Ambra1+/gt (autophagy/beclin-1 regulator 1+/gt) mice we analysed the contribution of autophagy deficiency on retinal ganglion cell survival in an age dependent context. Interestingly, old Ambra1+/gt mice showed decreased RGC survival after optic nerve crush in comparison to old Ambra1+/+, an effect that was not observed in the young animals. Proteomics and mRNA expression data point towards altered oxidative stress response and mitochondrial alterations in old Ambra1+/gt animals. This effect is intensified after RGC axonal damage, resulting in reduced oxidative stress response showing decreased levels of Nqo1, as well as failure of Nrf2 induction in the old Ambra1+/gt. Old Ambra1+/gt also failed to show increase in Bnip3l and Bnip3 expression after optic nerve crush, a response that is found in the Ambra1+/+ controls. Primary RGCs derived from Ambra1+/gt mice show decreased neurite projection and increased levels of apoptosis in comparison to Ambra1+/+ animals. Our results lead to the conclusion that oxidative stress response pathways are altered in old Ambra1+/gt mice leading to impaired damage responses upon additional external stress factors.Glaucoma is a common age-related disease leading to progressive retinal ganglion cell (RGC) death, visual field defects and vision loss and is the second leading cause of blindness in the elderly worldwide. Mitochondrial dysfunction and impaired autophagy have been linked to glaucoma and induction of autophagy shows neuroprotective effects in glaucoma animal models. We have shown that autophagy decreases with aging in the retina and that autophagy can be neuroprotective for RGCs, but it is currently unknown how aging and autophagy deficiency impact RGCs susceptibility and survival. Using the optic nerve crush model in young and olWelcome@1234d  The risk for developing glaucoma increases with age and prevalence rapidly rises after the age of 40 years1. Next to the clinically most relevant risk factors such as increased intraocular pressure and ageing, one major factor associated with RGC death in glaucoma is mitochondrial dysfunction, which was recently confirmed in a proteomics study analysing human retinal post-mortem glaucoma samples4.Glaucoma are a group of diseases leading to progressive optic nerve damage and accompanying visual field loss, caused by retinal ganglion cell (RGC) death. This multifactorial, neurodegenerative disease is one of the leading causes for blindness and although estimating worldwide prevalence for all glaucoma cases is challenging, we know that glaucoma will affect at least 111.8 million people by the year 20405. During autophagy the material targeted for degradation is packed into a double membrane structure, the autophagosome, which then can fuse with the lysosome for cargo degradation6. Not only soluble cell fractions such as proteins are degraded via autophagy, but also organelles, such as mitochondria, during selective autophagy. In this process cargo receptors and adaptors determine specificity for organelles and other cargo for degradation7. Autophagy levels decline with age in many tissues including the brain11 which contributes to the pathogenesis of various, if not all age-related neurodegenerative diseases14. Our data in the aging retina also supports this notion and we find decreased mRNA expression of several autophagy regulators such as Atg7 and Beclin1 that results in decreased autophagy flux from 12 months of age onwards in the mouse retina11. Other studies have demonstrated the importance of autophagy for proper neuronal development and embryonic survival16. Programmed cell clearance in early stages of retinal development is dependent on autophagy17 and we have shown that mitophagy is important for RGC development, leading to the metabolic shift towards glycolysis which is essential for retinal ganglion cell neurogenesis18. Genetic studies show a link between glaucoma and autophagy related genes19. Of the genes that have been found associated with glaucoma in genome-wide association studies (GWAS) studies Optn20, Tbk121, and Opa-124 play a role in mitochondrial function and also in mitophagy pathways28. Interestingly, these genes are supposed to play a role in normal tension glaucoma (NTG) rather than primary open angle glaucoma (POAG), which is, in contrast to NTG, associated with elevated intraocular pressure. Approximately 30–40% of glaucoma patients suffer from NTG29.Autophagy is an important cell catabolic pathway necessary for the recycling of intracellular components via their delivery to the lysosomeAmbra1+/gt mice. AMBRA1 (autophagy/beclin-1 regulator 1) plays a role in the initiation of the autophagy process30. It also is a relevant mitophagy receptor that can act in a PINK1/PARKIN dependent and independent way33. Ambra1gt/gt mice display embryonic lethality at E10–E14.5 associated with significant neural tube defects30. Ambra1+/gt animals have been used as a model of subtle autophagy deficiency in many studies including our own, where we show alterations in differentiation of neural stem cells34. In this study we find that aged Ambra1+/gt mice have increased susceptibility to axonal insult in vivo in a model of optic nerve crush (ONC). Proteomic analysis shows mitochondrial alterations and changes in the oxidative stress response in the Ambra1+/gt animals that could increase the susceptibility to RGC damage.In this study we analysed the effect of ageing and autophagy deficiency on RGC survival using Ambra1+/+ as well as Ambra1gt/+ mice with a CD1 background were used for these experiments. The ratio male/female in all experiments was 1:1 and we could not detect any apparent changes in behaviour of the female mice in our colony. Animals were housed, cared for and euthanized in accordance with European Union guidelines and experiments were approved by the CIB ethics committee for animal experimentation. The mice were housed in a 12 h/12 h light/dark environment and fed ad libitum. AMBRA1 mutant mice were provided by Francesco Cecconi, University of Rome Tor Vergata30. The animals were genotyped by processing tail bud tissue. DNA was isolated from tissue using the NzyTech gDNA Isolation kit (NZYTech) and PCR was performed as previously described30. In preparation for the ONC the mice were anaesthetised with a weight adapted intraperitoneal (i.p.) injection of 80 mg/kg ketamine chlorhydrate solution  and 10 mg/kg 2% xylacine chlorhydrate . For surgery, the body temperature of the animals was maintained by placing them on a 37.5 °C heating platform.5–6 months (young) and 12–14 months (old) ONC was performed on the left eye. Using 2.5 mm Vannas Spring Scissors (Fine Science Tools), the conjunctiva and tenon was opened from the 1 o’clock to the 3 o’clock position. By slightly rotating the eyeball nasally and using fine forceps the optic nerve was carefully exposed. Using self-closing negative action tweezers  the optic nerve was crushed for 7 s at a site between 1 and 2 mms behind the globe. During surgery both eyes were moisturised with artificial eye drops, which was continued on the non-surgery eye until the animals woke up. After surgery Ofloxacin eye ointment was applied to the left, surgery eye and all mice received an intraperitoneal injection of Buprenorphine . Depending on the experiment, the mice were sacrificed 3, 4, 7, or 10 days after the ONC (indicated for each experiment) via cervical dislocation after a brief isoflurane sedation.35. For RGC counts, the flatmounts were stained for Gamma-Synuclein  and Calbindin  over night at 4 °C in a humid chamber. Brn3a staining in the cryosections was performed as previously published36. To stain RGCs with Brn3a in the cryosections, the sections were re-fixed with 4% PFA for 10 min, washed 3× with PBS for 10 min, then treated with 10 mM citrate buffer pH 6.0, heated in the microwave, and subsequently permeabilized with 1% Triton 4 × 20 min. After washing, the sections were blocked with BGT  for 1 h and then the primary antibody  was incubated over night at 4 °C. The following day, appropriate secondary antibodies  were incubated for 1 h at RT. The flatmounts were mounted in Fluoromount-G  with DAPI 1:1000 .The eyes were enucleated after cervical dislocation. For flatmount preparation, the eyes were opened through the cornea, the lens and vitreous body were extracted. Four petal cuts were performed in the retina, which was then mounted on nitrocellulose with the photoreceptors facing down. After fixing in 4% PFA 1 h at RT and washing with PBS, half of the flatmount was used for RGC counts and the other half of the retina was embedded in OCT and cryosections were prepared as previously describedPictures of the ganglion cell layer of the flatmounts as well as the cryosections were taken with a confocal microscope . Masked cell counting was performed using the Image J software  on maximal confocal projections. For the flatmounts 4–6 fields per half retina were acquired with a X63 objective. Hereby the cells only stained with Gamma-Synuclein were accounted as RGCs. For the Brn3a staining in the cryosections 12–16 pictures from eight sections covering all regions of the eye were taken per retina.Ambra1+/gt and Ambra1+/+ 3 and 7 days after ONC (n = 4–5 per group). Total RNA from retinas was extracted using TRIzol reagent (Invitrogen), and reverse transcription performed using the High‐Capacity cDNA Reverse Transcription Kit  according to the manufacturer’s instructions. Quantitative real‐time PCR was performed with 10 ng cDNA in a Light Cycler® 480 Instrument  with LightCycler® 480 probes master mix  using Taqman assays . TaqMan Gene expression arrays for Mfn2 (Mm00500120_m1), Optn (Mm01333245_m1), Park2 (Mm00450187_m1), Pink1 (Mm00550827_m1), Gpx1 (Mm00656767_g1), Nqo1 (Mm01253561_m1), Bnip3 (Mm01275600_g1), Bnip3l (Mm00786306_s1), Nfe2l2 (Mm00477784_m1), Becn1 (Mm01265461_m1). Assays were performed in duplicate, and results were normalised according to expression levels of 18s RNA (Hs99999901_s). Ratios were calculated using the contralateral eye.Retinal mRNA levels were measured from 13-month-old Ambra1+/gt and Ambra1+/+ animals were isolated and stored at −80 °C until further use (n = 6). Homogenisation and further handling of the tissue was performed as previously described in detail37. Briefly, the retinae were homogenised in lysis buffer  using a Precellys 24 homogeniser with 1.4 and 2.8 mm ceramic balls. Afterwards, the retinal homogenate was exchanged into 300 µl phosphate-buffered saline (PBS) using an Amicon 3 kDa centrifugal filter device . Protein concentration was determined with a BCA protein assay kit  according to manufacturer’s instructions and measured with a Multiscan Ascent photometer  at a wavelength of 570 nm. For the SDS gel protein separation, 2 retinas were pooled (resulting in n = 3 for WT and HT) and 50 µg of each pooled sample was loaded per lane and separated with 10-well NuPAGE 12% Bis–Tris minigels  under reducing conditions. In gel tryptic digestion was performed as described in detail previously and SOLAµTM HRP Spin plates were used for peptide purification prior to LC-MS/MS analysis with a Rheos Allegro Pump downscaling to a capillary HPLC system and coupled to a hybrid linear ion trap-Orbitrap MS system . Elution gradient of the HPLC and MS-specific parameters are described elsewhere in detail38. Parameters used for elution gradient and MS parameters were applied as described previously40. Data analysis was performed using Perseus software package version 1.6.5.041. LFQ intensities were log2 transformed and ANOVA was performed. For protein interaction analysis STRING software version 11.0 was used.Retinae from 13-month old Ambra1+/gt and Ambra1+/+ littermates were used to isolate RGCs. The eyes were extracted and the retina isolated. The retina was dissociated using the Papain kit from Worthington (PDS LK003150l). Then 25,000 retinal cells were incubated in 96-well plates , pre-incubated with poly-l-lysine and laminin, with neurobasal A  medium containing 2% B27 , 0.5% gentamicin , 0.25% l-glutamine . Cells were incubated up to 3 days. Light microscopic pictures were taken after 1 and 3 days in vitro (DIV) and axonal neurites were measured manually in masked pictures. Five images were taken per well (n = 15 per time point). DAPI  staining was performed to determine the total number of cells as well as the number of apoptotic nuclei, which were assessed for each condition in a masked manner. Neuronal Class III Beta-Tubulin (TUJ1)  staining was performed to analyse the % of RGCs in the culture.Postnatal day 1 (P1) p-values < 0.05 were estimated to be statistically significant. Graphs were performed with GraphPad Prism (Version 8.3.1) and represent ± SD or ± SEM (indicated in the figure legends).Prism *Version 8.3.19 was used for statistical analysis. Mann–Whitney tests or Krusak-Wallis ANOVA were performed. Ambra1+/gt animals and Ambra1+/+ littermate controls were subject to ONC, as AMBRA1 is involved in autophagy induction and serves as a mitophagy receptor. After ONC, the left eye was assessed at different times point after injury. To determine the number of RGCs, both the right and the left retina were flatmounted and stained with Gamma-Synuclein and Calbindin. Gamma-Synuclein staining serves as robust RGC marker in control and damage conditions42, however also stains displaced amacrine cells43. Although Gamma-Synuclein staining appears weaker in displaced amacrine cells, and therefore could be distinguished, Calbindin staining was used to identify these cells. Cells only stained for Gamma-Synuclein were counted as RGC. As expected, we found a steady, significant decrease of RGCs after ONC, Fig. Ambra1+/+ and Ambra1+/gt 7 days after ONC. When comparing young Ambra1+/+ and Ambra1+/gt, we found a significant decrease in RGCs after ONC in both groups but no difference in amount of RGC loss Fig. Ambra1+/gt animals than in the Ambra1+/+ mice, Fig. Ambra1+/gt animals after ONC in comparison to Ambra1+/+, Fig. The ONC is a model to mimic RGC death through IOP independent optic nerve damage. It therefore relates more to glaucoma without elevated eye pressure than POAG. As NTG has been linked to genes involved in autophagy and mitophagy, and is an age-related disease, we aimed to detect changes in RGC loss after ONC depending on age and autophagy impairment. For this, Ambra1+/gt and Ambra1+/+ animals, we wanted to explore the molecular players governing this interesting differential RGC survival between these two animal groups. Applying a bottom-up proteomic approach using a HPLC- LTQ Orbitrap XL MS setup, we aimed to understand relevant proteomic changes between old Ambra1+/gt and Ambra1+/+. We identified 1272 proteins in the retinae of the 13-month-old animals, using a false discovery rate <1% as filtering criteria. Seventy-one proteins were significantly differently regulated in Ambra1+/gt in comparison to Ambra1+/+ animals, Fig. Ambra1+/gt animals, Fig. p-value:10.0E−04), including significantly decreased ATP6V1A expression, Suppl. Fig. 45 and has been linked to the regulation of lysosomal acidification via ATP6V1A.As we found differences between RGC survival in old 47,we performed qPCR analysis studying Nfe2l2 , and its downstream factors Nqo1 (NAD(P)H Quinone Dehydrogenase 1) and Gpx1 (Glutathione peroxidase 1) in the retinae 3 and 7 days after ONC in Ambra1+/+ and Ambra1+/gt animals compared to the contralateral control eyes. Nfe2l2 showed a significant increase 7 days after ONC in Ambra1+/+ animals, whereas the expression levels were not altered in the Ambra1+/gt animals, Fig. Gpx1 3 days after ONC in the Ambra1+/gt animals, however lower levels 7 days after ONC, Fig. Ambra1+/gt mice have an impaired retinal oxidative stress response after RGC damage.As oxidative stress and mitochondrial damage were the main pathways altered, we next decided to follow up in this pathway. Given the reported connections between NFE2L2, mitochondria disfunction and oxidative stress response48 and in animal models of this disease, including ONC49. Our data also shows that Ambra1+/+ animals, but not the Ambra1+/gt respond to these levels of oxidative stress by increasing the expression of the master antioxidant regulator Nrf2. These observations suggest a loop where increased ROS could exacerbate mitochondrial damage in the absence of an adequate antioxidant response after autophagy deficiency. Another pathway that protects cells against ROS is the elimination of whole damaged mitochondria via autophagy during mitophagy51. Several lines of evidence suggest that AMBRA1 is a mitophagy receptor that can act in both PINK1/PARKIN dependent and independent pathways32. While some studies have found mitophagy events in RGCs after optic nerve transection36 it is currently unknown how this pathway affects RGCs survival and which mitophagy regulators could be playing a role. Therefore, we decided to assess mRNA expression of several mitophagy regulators after ONC. Seven days after ONC we could detect an increase in Bnip3l and Bnip3 in the Ambra1+/+ animals, that was not observed in the Ambra1+/gt, Fig. Ambra1+/gt did not show any changes of mitophagy regulators 3 or 7 days after ONC, Fig. Optn1, Park2, Pink1, and Mfn2 showed no changes. Interestingly, when we assessed the mRNA expression in the non-injured eye, we found that Ambra1+/gt mice already displayed increased mRNA expression of both Bnip3l, Nrf2 and Mfn2 , which do not display any apparent phenotype at this age. Mitochondrial alterations with impaired stress related mitophagy induction and altered oxidative stress response could play a role in the increased RGC susceptibility in the old Ambra1+/gt animals. This is supported by our proteomic data as well as mRNA transcription for mitochondrial and oxidative stress genes. Our in vitro data additionally suggest a role for AMBRA1 in RGC survival and neurite outgrowth.In this study we have demonstrated an age dependent decrease in RGC survival after ONC in the Ambra1+/gt in comparison to Ambra1+/+ littermates and to the young experimental groups. We can rule out a general age-related decline in RGC survival, as the old Ambra1+/+ did not show any changes in RGC loss after ONC in comparison to the young Ambra1+/+. Only few studies have analysed age related RGC susceptibility after ONC however, reduced RGC numbers after ONC has been shown for older animals, such as a study showing increased RGC damage after ONC for 24-month-old mice in comparison to young animals52. Regarding Ambra1+/gt no studies have been performed analysing the aging-related phenotype, but we did not observe differences in the number of RGCs in non-injured retinas (data not shown). Recent studies, however, have revealed that female Ambra1+/gt mice have some autistic features, but these are already apparent in young animals. Some of the analysed changes in the young animals however showed a slightly different characteristic in the middle aged mice, such as the form of induced seizures54, pointing towards a possible age related change. In our study we used a female to male ratio of 1:1 with an outbred CD1 background, whereas the studies showing autistic features were performed in Ambra1+/gt with a C57BL/6N background and observations were only found in the female mice. Another study analysing neurogenesis in adult mice could demonstrate the importance of the Ambra1/Beclin 1 autophagy pathway in this context55. Increased RGC death after a severe ischaemia/reperfusion model, induced by increasing IOP and causing ischaemia of the retina for 60 mins, has been demonstrated previously in the Ambra1+/gt, the age of the animals was not stated in the paper56. None of the studies showed an age-related impact of Ambra1+/gt. With our results we therefore are the first to demonstrate an age related increase in RGC vulnerability in the context of autophagy deficiency, leading to the conclusion that Ambra1+/gt mice could be a perfect model to study age related neurodegenerative diseases in the context of autophagy deficiency.We demonstrate increased RGC loss in 13-month-old Ambra1+/gt animals, which could contribute to increased RGC loss after ONC in the aged Ambra1+/gt animals. 8.5% of the proteins significantly differently regulated in the Ambra1+/gt animals are involved in the oxidative stress response. Glutathione depletion was the most significantly altered toxicological function pathway found in the IPA analysis in the aged Ambra1+/gt retinae, pointing towards dysregulation of this pathway in the retinae of these animals. Glutathione is one of the most prominent intracellular antioxidant systems57 that it is known to decline with age and promote stress-induced premature senescence in RPE cells58. Ambra1+/gt animals show altered oxidative stress response after ONC displaying reduced mRNA Gpx1 induction in Ambra1+/gt animals, and the failure to increase Nrf2 (Nfe2l2) mRNA or to adequately maintain Nqo1 mRNA levels sufficiently after ONC. GPX1 belongs to the very potent group of hydroperoxide-detoxifying enzymes, protecting the cell against oxidative damage such as offering a first line response for tackling mitochondrial derived ROS60. Briefly, upon overload of the GPX1 response, ROS accumulate and transcription of antioxidant genes such as the downstream NRF2 genes are activated. Increased Nrf2 expression promotes RGC survival after ONC and also plays a role in protecting RGCs against IOP related damage62. Additionally, Nrf2 knockout mice have also been shown to exacerbate optic neuritis in an experimental autoimmune encephalomyelitis model as well as in an ocular ischaemia and reperfusion model64. NQO1 is another important antioxidant protein and can transcriptionally be regulated via Nrf2, as well as Aryl hydrocarbon receptor (AhR), although this does not necessarily lead to the same expression pattern65. Another study analysing Nqo1 mRNA expression found a slight increase 1 day after ONC, however 4 and 7 days after ONC, the levels were back to baseline66. We believe that impaired oxidative stress response plays an important role for higher RGC vulnerability after damage in the aged Ambra1+/gt autophagy impaired animals. We furthermore conclude, that non-injured Ambra1+/gt animals already have a higher activity of stress response mechanisms, due to autophagy deficiency. These chronically induced pathways could lead to an exhaustion of the system. If additional factors such as age in combination with more severe damage, as performed with the ONC, are present, these pathways fail to protect the RGC.Our experiments show an altered oxidative stress response in 68. More specifically, AMBRA1 mediated mitophagy plays an important role in counteracting oxidative stress in neuronal cells69. Our results suggest increased mitophagy induction (Bnip3 and Bnip3l) in Ambra1+/+ animals) 7 days after ONC, whereas those levels are not increased in the Ambra1+/gt animals. Increased Bnip3 levels 7 days have also been demonstrated in other CNS damage models such as in acute CNS ischaemia70 and induction of mitophagy via Bnip3l showed neuroprotective effects in acute cerebral damage independently of PRKN72. More generally, rapamycin has demonstrated beneficial effects in the context of acute CNS damage showing increased neuronal survival after spinal cord or brain injury as well as RGC rescue after optic nerve transection and ischaemia/reperfusion56. Rapamycin is well known to increase autophagy, and also upregulates mitophagy and mitochondrial fission in in vivo CNS damage models76. Supporting possible increase of mitophagy after ONC, EM pictures of RGCs after optic nerve transection show increased numbers of mitochondria in autolysosomes 6 days after the insult36. It is tempting to speculate that increasing mitophagy therefore could possibly have a beneficial role for optic nerve damage and glaucoma.Mitochondria are the main source of ROS within the cell and mitophagy is not only induced by oxidative stress but also plays a major role in modulating ROS in the cellAmbra1+/gt animals show less survival and reduced neurite outgrowth in vitro in comparison to Ambra1+/+ derived RGCs. Eleven of the proteins found to be differently regulated in Ambra1+/gt animals are involved in neuron projection and 7 proteins are involved in eye development. AMBRA1 plays an important role in embryonic neuronal development, leading to early embryonic death when totally knocked out30. However, Ambra1+/gt animals show normal development and no apparent phenotype. Studies have demonstrated the role of AMBRA1 induced autophagy in the development of embryonic olfactory bulb neurons. Using eOBSCs (Stem/progenitor cells from the mouse embryo olfactory bulb) it was demonstrated that Ambra1+/gt stem cells grow less and generate smaller neurospheres and less neurons, underlining the importance for AMBRA1 in neurons in a developmental stage34.We can show that primary RGCs derived from postnatal Ambra1+/gt retinae. Alpha-crystallins display chaperone like features, belong to the small heat shock family77 and can protect cells from stress induced apoptosis78. Alpha-crystallin expression in the retina is increased in various stress conditions such as diabetic retinopathy or glaucoma, aiming to protect the retinal cells from cell death79. All of the crystallins found in this study are predominantly expressed in RGCs44. More importantly, alpha-crystallins show RGC protective effects after ONC80 and neuroprotective effects of beta-crystallin B2 have been extensively studied in the context of RGC damage and survival models, as well as RGC axonal outgrowth81. Additionally, crystallins can also be linked to age related macular degeneration, and altered crystallins lead to impaired lysosomal clearance in the retinal pigment epithelium83, however they have not been linked to AMBRA1 so far. Studies have been able to link crystallins (CRYBA1 and CRAYAB) to ATP6V1A expression. ATP6Va1 is a subunit of the vacuolar H+ATPase (V-ATPase) necessary for lysosomal acidification and also for autophagy85. Our proteomics analysis shows decreased ATP6Va1 in Ambra1+/gt retinae, as well as other proteins involved in phagosome maturation. Thus, decreased crystallins in Ambra1+/gt mice could not only lead to a loss of neuroprotective functions but also to defective lyosomal function and autophagy arrest. In addition, crystallins increase axonal growth in embryonic as well as young RGCs and neurons in vitro promoting neurite and axonal growth87 and reduced expression of these proteins could be playing a role in decreased RGC neurite outgrowth of Ambra1+/gt derived RGCs.Our proteomics data showed decreased expression of several crystallin proteins  in Ambra1+/gt mice have increased levels of defence pathways such as the oxidative stress response, resulting in an exhaustion of the system that leads to a reduced response after additional stress conditions. Future research should analyse in more detail the relevance of mitophagy and oxidative stress after neuronal damage to evaluate possible therapeutic targets for glaucoma and other related diseases.In conclusion, we have shown an age-related increase in RGC susceptibility in the context of autophagy deficiency. Altered mitochondrial and oxidative stress response proteins in control but also after ONC conditions play a role in increased RGC vulnerability. It can be speculated that in control conditions, old Figure legends for Supplementary Figures 1 and 2Supplement Figure 1Supplement Figure 2


In addition, we observe the transition from ice XIX to its sibling ice XV upon heating, which proceeds via a transition state (ice VI‡) containing a disordered H-sublattice. To the best of our knowledge this represents the first order-order transition known in ice physics.Ice polymorphs usually appear as hydrogen disorder-order pairs. Ice VI has a wide range of thermodynamic stability and exists in the interior of Earth and icy moons. Our previous work suggested ice β-XV as a second polymorph deriving from disordered ice VI, in addition to ice XV. Here we report thermal and structural characterization of the previously inaccessible deuterated polymorph using ex situ calorimetry and high-resolution neutron powder diffraction. Ice β-XV, now called ice XIX, is shown to be partially antiferroelectrically ordered and crystallising in a √2×√2×1 supercell. Our powder data recorded at subambient pressure fit best to the structural model in space group  Water ice exhibits several hydrogen-disordered phases that become ordered upon lowering the temperature, but ordering of ice VI, one of the main ice phases, is not well understood. Here the authors identify and structurally refine a partially hydrogen-ordered phase, ice XIX, obtained from ice VI, and observe its transition to its partially hydrogen-ordered sibling ice XV. While the oxygen atoms fully occupy crystallographic sites in the molecular framework, the hydrogen atoms are disordered over partially-occupied sites. Yet, the Bernal-Fowler rules1, also known as the ice rules, are obeyed, in the sense that (i) the crystal is composed of H2O molecules and (ii) there is always a single hydrogen atom between two oxygen atoms, so that a space-filling hydrogen-bonded network is formed. Following these rules many different configurations are allowed, where the total number of possible microstates gives rise to a configurational entropy Sconf of approximately Sconf = R*ln(3/2) known as Pauling entropy2. Below the order-disorder temperature To-d thermodynamics requires a fully ordered phase to be more stable than this frustrated ice. In this phase both H and O atoms are ordered, so that the configurational entropy is zero. How the H atoms order and the net dipole moment of the ordered structure are a challenge to predict accurately. Quite often the ordered ice is not accessible through simple cooling. In case of ice IhTo-d was found to be very low, at 72 K5 – and yet, even upon cooling ice Ih slowly below 72 K it does not order. The times required for order to develop are simply beyond laboratory time scales. Only in 1972 Kawada3 achieved the transition, where applying two key concepts allowed access to the ordered ice6: (i) nucleation of the ordered phase by keeping the sample for a few days about 10 K below To-d, (ii) accelerated growth of the ordered ice phase through the use of extrinsic defects just below To-d. Specifically, Kawada was the first to use KOH doping, which generates an ionic OH- defect (violating ice rule (i)) together with a Bjerrum-L-defect (violating ice rule (ii))7. Such defects are now known to accelerate the reorientational dynamics by up to five orders of magnitude8. The ordered phase related to ice Ih that needs growth times of a few days is called ice XI. Ice XI represents the ground state of ice at 0 K and ambient pressure, not ice Ih or ice II as previously believed9. Its ferroelectric ordering determined from single crystal neutron diffraction data6 and molecular simulations10 has been challenged and subsequently claimed to be antiferroelectric11. The same issues arise for a plethora of high-pressure ice phases. For instance, disordered ice V and ice XII, could only be transformed to their ordered counterparts, ice XIII and ice XIV, through the use of HCl doping12. HCl doping introduces an ionic H3O+ defect, together with a Bjerrum-L-defect. In these cases To-d is 112 ± 3 K15 and 102 ± 3 K18, respectively. Their growth takes place on the time scale of hours rather than days because of the higher To-d. Undoped or KOH-doped high-pressure ices do not order sufficiently fast, for reasons that are yet not fully understood. The ice III/IX and ice VII/VIII order-disorder pairs have To-ds of 170 K and 273 K7, respectively – high enough so that the use of dopants is no longer necessary to achieve ordering.Hexagonal ice . Considering the difference of 25 K in To-d for these two endotherms this corresponds to a loss of Sconf of 0.46 and 0.35 J mol−1K−1 in pure H2O samples, respectively. For pure D2O the exact same procedure results in the trace depicted at the bottom of Fig. −1. That is, the bulk of the sample had remained disordered ice VI upon cooling under pressure. This had prevented neutron diffraction work on the crystal structure before the present study. In order to resolve the issue we have first attempted to reduce the cooling rate significantly below 3 K min−1, which is the rate that successfully produces H2O ice β-XV. The lowest cooling rate employed for D2O samples was 0.1 K min−1, thereby providing 13 h for the sample to order upon cooling. Even reduction of the cooling rate by this factor of 30 has not changed the picture, where still barely any ordering takes place upon cooling D2O ice VI . Figure 2O ice β-XV is inhibited and the limiting factor that needs to be tackled to prepare the deuterated polymorph. We know from our previous work that H2O ice β-XV successfully nucleates within ice VI25. Thus, we have attempted to enhance D2O ice β-XV nucleation kinetics by adding H2O. The result of deliberately adding H2O to D2O samples is summarized in Fig. 2O. Already 0.5% makes a tremendous difference. The disordering endotherm near 100 K suddenly appears with an enthalpy of 61 J mol−1. Repeating the experiment with 1%, 2%, 5%, 10% or even 30% added H2O barely changes this picture. Only for the 95% H2O sample the calorimetry traces of pure H2O are restored, which suggests that our strategy has been successful. This is confirmed when inspecting isotope effects on the latent heat and disordering temperature. The enthalpy associated with disordering of D2O ice β-XV is about 64 ± 8 J mol−1 as compared to 45 ± 5 J mol−1 for the case of H2O ice β-XV – a typical isotope effect for endotherms. The onset point for the D2O sample shifts to higher temperatures by about 3 K – again a quite typical isotope effect31. That is, the DSC traces suggest that D2O ice β-XV indeed does form in all mixtures containing from 0.5% to 30% H2O. For this reason these compositions are coloured in blue and marked D2O ice XIX in Fig. To-d of 107 K an entropy change of 0.60 ± 0.07 J K−1 mol−1 results. This corresponds to 18 ± 2% of the Pauling entropy.The mere fact that reducing the cooling rate still does not increase the order within the ice VI sample points against phase growth as the issue. Instead nucleation of D‡ here.In the d-spacings from 0.65 to 2.60 Å for structure refinements. Figure 32 or ex situ by Salzmann et al.21 on the GEM instrument. It also matches the tetragonal P42/nmc structure deduced by Kamb in 1965 from X-ray measurements33. Our refined ice VI structure contains comparatively short O-D distances, ranging from 0.917 to 0.936 Å, which is a consequence of orientational disorder leading to static distortions as outlined by Kuo and Kuhs34. The same effect also appears for other disordered ices, such as ices III and V35 or VII32. The ice XV pattern recorded from a sample recooled from 135 K with a cooling rate of 0.4 K min−1 at 50 mbar matches nicely with the pattern recorded by Salzmann et al.21. Compared to ice VI, new Bragg peaks at 1.775, 1.938, 2.013, 2.066 and 2.129 Å are found in the ice XV pattern21. The ice β-XV pattern recorded from a sample containing 5% H2O is depicted at the bottom of Fig. d-spacings between 1.5 and 2.4 Å are marked by blue dashed lines that appear in ice β-XV, but not in ice VI. The 1.583, 1.734, 2.254 and 2.326 Å features also do not appear in ice XV. The 1.775, 1.938 and 2.129 Å features characteristic of ice XV on the other hand do not appear in ice β-XV 21. This explains why high pressure favors the formation of ice XIX over ice XV and vice versa at low pressure. At about 107 K the c-axis length obtained in the heating scan of ice XIX crosses the c-axis length of undoped ice VI. This is exactly where the disordered transition state ice VI‡ is indicated in the calorimetry and neutron diffraction experiments described above. Above 130 K the c-axis length in ice XV then drops back from 5.805 to 5.792 Å, i.e., the value of ice VI. Thus, the transition sequence ice XIX → ice VI‡ → ice XV → ice VI is clearly evidenced from these heating experiments and marked accordingly in Fig. The phase behaviour upon heating ice XIX from 70 to 132.5 K is demonstrated in Fig. 36. These authors have studied the ice XIX structure in situ at 1.6 GPa using small volume samples, whereas we have studied the ice XIX structure ex situ at about 50 mbar using gram quantities of ice XIX. Consequently, their peak intensities are smaller than ours and suffer from significant peak overlapping with reflections from the high-pressure cell. Furthermore, they have not added a small amount of H2O, which leads us to think that the fraction of ice XIX in their sample is smaller than in ours due to adverse nucleation kinetics for D2O ice XIX.The issue of refining the ice XIX structure was simultaneously also tackled by Yamane et al.37, starting from the structural model of Kuhs et al.32. This yielded a fit with χ2 = 2.307 and weighted Rietveld powder statistic wRp = 1.50 %. Lattice parameters for ice VI at 70 K were found to be a = 6.242485(11) Å, c = 5.770048(22) Å, V = 224.851(1) Å3. This structure refinement formed the basis for deriving models to test against the ice XIX data. One observes in the doped ice sample that many peaks permitted by the P42/nmc space group of ice VI, but which have negligible or zero intensity in ice VI, adopt a measurable intensity in ice XIX, albeit being very broad. Examples include the 212 and 311 peaks at d = 2.00 and 1.868 Å respectively , a set of 21 higher symmetry space groups is obtained – P42, 1m, m, P42nm, P42cm, Pbcn, Pcca, Pnna, Pban, Pnn2, Pna21, Pba2, Pnc2, Pca2, Pcc2, P21212, P2221, P222, Pmmn and Pmm2. In order to investigate their compatibility with the O-lattice, the structure was centred in line with their respective transformation matrix42. This procedure is illustrated in Supplementary Figures P42, P21212, Pcc2 and Pcca. In order to obtain a feasible set of candidate structures, the H-atom networks of these space groups have to be taken into account. That can be done by observing both Bernal-Fowler rules and the respective space group symmetry. Specifically, each H-site is reflected through all symmetry operations so that H-positions of the same occupancy could be found. The occupancies of even more positions were derived from the Bernal-Fowler rules, as illustrated in Supplementary Figure Pcc2, which implies that a structural model in space group Pcc2 is necessarily only partially ordered. In total 109 valid structures in five space groups could be determined as possible candidate structure through these considerations, which can still not be tested quantitatively against the data. Moreover, the deviation of these structures from the average ice VI structure is very small and the amount of information required to describe this is represented by just a few quite weak fundamental and super-lattice peaks. Hence, the refinement of structural models is quite delicate, requiring restraints, constraints and damping in order to avoid divergence and to arrive at stable solutions. Even then, the difference in the statistical quality of the fit between models turns out to be small. We have, therefore, based our choice of tested structures on a few specific examples, and once we became aware of the structure fitting reported by Yamane et al.36, first deposited as a preprint, we have chosen to report the equivalent best-fitting for their four best structural models in space groups, Pcc2 and P21212 and Pca21 . The quality of the fits to the diffraction data are shown in Fig. Pcc2), 6 (for P21212) and 8 (for Pca21). These refinements yield accurate atomic coordinates, D-atom occupancies and average isotropic displacement parameters, being reported in Table Pcc2), 2 (for P21212) and 3 (for Pca21) using the atom labelling as shown in Fig. 2 of 3.278 was obtained, with wRp = 2.38 %. The tetragonal lattice parameters at 70 K are a = 8.834721(33) Å, c = 5.75542(5) Å, V = 449.224(4) Å3. With respect to an exact √2×√2×1 super-cell of ice VI, the volume of ice XIX is smaller by ΔV/V = −0.11%. This reduction in volume is dominated by a shortening of the c-axis (−0.254%) partially offset by a small expansion in the two orthogonal directions perpendicular to c.In total almost 2000 possible structure models are feasible for the supercell of double the ice VI unit cellP21212 and Pca21 models clearly fall short of Pcc2 model results in only a slightly poorer fit to the data. Especially the Bragg peak at 1.87 Å shows the best fit with the Pcc2 model  Å, b = 8.82654(7) Å, c = 5.75559(5) Å, V = 449.218(5) Å3. In common with the tetragonal model, we observe a reduction in volume relative to ice VI of approximately −0.10 %, much of which is due to contraction of the c-axis. That is, c-axis contraction is necessary to reach ice XIX from ice VI, which can be achieved under high-pressure conditions near 2 GPa, but not at low-pressure conditions. Hence the Yamane et al. data obtained in situ at 1.6 GPa and our data obtained ex situ at ~50 mbar can be described using the same structural models and we conclude that their work and ours indicates the same partially ordered superstructure, described as ice XIX. The two best models differ from each other in one important aspect: the two interpenetrating frameworks in the Pcc2 model are related by symmetry and thus the degree of order achieved is the same in both components of the framework. Since the two leading candidate models crystallise in non-centrosymmetric space groups, a simple powder test (such as second harmonic generation) cannot definitively distinguish between the two choices. On the other hand, Pcc2 represents a polar point group, exhibiting pyroelectricity, whereas the c-axis of ice Ih is observed upon transformation to the ferroelectrically-ordered phase ice XI43. This leads to local partial ordering of ice Ih on cooling towards the ordering transition and formation of domains of ice XI within ice Ih44.While the odel see , a χ2 ofPcc2 model. The difficulty to distinguish between the two is likely to be related to small domains of ice XIX. Indeed, with powder data alone, a conclusive determination of the symmetry resulting from the partial ordering is extremely difficult and efforts to prepare ice XIX as a single crystal are required, as well as systematic computational studies of the thousands of possible orientational configurations. The space group symmetry requires ice VI to be fully hydrogen disordered. Any change in hydrogen order has to be associated with breaking of the space group symmetry21. That is, fractional occupancies of D-atoms deviating from it make the case for a new ice structure, as is the case for both structures fitting the data. Ice XIX is slightly better ordered compared to ice XV based on the calorimetry data, where D2O and H2O ice XIX release 18% and 14% of the Pauling entropy upon disordering, respectively, compared to 10% in case of H2O ice XV. Both structures feature cancellation of dipole moments, such that the structure’s partial hydrogen ordering is antiferrolectric. That is, our earlier speculation of a possible ferroelectric structure is incorrect26. Also earlier theoretical predictions about a ferroelectric structure in the Cc space group are incorrect45. While Nanda and Beran had correctly predicted that the Cc structure is less favourable than the experimental ice XV structure, the supercell necessary to describe ice XIX was not considered46. We can certainly rule out any 1×1×1 unit cell, including the one for space group Cc, e.g., because our sharp peak at 1.960 Å and the broad peak at about 2.01 Å would be absent in Cc. Knight and Singer examined √2×√2×2 cells and found a nearly energetically degenerate antiferroelectric structure in P21212142. Even though we do not see any evidence for a doubling along c in our ice XIX data, this illustrates how sensitive the ordering is to long-range interactions. And this is where more recent developments in DFT, such as the widespread and easy implementation of dispersion corrections, looks to be essential to solving this very delicate problem. Now that we have established the correct unit cell, it should be possible computationally to provide a robust prediction of the ground-state configuration in future work.We here report the crystal structure for a partially hydrogen-ordered ice polymorph. Based on common practice, the availability of the crystal structure allows us to assign a Roman numeral to this ice phase. Following the latest discovery of the superionic phase ice XVIII appearing at ultrahigh-pressure, we here add ice XIX to the ice phase diagram in the versatile intermediate pressure range between 0.5 and 2.0 GPa, in which 13 ice polymorphs are now known. Ice XIX represents an ordered phase sharing the same oxygen atom topology with its parent, disordered ice VI, and its sibling, partially antiferroelectrically ordered ice XV. The tetragonal −1) and neutron powder diffraction scans at HRPD (averaged over the whole run at 2.5 K hour−1). To the best of our knowledge this makes the case for the first order-order transition in the H-subnetwork in a given O-network in ice physics. Ice XIX shows an O-lattice and a partly ordered H-network, making the case for a fully crystalline polymorph, as opposed to a crystal that shows a disordered H-subnetwork. That is, ice XIX, formerly called ice β-XV, cannot be described as a deep glassy state. The mechanism of the order-order transition from ice XIX to ice XV is shown to proceed in an activated fashion, where the activation barrier needs to be determined in future work. In the present work we are able to show that a transient, disordered state is encountered as the transition state – called ice VI‡. The deep glassy state put forward in earlier work by Rosu-Finsen & Salzmann29 could then be the transiently encountered ice VI‡, but not ice XIX. We also rule out the possibility of ice XIX turning into deep glassy ice upon pressure change. The same structural models for ice XIX fit both data recorded at 1.6 GPa (reported in ref. 36) and data recorded at 50 mbar (reported in the present work). A comparison of unit cell volumes at 1.6 GPa and 50 mbar translates into an approximate estimate for ice XIX’s bulk modulus of 21 GPa at 70 K. This compares with a bulk modulus of 18.5 GPa for its disordered parent ice VI47 and for ice Ih of 11.2 GPa7, both at 70 K.Upon heating ice XIX transforms in two steps first to ice XV above 107 ± 1 K, and then to ice VI at 128 K. This is consistently seen in the heating scans in calorimetry  cooling 600 µl 0.01 M DCl in D2O:H2O mixtures (0.04 to 99.99% H2O) to 77 K, (ii) compressing to 1.8 GPa using a piston-cylinder setup with an 8 mm diameter bore in a Zwick BZ100 material testing machine, (iii) heating to 255 K, followed by (iv) slow cooling at rates of 0.1 to 3.0 K min−1 to 77 K. Undoped ice VI was prepared following a similar pathway using a 95:5 D2O:H2O mixture. After cooling to 77 K ice VI samples were compressed to 1.0 GPa before heating to 255 K, followed by quenching with liquid nitrogen at ≈ 80 K min−1. After releasing the pressure at 77 K, ice XIX and ice VI samples were recovered and stored under liquid nitrogen at atmospheric pressure. The ice XV reference was prepared in situ from ice XIX by heating to 135 K at 50 mbar (converting it to ice VI) and then recooling it with 0.4 K min−1 to 70 K (converting it to ice XV).Sample preparation was done using the same set of equipment as used in our previous work−1 from 93 to 253 K, which leads to the transformation of both, ice XIX (over the sequence ice VI‡ → XV → VI) and ice VI, to ice Ih. The resulting ice Ih was cooled to 93 K and heated in a second scan to 313 K. The second scan was used to correct the background of the first heating run. The enthalpies of fusion of H2O 48 and D2O49, 6012 and 6280 J mol−1, were used to determine the mass of ice inside the crucible. The baseline was interpolated between the straight sections before the first and after the second endotherm to evaluate peak areas, onset and offset points. In selected experiments, ice XIX (D2O:H2O = 95:5) samples were heated from 93 to 120 K at 10 K min−1 and annealed at this temperature for 30 min to allow ice VI‡ to transform to ice XV. Afterwards, the samples were heated to 253 K to record the second endotherm pertaining to the ice XV to ice VI transition.All quench-recovered ices were analyzed calorimetrically using a Perkin Elmer DSC 8000 at ambient pressure. The samples were encapsulated in aluminium crucibles under liquid nitrogen and transferred to the precooled oven of the calorimeter. Every batch was characterized by heating at 10 K min2O ice VI and doped ice XIX were examined using neutron powder diffraction methods on the High Resolution Powder Diffractometer (HRPD) at the ISIS Neutron and Muon Spallation Source, Rutherford Appleton Laboratory, UK50. The various ices were measured in slab-geometry sample holders that are described in detail elsewhere51, having internal dimensions with width, height and depth = 18 × 23 × 5 mm relative to the incident neutron beam. These were partially assembled and immersed in liquid nitrogen for the loading procedure. The powdered samples were transferred from a nitrogen-chilled steel cryomortar into the sample holder using a nitrogen-chilled spoon. Once filled, the ‘back’ vanadium foil window of the sample can was attached with screws. Both the ‘front’  and ‘back’ windows were sealed with 1 mm indium wire to prevent leakage of material from the interior. The front windows and the body of the sample holder were masked with Gd and Cd foil.Samples of pure D−1 with a mandatory wait of 10 min at each temperature prior to beginning a measurement in order to be sure that complete thermal equilibrium of the sample was achieved.The fully-assembled sample holder was then transferred into a top-loading Closed Cycle Refrigerator (CCR) mounted on the HRPD beam line at 70 K. Temperature control was achieved using a cartridge heater and a RhFe thermometer inserted into the aluminium frame of the sample holder, the background temperature of the He exchange gas being maintained ~30 K below the sample temperature where possible. Moving from one temperature to another was done at a rate of 3 K mind-spacings from 0.65 to 2.60 Å, which contains the great majority of Bragg reflections required for a high-precision structure refinement. For example, ice VI has >240 reflections in this d-spacing range whereas the next available detector bank at 2θ = 90 ± 10°, which allows us to access d-spacings from 1–4 Å, contains only an additional five reflections. Nevertheless, these fewer but more intense peaks are often useful for rapid tracking of phase changes, as shown in Fig. Data were collected using a neutron time-of-flight window extending from 30 to 130 ms. In HRPD’s highest resolution backscattering detector banks, this TOF range yields data covering 52. The CCR makes a comparatively small contribution to the background, but of most concern in the case of these data are the weak peaks from the vanadium foil windows used on the CCR tails, as they occur in a region of very weak peaks of interest from the ice XIX sample. Consequently, a long background measurement from an empty masked slab can in the CCR was made at 70 K to ensure accurate subtraction of the parasitic peaks from the structural datasets obtained from ice VI and ice XIX at 70 K.Raw time-of-flight data were focussed to a common scattering angle for each detector bank, normalised to the incident spectrum and corrected for instrument efficiency by reference to measurements of a V:Nb rod and the empty instrument with the Mantid suite of powder diffraction algorithmsiso, to achieve an average value for each type of atom (O or D). Constraints were also used to ensure that the D-atom occupancy along each D-bonded O–O vector summed to one. Chemical restraints were imposed to insure that, where not otherwise determined by the occupancy constraints or by symmetry, the total number of D-atoms per O-atom remained fixed equal to two.Structural models in different space groups were fitted to the high-resolution neutron powder diffraction data using the Rietveld method implemented in GSAS/Expgui. Bond length restraints of 0.925 ± 0.015 Å were placed on the O–D bond length, based on the average length found in our ice VI refinements; no bond angle restraints were imposed. Constraints were applied to the isotropic displacement parameters, USupplementary InformationPeer Review File


No consistent pattern was apparent in the vertical distribution of microplastics within sea ice cores. Backward drift trajectories estimated that cores possibly originated from the Siberian shelves, western Arctic and central Arctic. Knowledge about microplastics in environmental compartments of the Arctic Ocean is important in assessing the potential threats posed by microplastics to polar organisms.Within the past decade, an alarm was raised about microplastics in the remote and seemingly pristine Arctic Ocean. To gain further insight about the issue, microplastic abundance, distribution and composition in sea ice cores (n = 25) and waters underlying ice floes (n = 22) were assessed in the Arctic Central Basin (ACB). Potential microplastics were visually isolated and subsequently analysed using Fourier Transform Infrared (FT-IR) Spectroscopy. Microplastic abundance in surface waters underlying ice floes (0–18 particles m Of the environmental compartments in this remote oceanic basin, it was shown that sea ice can function as a temporal sink, a secondary source and a transport medium for microplastics2. Historically, however, observational records of ‘dirty ice’, examination of Arctic ice cores, laboratory-based experiments and modelling studies were the first to highlight the potential for sea ice in the Arctic Ocean to trap, transport and redistribute sediments and various contaminants 27. Microplastics (plastic particles <5 mm in diameter) were first discovered in sub-sections of 4 ice cores retrieved from various locations in the Arctic Ocean1. In this initial study, a total of 6 types of synthetic polymers were reported in the ice cores and microplastic concentrations in Arctic sea ice were estimated (based on extrapolations) to be between (1.3–9.6) × 104 particles m−3. A second study2, subsequently examined 5 sea ice cores from the Arctic Ocean, reported on the presence of smaller (<100 µm in diameter), more diverse types of synthetic polymers (n = 17) and estimated (based on extrapolations) microplastic concentrations in Arctic sea ice to range between (1.1 × 106)–(1.2 × 107) particles m−3. Both studies2, while limited in scale and extent, collectively suggested that sea ice can function as a sink, source and transport medium for microplastics in the Arctic Ocean.Within the past decade, microplastic pollution emerged as an issue of concern in the Arctic Ocean due to the discovery of these contaminants in its sea ice14. In the Arctic Ocean, while sea ice formation occurs over the central Arctic Ocean, the most important regions for this are the shallow Siberian shelves in the Eurasian Basin and the Beaufort Sea in the Amerasian Basin15. Microplastics entrapped within sea ice during its formation can potentially be reflective of microplastics present in seawater from known ice formation regions in the Arctic2. While the majority of sea ice melts in close proximity to its formation zone, some sea ice (i.e. that which forms over the Siberian shelves) is advected off the coast, joins the Transpolar Drift with some eventually exiting through the Fram Strait16. Sea ice from the Beaufort, Chukchi and East Siberian seas may become incorporated into the Beaufort gyre with some sea ice having the potential to exit this gyre and eventually join the Transpolar Drift17. Within the Arctic Ocean, sea ice dynamics are one of the key factors that potentially influences contaminant fate. Mobile sea ice floes in the Arctic Ocean are capable of entrapping contaminants along their drift pathways and playing a role in the redistribution of contaminants due to their eventual release upon melting of the ice2,19. Estimating backward sea ice trajectories is an important tool that facilitates an examination of sea ice sources, drift pathways, thickness changes and atmospheric processes acting on the ice cover30. When utilized in microplastic studies, backward sea ice trajectory data (i.e. sea ice sources and drift pathways) can be used to make inferences about potential regions where microplastic entrapment in sea ice occurred. The AWI ICETrack application, a lagrangian approach that traces sea ice backward in time using a combination of satellite-derived low-resolution drift products, is one available modelling approach that was utilised in the most recent study on microplastics in Arctic sea ice2. In the Arctic Ocean, sea ice has been identified as a temporal sink and secondary source of microplastics since contaminant release is projected to occur upon the melting of sea ice2. In the context of a changing climate, projections for Arctic sea ice include decreasing sea ice extent, reductions in sea ice thickness (less multi-year ice), alterations in the rate of sea ice drift, intensified melting of sea ice in the marginal zones and interruption of its Transpolar Drift33. These changing conditions will inevitably influence the dynamics of contaminant fate and transport in the Arctic Ocean, especially if the contaminants of interest are capable of being entrapped within, transported and subsequently released by sea ice.Within this remote oceanic basin, microplastic entrapment within sea ice potentially occurs during sea ice formation and drift while microplastic release occurs upon the melting of sea ice34 and sea ice provides a range of microhabitats for numerous species37, an understanding of microplastic contamination in sea ice and surface waters of the Arctic Ocean is vitally important. The specific objectives of this study were to (i) provide a more spatially comprehensive assessment of microplastic concentration and composition in sea ice cores from the Arctic Ocean, (ii) assess the vertical distribution of microplastics in entire sea ice cores, (iii) estimate backward drift trajectories and identify source areas of sampled sea ice cores and (iv) assess microplastic abundance, distribution and composition in surface waters (beneath ice floes) in the Arctic Ocean.Given that the 18 Arctic Large Marine Ecosystems (LMEs) support a diverse array of marine lifeOf the shipboard air contamination checks (n = 13) that were carried out, a single fibre  was found. This indicates a low likelihood that microplastics were introduced to the samples as a result of airborne contamination. Of the method blanks (n = 15), 7 were free of contamination while the remainder contained either a single fibre (n = 6) or 2 fibres (n = 2). Fibres in the method blanks were polyester (n = 6), polyamide (n = 1) or a polyamide blend (n = 3). In order to account for any contamination that might have been introduced during ice core processing, a blank correction was applied whereby a single fibre was removed from each sub-section total. Additionally, if there were any matches between synthetic polymers found in the samples and those that came into contact with the samples (either during sampling or laboratory processing), these particles were excluded from the results.A total of 2031 particles were isolated from the 25 sea ice cores and analysed using FT-IR spectroscopy. Of these, 501 particles were rejected due to (i) poor spectral matches, (ii) matches with polymers used during sample collection or processing and, (iii) identification as being natural or semi-synthetic polymers. A further 117 synthetic polymers were excluded from further analyses since they were categorized as being macroplastics (>5 mm). Of the 1413 confirmed synthetic polymers, 223 were removed during the blank correction processes. Subsequent analyses are therefore based on 1190 synthetic polymers <5 mm from the sea ice cores.−1 with particle size ranging between 0.10 mm–4.99 mm  and 3 (15 particles L−1),  from the Arctic Central Basin ranged between 2–17 particles LOverall, there appears to be no consistent pattern in the vertical distribution of microplastics within sea ice cores Fig. , as well−1 possibly originated in the Laptev, East Siberian and Chukchi Seas , multivariate analyses , was unable to provide any useful discrimination between sea ice cores.Backward trajectories of the ice cores indicated that they possibly originated from the (i) Siberian shelves in the Eurasian basin , (ii) western Arctic  and, (iii) Central Arctic Ocean Fig. . Of all as Figs. . Sea ice−3, Fig. 3) to (1.7 × 104) particles m−3 (extrapolated from particles L−1). Of the 22 sites where surface waters were sampled, only one site did not have microplastics detected. In terms of polymer composition, the majority of polymers detected in surface waters of the ACB were polyesters (70%) and polyamides (23%) with a minority of polyvinyl chloride (7%). Microplastic size class distributions were as follows: 0.25–0.5 mm (16%), 0.5–1 mm (18%), 1–2 mm (34%), 2–3 mm (14%), 3–4 mm (11%), 4–5 mm (6%), with the majority of microplastics (68%) being <2 mm. Overall, fibrous microplastics predominated (89%). In terms of colour, the majority of microplastics were blue (58%) and red (18%), with other colours such as transparent (5%), pink (4%), yellow (4%), grey (4%), purple (3%), green (2%), black (2%) and brown (1%) also being recorded.A total of 189 particles were isolated from surface water beneath ice floes samples in the ACB. Of these, 47 were rejected for the above-mentioned reasons (i.e. those stated for the ice core samples). A further 17 synthetic polymers were excluded since they were categorized as macroplastics (>5 mm). Subsequent analyses were based on 125 synthetic polymers <5 mm from the surface water samples. Microplastic abundance in seawater beneath the ice floes (0–18 particles m3) to (1.7 × 104) particles m−3) were orders of magnitude higher than those reported for seawater beneath ice floes (0–18 particles m−3). While these findings corroborate those of previous studies2 that identified sea ice as a temporary sink for microplastics in the Arctic Ocean, it is collectively apparent that to date microplastic concentrations in Arctic sea ice have been underestimated. Analytical techniques  employed in the present study led to the exclusion of particles <100 µm from analysis and as such would have resulted in an underestimation of microplastic concentration in sea ice cores –(1.7 × 104) particles m−3). This is particularly relevant in light of the fact that the majority of microplastics in Arctic sea ice reported by a previous study2 using Imaging FTIR were <50 µm  – (1.2 ×107) particles m−3). Although the previous study2 reported the highest microplastic concentrations thus far in sea ice, fibres were excluded from the analysis. By contrast, the present study reported a pre-dominance of fibrous microplastics (79%) in sea ice from the Arctic Ocean. It is therefore apparent that if either fibres or particles <100 µm are excluded from the findings, microplastic concentrations in sea ice will be underestimated. Furthermore, both the present study and a previous study2 showed that there was no consistent pattern in the vertical distribution of microplastics within sea ice cores. If isolated sub-sections of ice cores are used to estimate microplastic concentrations in Arctic sea ice as was done in a previous study 1, those extrapolations will either be underestimations or overestimations of microplastic concentrations. In the present study, meltwater volumes in ice cores ranged between 3–12 L. Extrapolations from particles L−1 to particles m−3 are relevant for comparison to microplastic concentrations in surface and sub-surface waters. However, when microplastic concentrations from <20 L of meltwater from a single ice core is used to estimate microplastic concentrations in 1,000 L or 1 m−3 of meltwater, such estimations are based on numerous assumptions and limited datasets . It is therefore suggested that microplastic concentrations in sea ice should be reported as particles L−1.Microplastics, as evidenced by the present study, were ubiquitous in both sea ice cores and seawater underlying ice floes from the Arctic Central Basin (ACB). Microplastic concentrations in sea ice  and polyamides (16%). By contrast, although another study2 on microplastics in Arctic sea ice did report on the presence of polyester and polyamide, the most dominant synthetic polymer in the examined cores was polyethylene (48%) with the difference in findings possibly occurring due to the exclusion of fibres. In the western Arctic at the Bering and Chukchi Seas8, polyesters predominated in surface waters. In the present study, the majority of microplastics in sea ice cores (79%) and surface waters (89%) were fibrous. Similarly, in the Bering and Chukchi Seas8, fibrous microplastics were predominant in surface waters. In the marine environment, fibres may be originating from fishing gear, textiles due to laundering fabric and cigarette filters38. Laboratory experiments have indicated that the input of textile fibres into the marine environment can occur following the discharge of wastewater from domestic washings43. Recently, it was reported14 that both microplastics and microfibers were present in snow from ice floes in the Fram Strait which suggests that these particles could have been transported into the region by winds and been deposited onto ice floes and surface waters via snow. For the remote Arctic Ocean, it is difficult to pinpoint the exact origin of fibrous microplastics. Although definitive statements cannot be made about the origin of microplastics in surface waters or sea ice of the ACB, potential sources of these contaminants may include (i) riverine discharge from the Siberian and Canadian rivers7, (ii) influx of contaminated Pacific and Atlantic waters1, (iii) grey water discharge from vessels operating in the Arctic7 and, (iv) atmospheric deposition14.The identification of microplastic type  and polymer composition is a critical component of microplastic studies as it provides investigators with some insight about the potential sources of microplastics in the environment. In the present study, 9 different types of synthetic polymers were reported in the sea ice cores while 3 were reported in surface waters underlying the ice floes. In both environmental compartments, the majority of microplastics were comprised of fibrous polyesters  and polyamides . Both polyesters and polyamides have a higher density than seawater27, microplastic entrapment in Arctic sea ice potentially occurs during its initial formation over both the shallow marginal shelves of the Arctic Ocean and the deep central basin. In the present study, backward drift trajectories estimated that the sea ice floes from which the ice cores were sampled originated from the Siberian shelves in the Eurasian Basin, western Arctic and central Arctic. If microplastics were entrapped during sea ice formation in these areas and ice floes survived subsequent melt seasons, microplastic composition in sampled sea ice cores could be reflective of the microplastic composition in surface waters from these areas. At the marginal shelves of the Arctic, freshwater discharge from Siberian rivers; Dvina and Pechora (Barents Sea), Ob and Yenisei (Kara Sea), Lena (Laptev Sea) and Kolyma rivers (East Siberian Sea), and the Canadian Mackenzie river (Beaufort Sea)44, could be potential contributors to the microplastic load in Arctic sea ice. Since anthropogenic activities occur within the catchment areas of these rivers, the influx of freshwater into the Arctic basin is a potential pathway via which contaminants could enter this marine ecosystem46. Presently however, the contribution of riverine discharge to the microplastic load in Arctic sea ice remains uncertain due to the absence of field data. Pacific water influx into the Arctic Ocean through the Bering Strait also represents a potential source of contamination2 in that Pacific waters are influenced by anthropogenic activities that occur in northern America and eastern Russia. The Chukchi, Beaufort and East Siberian Seas which border the central Arctic are influenced by Pacific waters8 and thus any sea ice formed in these seas could potentially reflect microplastics that are present in the surface waters in these areas. The backtracking results that were presented in the present study must be interpreted with caution since there was a significant mismatch (>75%) between field and model-predicted ice thickness for 10 of the 25 ice cores (Supplementary Table Similar to the situation for sediments and other contaminants−3) and sub-surface waters of the central Arctic7 indicates the availability of these particles for incorporation into sea ice, whether that is first year ice forming over the central basin or vertical ice growth on the underside of the floes. In the western Arctic8, microplastic abundance in surface waters of the Bering Sea ranged between 0.035–0.26 particles m−3 and in the Chukchi Sea between 0.086–0.31 particles m−3. Outside the central Arctic, microplastic abundance in surface Arctic waters south and southwest of Svalbard3 ranged between 0–1.3 particles m−3 and east of Greenland4 it ranged between 0.2–2.6 particles m−3 in 2005 and 0.8–4.5 particles m−3 in 2014. While conclusive statements cannot be made about differences in the reported microplastic abundances, it is plausible that sea ice functions as a secondary source of microplastics in the central Arctic and contributes to higher microplastic abundances. During transport, atmospheric deposition of microplastics unto the surface of an ice floe may also occur. A recent study14 reported that microplastics and microfibers were present in snow retrieved from ice floes in the Fram Strait. These findings suggested that these particles were potentially transported into the Arctic by winds and deposited unto the ice floes via snow14. Atmospheric fallout of microplastics suggests that these contaminants can be transported through the atmosphere and reach remote areas48. It is possible that microplastics can be transported into the Arctic region by winds and that these particles can be deposited either unto ice floes during transport or directly unto surface waters14.Microplastic incorporation into sea ice floes can also potentially occur during its drift across the central Arctic. Backward drift trajectories produced for sea ice sampled in the present study indicated that 24 of the 25 sea ice cores survived at least one summer melt and endured at least one winter period and that there was either drift across or initial sea ice formation within the ACB. These findings suggest that microplastics found in the sampled sea ice cores were potentially reflective of microplastics in surface waters of the ACB. Once present in surface waters of the central Arctic, periods of freezing will facilitate microplastic entrapment in newly formed ice or on the underside of existing ice floes. Microplastic presence in waters beneath ice floes  and Arctic cod 37. Recently, microplastic fragments were reported in the stomachs of polar cod sampled from waters in the Eurasian Basin of the Arctic Ocean and north of Svalbard13 and in the digestive tracts of polar cod sampled in Arctic waters east of Greenland6. Based on the fact that interactions can potentially occur between marine organisms and microplastics in the Arctic Ocean, laboratory experiments are needed to elucidate the impact of those interactions with polar organisms. From a spatial perspective, regions which could be most at risk from an influx of contaminants (e.g. microplastics) from melting sea ice include nearshore areas over the marginal shelves, the central Arctic basin and the marginal ice zone e.g. Fram Strait, Barents Sea31.Arctic sea ice is not the ultimate but an intermediate sink for microplastics. From a temporal perspective, seasonal environmental conditions (spring/summer melt seasons) influence sea ice melting and subsequent microplastic release in the Arctic Ocean. During summer, snow and ice melt off the upper portion of the ice floe with meltwater either running off the ice floe, percolating into the surface of the floe, accumulating in melt ponds or refreezing on the underside2, the present study evidenced that sea ice is capable of functioning as an intermediate sink, secondary source and a transport medium for microplastics in the Arctic Ocean. For the first time, microplastic presence in seawater underlying ice floes was reported for the central Arctic. Understanding the presence, sources, transport pathways and fate of microplastics in the Arctic Ocean is critical to determining the potential threats posed by such contaminants to marine organisms that inhabit or depend upon different environmental compartments in this ecosystem.The Arctic Ocean is a dynamic ecosystem where projections for Arctic sea ice in the context of a changing climate can inevitably influence contaminant fate and transport, especially if the contaminants of interest are capable of being entrapped within, transported and subsequently released by sea ice. Corroborating previous studiesth to September 19th 2016). At 25 ice stations, sea ice cores (n = 25) were retrieved and seawater (n = 22) was pumped from beneath the ice and filtered onsite for microplastics. At each ice station, a suitable location upwind of all other site activities was selected and overlying snow was removed from an area of approximately 0.5 m2. Ice cores were collected using a Nordic ice drill with an attached Husqvarna X-series 326A125 motor and a stainless-steel core barrel of 12.5 cm diameter. At all sites, the goal was to completely penetrate the ice by drilling and reach the underlying seawater. A single ice core (n = 1) was retrieved at each site, placed into clean bags (polyethylene) and transported to the laboratory onboard the vessel for further processing. Once the sea ice core was retrieved at a site, water was then pumped from under the ice floe. A pre-cleaned polyvinyl chloride (PVC) hose (approximately 2 m in length) was inserted into the drilled hole. This hose was then connected to the inlet of a manual JABSCO Amazon Warrior pump (Model Number 29280-0000). Another hose of approximately 1 m in length was then connected to the outlet of the pump. Prior to any further connections, seawater was pumped from beneath the ice to flush the system of any contaminants. At this point, the flow rate of water through the system was manually checked by pumping seawater into a 1 L measuring cylinder. This was performed in triplicate in order to estimate the length of time needed for pumping the relevant volume of water. Following this, the hose from the outlet of the pump was positioned into the cover of a wooden stand containing a stainless-steel sieve (250 μm). This wooden stand with the sieve was positioned over a bucket into which filtered water flowed. The water that entered the bucket exited the site via a hose that was approximately 3 m in length. At 22 (of the 25) ice stations, water was manually pumped for at least 40 minutes thus ensuring that 1200 L of water was pumped at all sites, with the exception of two sites at which lower volumes  were pumped. Once pumping of water from beneath the ice was completed, the sieve was covered with aluminium foil, secured in the wooden stand and transported to the laboratory for further processing. At 3 (of the 25) ice stations, seawater could not be pumped from beneath the ice floe due to the incomplete penetration of the ice floe during drilling.This study was conducted onboard Swedish icebreaker Oden during the Arctic Ocean 2016 expedition  equipped with a polariser and camera (Q Imaging Retiga 2000R) and potential microplastics were identified based on characteristic features49. Potential microplastics from each sample were photographed, described according to form  and length measurements were taken prior to transferring to a clean filter paper. Potential microplastics were assigned to two broad categories  and to six length categories: 0.1–0.5 mm, 0.5–1.0 mm, 1.0–2.0 mm, 2.0–3.0 mm, 3.0–4.0 mm, 4.0–5.0 mm. Filter papers with potential microplastics from each sample were stored in clean, labelled petri dishes. All potential microplastics were analysed by Fourier transform infrared (FT-IR) spectroscopy on a Bruker Vertex 70 Infrared Spectrometer coupled to a Hyperion 1000 microscope according to a previously described method49. Briefly, each sample spectrum was compared with those of known standard polymers in the (i) Bruker Optics Attenuated Total Reflectance (ATR) Polymer and (ii) Synthetic Fibres ATR libraries. Samples which produced spectra with a match <60% were automatically rejected. All remaining spectra (>60%) were individually examined to ensure that there was clear evidence of peaks from the sample corresponding to known peaks of standard polymers. Overall, matches with >70% similarity were accepted while some between 60–70% similarity were accepted.The outer surface of each ice core was scraped off using a boomerang scraper. A stainless-steel hand saw was then used to cut each ice core into 10 cm vertical subsections. Subsections were placed into individual clean Ziploc bags (polyethylene) and allowed to melt for 24–48 hours. Once melted, the water from each subsection was transferred to a graduated cylinder and its volume measured. Each Ziploc bag was rinsed in triplicate with Milli-Q water to ensure that all particles were transferred out of the bag. Water from each sub-section was filtered under vacuum onto glass microfiber paper (GF/C); Whatman: 47 mm, pore size: 1.2 μm, using a Buchner funnel and a vacuum flask. Each filter paper was folded, placed into an aluminium foil packet and stored in a freezer (−20 °C) until further processing. The sieve that was used for filtering water from beneath the ice was rinsed in triplicate and all water was also processed in the same manner (vacuum filtration of water and collection of particles onto glass microfiber paper). Potential microplastics were identified and isolated based on a previously described methodSeveral measures were taken to minimise contamination of samples. In the field, (i) microplastic sampling was conducted upwind of all other activities, (ii) nitrile gloves were used when handling ice cores, (iii) the manual pump used at the ice stations was flushed with water prior to pumping seawater, and (iv) the stainless steel sieve that was used at the ice stations had a wooden cover affixed to it during filtration. In the lab, (i) ice processing was conducted on a wooden surface, (ii) the wooden work area was washed down with Milli-Q water in between processing of individual ice core subsections, (iii) all equipment  was washed with MilliQ water, (iv) lab coats, cotton clothing and gloves were worn during sample processing, and (v) all containers used during sample processing were cleaned using Milli-Q water. Checks were conducted to determine whether there was any contamination during sample processing. Clean petri dishes with filter paper were left exposed to the air during ice core and laboratory processing to determine if there was any airborne contamination. To determine whether there was any additional contamination during the processing of the melted sea ice, method blanks were conducted. For each method blank, 750 mL of Milli-Q water was placed into clean Ziploc bags and left for 24–48 hours. This water then underwent the exact processing as would have occurred for water from an ice core sub-section.28. So far, ICETrack has been used in a number of publications to examine sea ice sources, pathways, thickness changes and atmospheric processes acting on the ice cover cover30. For each ice core, input to the application included sampling date and location  while output included a plot of the estimated pathway as well as ancillary data associated with the pathway. Predicted sea ice thickness by a thermodynamic model and measured sea ice thickness was compared in order to assess the validity of the findings for the various sea ice cores. All maps were generated using Ocean Data View (ODV) Version 4.7.1050 and all graphs were generated using R version 3.4.451. Univariate analyses were conducted to determine whether (i) there were significant differences in microplastic concentrations among the sea ice cores  and, (ii) there were significant correlations between microplastic concentration and sub-section depth of the ice cores (Spearman’s Rank Correlation). Multivariate analysis, i.e. Principal Components Analysis (PCA), was conducted to provide further discrimination between the ice cores.Source areas and backward drift trajectories for the sea ice cores were estimated using the AWI ICETrack application. The lagrangian approach traces sea ice backward in time using a combination of satellite-derived low-resolution drift productsSupplementary Information.