanic and Atmospheric Administration (NOAA) ground-based stations and with aircraft observations made during the NSF (National Science Foundation) HIAPER Pole-to-Pole Observations (HIPPO) project. For CHBr3, the mean absolute deviation between model and surface observation ranges from 0.22 (38%) to 0.78 (115%) parts per trillion (ppt) in the tropics, depending on emission inventory. For CH2Br2, the range is 0.17 (24%) to 1.25 (167%) ppt. We also use aircraft observations made during the 2011 Stratospheric Ozone: Halogen Impacts in a Varying Atmosphere (SHIVA) campaign, in the tropical western Pacific. Here, the performance of the various inventories also varies significantly, but overall the CTM is able to reproduce observed CHBr3 well in the free troposphere using an inventory based on observed sea-to-air fluxes. Finally, we identify the range of uncertainty associated with these VSLS emission inventories on stratospheric bromine loading due to VSLS (BryVSLS). Our simulations show BryVSLS ranges from ~4.0 to 8.0 ppt depending on the inventory. We report an optimised estimate at the lower end of this range (~4 ppt) based on combining the CHBr3 and CH2Br2 inventories which give best agreement with the compilation of observations in the tropics.

scholarly journals ML-TOMCAT: machine-learning-based satellite-corrected global stratospheric ozone profile data set from a chemical transport model

2021 ◽  
Vol 13 (12) ◽  
pp. 5711-5729
Author(s):  
Sandip S. Dhomse ◽  
Carlo Arosio ◽  
Wuhu Feng ◽  
Alexei Rozanov ◽  
Mark Weber ◽  
...  
Keyword(s):  
Transport Model ◽  
Stratospheric Ozone ◽  
Chemical Transport ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Profile Data ◽  
Data Set ◽  
Ozone Profile ◽  
Satellite Instruments

Abstract. High-quality stratospheric ozone profile data sets are a key requirement for accurate quantification and attribution of long-term ozone changes. Satellite instruments provide stratospheric ozone profile measurements over typical mission durations of 5–15 years. Various methodologies have then been applied to merge and homogenise the different satellite data in order to create long-term observation-based ozone profile data sets with minimal data gaps. However, individual satellite instruments use different measurement methods, sampling patterns and retrieval algorithms which complicate the merging of these different data sets. In contrast, atmospheric chemical models can produce chemically consistent long-term ozone simulations based on specified changes in external forcings, but they are subject to the deficiencies associated with incomplete understanding of complex atmospheric processes and uncertain photochemical parameters. Here, we use chemically self-consistent output from the TOMCAT 3-D chemical transport model (CTM) and a random-forest (RF) ensemble learning method to create a merged 42-year (1979–2020) stratospheric ozone profile data set (ML-TOMCAT V1.0). The underlying CTM simulation was forced by meteorological reanalyses, specified trends in long-lived source gases, solar flux and aerosol variations. The RF is trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set over the time periods of the Microwave Limb Sounder (MLS) from the Upper Atmosphere Research Satellite (UARS) (1991–1998) and Aura (2005–2016) missions. We find that ML-TOMCAT shows excellent agreement with available independent satellite-based data sets which use pressure as a vertical coordinate (e.g. GOZCARDS, SWOOSH for non-MLS periods) but weaker agreement with the data sets which are altitude-based (e.g. SAGE-CCI-OMPS, SCIAMACHY-OMPS). We find that at almost all stratospheric levels ML-TOMCAT ozone concentrations are well within uncertainties of the observational data sets. The ML-TOMCAT (V1.0) data set is ideally suited for the evaluation of chemical model ozone profiles from the tropopause to 0.1 hPa and is freely available via https://doi.org/10.5281/zenodo.5651194 (Dhomse et al., 2021).

scholarly journals Modelling of organic aerosols over Europe (2002–2007) using a volatility basis set (VBS) framework with application of different assumptions regarding the formation of secondary organic aerosol

2012 ◽  
Vol 12 (2) ◽  
pp. 5425-5485 ◽  
Author(s):  
R. Bergström ◽  
H. A. C. Denier van der Gon ◽  
A. S. H. Prévôt ◽  
K. E. Yttri ◽  
D. Simpson
Keyword(s):  
Observational Studies ◽  
Transport Model ◽  
Organic Aerosol ◽  
Basis Set ◽  
Emission Inventories ◽  
Chemical Transport Model ◽  
Model Studies ◽  
Primary Emissions ◽  
Different Sources

Abstract. A new organic aerosol (OA) module has been implemented into the EMEP chemical transport model. Four different volatility basis set (VBS) schemes have been tested in long-term simulations for Europe, covering the six years 2002–2007. Different assumptions regarding partitioning of primary OA (POA) and aging of POA and secondary OA (SOA), have been explored. Model results are compared to filter measurements, AMS-data and source-apportionment studies, as well as to other model studies. The present study indicates that many different sources contribute significantly to OA in Europe. Fossil POA and oxidised POA, biogenic and anthropogenic SOA (BSOA and ASOA), residential burning of biomass fuels and wildfire emissions may all contribute more than 10% each over substantial parts of Europe. Simple VBS based OA models can give reasonably good results for summer OA but more observational studies are needed to constrain the VBS parameterisations and to help improve emission inventories. The volatility distribution of primary emissions is an important issue for further work. This study shows smaller contributions from BSOA to OA in Europe than earlier work, but relatively greater ASOA. BVOC emissions are highly uncertain and need further validation. We can not reproduce winter levels of OA in Europe, and there are many indications that the present emission inventories substantially underestimate emissions from residential wood burning in large parts of Europe.

scholarly journals Impact of different emission inventories on simulated tropospheric ozone over China: a regional chemical transport model evaluation

2004 ◽  
Vol 4 (1) ◽  
pp. 507-532 ◽  
Author(s):  
J. Ma ◽  
J. A. van Aardenne
Keyword(s):  
Tropospheric Ozone ◽  
Emission Inventory ◽  
Transport Model ◽  
Chemical Transport ◽  
Dominant Factor ◽  
Emission Inventories ◽  
Chemical Transport Model ◽  
Model Simulations ◽  
The Impact ◽  
Surface O3

Abstract. The importance of emission inventory uncertainty on the simulation of summertime tropospheric Ozone over China has been analyzed using a regional chemical transport model. Three independent emissions inventories, that are (i) emission estimates from the Emission Database for Global Atmospheric Research (EDGAR) for the year 1995, (ii) a regional emission inventory used in the Transport and Chemical Evolution over the Pacific (TRACE-P) program with emissions for the year 2000 and (iii) a national emission inventory used in the China Ozone Research Program (CORP) with emission estimates for the year 1995, are used for model simulation over a summer period. Methods used for the development of the inventories are discussed and differences in simulated ozone and its precursors with these emission inventories are analyzed. Comparison of the emission inventories revealed large differences in the emission estimates (up to 50% for NOx, ~100% for NMVOC and ~1000% for CO). Application of the different emission inventories in three model simulations showed minor differences in both surface O3 in rather unpolluted areas in China and at higher altitudes (500 mbar). In polluted areas, differences in surface O3 are 30-50% between the different model simulations which seems rather small taking into account the large differences in the emission inventories. Additional sensitivity runs showed that the difference in NOx emissions as well NMVOC emissions is a dominant factor which controls the differences in simulated O3 concentrations while the impact of differences in CO emissions is relatively small. Although the CO emission estimate by CORP seems to be underestimated, there is no confidence to highlight one emission inventory better than the others.

scholarly journals New Observations of Upper Tropospheric NO<sub>2</sub> from TROPOMI

2020 ◽  
Author(s):  
Eloise A. Marais ◽  
John F. Roberts ◽  
Robert G. Ryan ◽  
Henk Eskes ◽  
K. Folkert Boersma ◽  
...  
Keyword(s):  
Transport Model ◽  
Polar Regions ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Mauna Loa ◽  
Mixing Ratios ◽  
Spatial Coverage ◽  
Aircraft Observations ◽  
The Tropics ◽  
Improve Representation

Abstract. Nitrogen oxides (NOx ≡ NO + NO2) in the NOx-limited upper troposphere (UT) are long-lived and so have a large influence on the oxidizing capacity of the troposphere and formation of the greenhouse gas ozone. Models misrepresent NOx in the UT and observations to address deficiencies in models are sparse. Here we obtain a year of near-global seasonal mean mixing ratios of NO2 in the UT (450–180 hPa) at 1 ° x 1° by applying cloud-slicing to partial columns of NO2 from TROPOMI. This follows refinement of the cloud-slicing algorithm with synthetic partial columns from the GEOS-Chem chemical transport model. We find that synthetic cloud-sliced UT NO2 are spatially consistent (R = 0.64) with UT NO2 calculated across the same cloud pressure range and scenes as are cloud-sliced (“true” UT NO2), but the cloud-sliced UT NO2 is 11–22 % more than the "true" all-sky seasonal mean. The largest contributors to differences between synthetic cloud-sliced and “true” UT NO2 are target resolution of the cloud-sliced product and uniformity of overlying stratospheric NO2. TROPOMI, prior to cloud-slicing, is corrected for a 13 % underestimate in stratospheric NO2 variance and a 50 % overestimate in free tropospheric NO2 determined by comparison to Pandora total columns at high-altitude sites in Mauna Loa, Izaña and Altzomoni, and MAX-DOAS and Pandora tropospheric columns at Izaña. Two cloud-sliced seasonal mean UT NO2 products for June 2019 to May 2020 are retrieved from corrected TROPOMI total columns using distinct TROPOMI cloud products that assume clouds are reflective boundaries (FRESCO-S) or water droplet layers (ROCINN-CAL). TROPOMI UT NO2 typically ranges from 20-30 pptv over remote oceans to > 80 pptv over locations with intense seasonal lightning. Spatial coverage is mostly in the tropics and subtropics with FRESCO-S and extends to the midlatitudes and polar regions with ROCINN-CAL, due to its greater abundance of optically thick clouds and wider cloud top altitude range. TROPOMI UT NO2 seasonal means are spatially consistent (R = 0.6–0.8) with an existing coarser spatial resolution (5° latitude x 8° longitude) UT NO2 product from the Ozone Monitoring Instrument (OMI). UT NO2 from TROPOMI is 12–26 pptv more than that from OMI due to increase in NO2 with altitude from the OMI pressure ceiling (280 hPa) to that for TROPOMI (180 hPa), but possibly also systematic altitude differences between the TROPOMI and OMI cloud products. The TROPOMI UT NO2 product offers potential to evaluate and improve representation of UT NOx in models and supplement aircraft observations that are sporadic and susceptible to large biases in the UT.

scholarly journals Stratospheric impact on tropospheric ozone variability and trends: 1990–2009

2013 ◽  
Vol 13 (2) ◽  
pp. 649-674 ◽  
Author(s):  
P. G. Hess ◽  
R. Zbinden
Keyword(s):  
Tropospheric Ozone ◽  
Large Scale ◽  
Transport Model ◽  
Spatial Scales ◽  
Stratospheric Ozone ◽  
Atmospheric Model ◽  
Chemical Transport Model ◽  
Ozone Trends ◽  
Environmental Prediction

Abstract. The influence of stratospheric ozone on the interannual variability and trends in tropospheric ozone is evaluated between 30 and 90° N from 1990–2009 using ozone measurements and a global chemical transport model, the Community Atmospheric Model with chemistry (CAM-chem). Long-term measurements from ozonesondes, at 150 and 500 hPa, and the Measurements of OZone and water vapour by in-service Airbus aircraft programme (MOZAIC), at 500 hPa, are analyzed over Japan, Canada, the Eastern US and Northern and Central Europe. The measurements generally emphasize northern latitudes, although the simulation suggests that measurements over the Canadian, Northern and Central European regions are representative of the large-scale interannual ozone variability from 30 to 90° N at 500 hPa. CAM-chem is run with input meteorology from the National Center for Environmental Prediction; a tagging methodology is used to identify the stratospheric contribution to tropospheric ozone concentrations. A variant of the synthetic ozone tracer (synoz) is used to represent stratospheric ozone. Both the model and measurements indicate that on large spatial scales stratospheric interannual ozone variability drives significant tropospheric variability at 500 hPa and the surface. In particular, the simulation and the measurements suggest large stratospheric influence at the surface sites of Mace Head (Ireland) and Jungfraujoch (Switzerland) as well as many 500 hPa measurement locations. Both the measurements and simulation suggest the stratosphere has contributed to tropospheric ozone trends. In many locations between 30–90° N 500 hPa ozone significantly increased from 1990–2000, but has leveled off since (from 2000–2009). The simulated global ozone budget suggests global stratosphere-troposphere exchange increased in 1998–1999 in association with a global ozone anomaly. Discrepancies between the simulated and measured ozone budget include a large underestimation of measured ozone variability and discrepancies in long-term stratospheric ozone trends. This suggests the need for more sophisticated simulations including better representations of stratospheric chemistry and circulation.

scholarly journals Impact of different emission inventories on simulated tropospheric ozone over China: a regional chemical transport model evaluation

2004 ◽  
Vol 4 (4) ◽  
pp. 877-887 ◽  
Author(s):  
J. Ma ◽  
J. A. van Aardenne
Keyword(s):  
Tropospheric Ozone ◽  
Emission Inventory ◽  
Transport Model ◽  
Chemical Transport ◽  
Dominant Factor ◽  
Emission Inventories ◽  
Chemical Transport Model ◽  
Model Simulations ◽  
The Impact ◽  
Surface O3

Abstract. The importance of emission inventory uncertainty on the simulation of summertime tropospheric ozone over China has been analyzed using a regional chemical transport model. Three independent emissions inventories, that are (i) emission estimates from the Emission Database for Global Atmospheric Research (EDGAR) for the year 1995, (ii) a regional emission inventory used in the Transport and Chemical Evolution over the Pacific (TRACE-P) program with emissions for the year 2000 and (iii) a national emission inventory used in the China Ozone Research Program (CORP) with emission estimates for the year 1995, are used for model simulation over a summer period. Methods used for the development of the inventories are discussed and differences in simulated ozone and its precursors with these emission inventories are analyzed. Comparison of the emission inventories revealed large differences in the emission estimates (up to 50% for NOx, ~100% for NMVOC and ~1000% for CO). Application of the different emission inventories in three model simulations showed minor differences in both surface O3 in rather unpolluted areas in China and at higher altitudes (500mbar). In polluted areas, differences in surface O3 are 30-50% between the different model simulations which seem rather small taking into account the large differences in the emission inventories. Additional sensitivity runs showed that the difference in NOx emissions as well NMVOC emissions is a dominant factor which controls the differences in simulated O3 concentrations while the impact of differences in CO emissions is relatively small. Although the CO emission estimate by CORP seems to be underestimated, there is no confidence to highlight one emission inventory better than the others.

Machine-Learning-Based Satellite-Corrected Global Stratospheric Ozone Profile Dataset from a Chemical Transport Model

2021 ◽  
Author(s):  
Sandip Dhomse ◽  
Martyn Chipperfield
Keyword(s):  
Machine Learning ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Chemical Transport ◽  
Recovery Phase ◽  
Horizontal Resolution ◽  
Chemical Transport Model ◽  
High Quality ◽  
Ozone Profile

&lt;p&gt;High quality global ozone profile datasets are necessary to monitor changes in stratospheric ozone. Hence, various methodologies have been used to merge and homogenise different satellite datasets in order to create long-term observation-based ozone profile datasets with minimal data gaps. However, individual satellite instruments use different measurement methods and retrieval algorithms that complicate the merging of these different datasets. Furthermore, although atmospheric chemical models are able to simulate chemically consistent long-term datasets, they are prone to the deficiencies associated with the computationally expensive processes that are generally represented by simplified parameterisations or uncertain parameters.&lt;/p&gt;&lt;p&gt;Here, we use chemically consistent output from a 3-D Chemical Transport Model (CTM, TOMCAT) and an ensemble of three machine learning (ML) algorithms (Adaboost, GradBoost, Random Forest), to create a 42-year (1979-2020) stratospheric ozone profile dataset. The ML algorithms are primarily trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) dataset by selecting the UARS-MLS (1992-1998) and AURA-MLS (2005-2019) time periods. This ML-corrected version of monthly mean zonal mean TOMCAT (hereafter ML-TOMCAT) ozone profile data is available at both pressure (1000 hPa - 1 hPa) and geometric height (surface to 50 km) levels at about 2.5 degree horizontal resolution.&lt;/p&gt;&lt;p&gt;We will present a detailed evaluation of ML-TOMCAT profiles against range of merged satellite datasets (e.g. GOZCARDS, SAGE-CCI-OMPS, and BVertOzone) as well high quality solar occultation observations (e.g. SAGE-II v7.0 (1984-2005), HALOE v19 (1991-2005) and ACE v4.1 (2004-2020). Overall, ML-TOMCAT shows good agreement with the evaluation datasets but with poorer agreement at low latitudes. We also show that, as in different merged satellite data sets, ML-algorithms show larger spread in the tropical middle stratosphere. Finally, we will present a trend analysis from TOMCAT and ML-TOMCAT profiles for the post-1998 ozone recovery phase.&lt;/p&gt;

scholarly journals ML-TOMCAT: Machine-Learning-Based Satellite-Corrected Global Stratospheric Ozone Profile Dataset from a Chemical Transport Model

2021 ◽  
Author(s):  
Sandip S. Dhomse ◽  
Carlo Arosio ◽  
Wuhu Feng ◽  
Alexei Rozanov ◽  
Mark Weber ◽  
...  
Keyword(s):  
Transport Model ◽  
Stratospheric Ozone ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Vertical Coordinate ◽  
Ozone Profile ◽  
Minimal Data ◽  
Almost All ◽  
Satellite Instruments

Abstract. High quality stratospheric ozone profile datasets are a key requirement for accurate quantification and attribution of long-term ozone changes. Satellite instruments obtain stratospheric ozone profile measurements over typical mission durations of 5–15 years. Various methodologies have then been applied to merge and homogenise the different satellite data in order to create longer term observation-based ozone profile datasets with minimal data gaps. However, individual satellite instruments use different measurement methods, sampling patterns and retrieval algorithms which complicate the merging of these different datasets. In contrast, atmospheric chemical models can produce chemically consistent long-term ozone simulations based on specified changes in external forcings, but they are subject to the deficiencies associated with incomplete understanding of complex atmospheric processes and uncertain photochemical parameters. Here, we use chemically self-consistent output from the TOMCAT 3-D chemical transport model (CTM) and a Random-Forest (RF) ensemble learning method to create a merged 42-year (1979–2020) stratospheric ozone profile dataset (ML-TOMCAT V1.0). The underlying CTM simulation was forced by meteorological reanalyses, specified trends in long-lived source gas, solar flux and aerosol variations. The RF is trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) dataset over the time periods of the Microwave Limb Sounder (MLS) from the Upper Atmosphere Research Satellite (UARS) (1991–1998) and Aura (2005–2016) missions. We find that ML-TOMCAT shows excellent agreement with available independent satellite-based datasets which use pressure as the vertical coordinate (e.g. GOZCARDS, SWOOSH for non-MLS periods) but weaker agreement with the datasets which are height-based (e.g. SAGE–CCI–OMPS, SCIAMACHY-OMPS). We find that at almost all stratospheric levels ML-TOMCAT ozone concentrations are well within uncertainties in the observational datasets. The ML-TOMCAT dataset is thus ideally suited for the evaluation of model ozone profiles from the tropopause to 0.1 hPa. ML-TOMCAT data is freely available via https://zenodo.org/record/4997959#.YNzleUlKiUk (Dhomse et al., 2021).

Record springtime stratospheric ozone depletion at 80°N in 2020

2021 ◽  
Author(s):  
Ramina Alwarda ◽  
Kristof Bognar ◽  
Kimberly Strong ◽  
Martyn Chipperfield ◽  
Sandip Dhomse ◽  
...  
Keyword(s):  
Ozone Depletion ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Polar Vortex ◽  
The Arctic ◽  
Optical Absorption Spectroscopy ◽  
Chemical Transport Model ◽  
Polar Stratospheric Clouds ◽  
Ozone Loss ◽  
Stratospheric Clouds

&lt;p&gt;The Arctic winter of 2019-2020 was characterized by an unusually persistent polar vortex and temperatures in the lower stratosphere that were consistently below the threshold for the formation of polar stratospheric clouds (PSCs). These conditions led to ozone loss that is comparable to the Antarctic ozone hole. Ground-based measurements from a suite of instruments at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Canada (80.05&amp;#176;N, 86.42&amp;#176;W) were used to investigate chemical ozone depletion. The vortex was located above Eureka longer than in any previous year in the 20-year dataset and lidar measurements provided evidence of polar stratospheric clouds (PSCs) above Eureka. Additionally, UV-visible zenith-sky Differential Optical Absorption Spectroscopy (DOAS) measurements showed record ozone loss in the 20-year dataset, evidence of denitrification along with the slowest increase of NO&lt;sub&gt;2&lt;/sub&gt; during spring, as well as enhanced reactive halogen species (OClO and BrO). Complementary measurements of HCl and ClONO&lt;sub&gt;2&lt;/sub&gt; (chlorine reservoir species) from a Fourier transform infrared (FTIR) spectrometer showed unusually low columns that were comparable to 2011, the previous year with significant chemical ozone depletion. Record low values of HNO&lt;sub&gt;3&lt;/sub&gt; in the FTIR dataset are in accordance with the evidence of PSCs and a denitrified atmosphere. Estimates of chemical ozone loss were derived using passive ozone from the SLIMCAT offline chemical transport model to account for dynamical contributions to the stratospheric ozone budget.&lt;/p&gt;

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