Indicators of volcanism in ice cores

Master thesis Kasper Holst Lund mjb639 July, 2018

[14]

Center for Ice and Climate Niels Bohr Institute University of Copenhagen

Supervisors: Paul Travis Vallelonga Helle Astrid Kjær

Abstract

The work done in this project has been to optimize existing continuous flow analysis 2− + (CFA) techniques used for measurements of sulphate (SO4 ) and acidity (H ). The optimized techniques have been tested on six short firn cores drilled during a 456 km long traverse from the NEEM drilling site to the EGRIP drilling site and on the first 350 metres of the EGRIP ice core. The measured records have been used to determine spatial variability between the cores and to investigate the volcanic signals found in the ice cores. The sulphate technique developed by Röthlisberger et al. (2000) was optimized by exchanging the cation exchange column (CEC) to another type of CEC. This was done to try and reduce the flow problems created by the CEC. The chosen CEC was Bio-Rads Bio-ScaleTM Mini UNOsphere S Cartridge, this had no flow problems in conditions with low dust concentrations while it did show a slight drift with high dust concentrations. The acidity technique developed by Kjær et al. (2016) was optimized by exchange the absorption cell from a 2 cm z-cell to a 1 cm cuvette, this was done to lower the risk of air bubbles getting stuck in the cell. The cuvette handled air bubble a lot better and no problems with air bubbles getting stuck was encountered. The cuvette also improved the response time from 45 seconds to 36 seconds but the sensitivity of the technique was halved due to the lower path length. The sulphate technique was tested on three of the traverse cores but failed to produce any data due to a too high detection limit. The high detection limit is suspected to be due to old chemistry and parts in the setup. No other sulphate measurements were carried out. The acidity and conductivity measurements of the six traverse cores was able to clearly determine volcanic eruption across all of the core but only some of the eruptions showed up in multiple cores. The correlations found between the cores were low and no sig- nificant correlations were found in neither acidity or conductivity. Thus the spatial variation between the cores were quite high even in the big volcanic events. The low correlations are suspected to be due to post depositional effects and to errors in the dating of the cores. The acidity and conductivity measurements of the EastGRIP core also clearly deter- mined big events such as volcanic eruptions and wildfires. A comparison with the NEGIS core drilled very close to the EastGRIP core showed comparable peaks for most of the large events seen while the smaller features had quite some variation most likely due to post depositional effect and errors in the depth assignment. Two conductivity records were measured during the EastGRIP campaign a Bern and a Copenhagen record. A comparison shows that the correlation between the two records gets lower with time. This is most likely due to contamination from build up of par- ticles in the line going from the Bern to the Copenhagen system. This could lead to problems with aligning the records from the different parts of the system.

Acknowledgments

I would like to thank my supervisor Paul Vallelonga and unofficial co-supervisor Helle Astrid Kjær for thier advice and expert guidance throughout the work on my thesis. Both of them have offered a great amount of help with practical problems in the lab- oratory, by answering all my questions and by correcting my thesis. I would also like to thank Anders Svensson for taking time between being on field work and going on vacation to correct my thesis. This leads me to thank the entire CFA group for all the great discussions on our Monday meetings and the enjoyable environment during the melting campaigns. Thanks to Sam Black and Patrick Zens for good discussions, being good working part- ners and to Patrick for letting me use some of his work for my thesis. This leads to thanking all the people and institutions being part of the EGRIP melting campaign in Bern. They provided an enjoyable and professional environment in the laboratory and a lot of great discussion. Especially a big thanks to Tobias Erhardt and Camilla Maria Jensen for hosting and planning the campaign in Bern. Lastly I would like to thank the Center for Ice and Climate for having me making me feel as a part of the group immediately. I have enjoyed my stay at the center immensely and hope to meet all of the great people here again. The research leading to these results has received funding from the European Re- search Council under the European Community’s Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement 610055 as part of the ice2ice project. EGRIP is directed and organized by the Center of Ice and Climate at the Niels Bohr Institute. It is supported by funding agencies and institutions in Denmark (A. P. Møller Foundation, University of Copenhagen), USA (US National Science Founda- tion, Office of Polar Programs), Germany (Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research), Japan (National Institute of Polar Research and Ar- tic Challenge for Sustainability), Norway (University of Bergen and Bergen Research Foundation), Switzerland (Swiss National Science Foundation), France (French Polar Institute Paul-Emile Victor, Institute for Geosciences and Environmental research) and China (Chinese Academy of Sciences and Beijing Normal University).

Contents

Acknowledgments i

Contents ii

List of Figures iv

List of Tables v

1 Introduction 1 1.1 Ice cores ...... 1 1.2 Continuous flow analysis (CFA) ...... 5

2 Acidity in ice cores 12 2.1 Ionic balance ...... 12 2.2 Volcanic eruptions and their impact on climate ...... 12 2.3 Determination of pH ...... 15 2.3.1 Dielectric profiling ...... 15 2.3.2 Electrical conductivity measurements ...... 16 2.4 Continuous determination of acidity using optical dye method . . . . . 16 2.5 Continuous determination of sulphate ...... 18

3 Optimizing the CFA techniques for acidity and sulphate 21 3.1 Continuous detection of acidity ...... 21 3.1.1 Response time ...... 23 3.1.2 Sensitivity ...... 24 3.1.3 Acidity spectrum ...... 26 3.2 Continuous detection of sulphate ...... 26 3.2.1 Coasol ...... 28 3.2.2 Cation exchange column ...... 29

4 Ice core measurements: Traverse cores 33 4.1 Measurements ...... 33 4.1.1 Standard calibrations ...... 36 4.1.2 Spatial variation ...... 38 4.1.3 Volcanic eruptions ...... 42

5 Ice core measurements: EastGRIP 45 5.1 Measurements ...... 45 5.1.1 Standard calibrations ...... 46 5.1.2 Bern and Copenhagen conductivity comparison ...... 50 5.1.3 Volcanic eruptions ...... 53 5.1.4 Comparison with NEGIS shallow core ...... 58 CONTENTS iii

6 Discussion 61 6.1 Sulphate optimization ...... 61 6.2 Acidity optimization ...... 62 6.3 Spatial variability ...... 65

7 Conclusion 67

References 69

Appendix 74

iii LIST OF FIGURES iv

List of Figures

1 Flow of an ice sheet ...... 2 2 Map of drilling locations ...... 4 3 CFA schematic ...... 5 4 Melt head ...... 7 5 Debubbler ...... 8 6 Abakus ...... 10 7 Absorption and Fluorence ...... 11 8 Climatic impact of volcanic eruptions ...... 13 9 Schematic of pH setup ...... 16 10 Indicator dyes ...... 17 11 Schematic of Röthlisberger SO4 setup ...... 18 12 Schematic of Bigler SO4 setup ...... 19 13 Absorption cuvette ...... 22 14 Example of pH standard series ...... 23 15 Calibration curves of different absorption cells ...... 25 16 pH absorption as a function of wavelength ...... 27 17 Coasol test ...... 28 18 Test of CECs Ca removal ...... 30 19 Test of CEC flow ...... 31 20 Schematic of pH setup in Copenhagen ...... 33 21 Conductivity measurements from the traverse cores ...... 34 22 Acidity measurements from the traverse cores ...... 35 23 Calibration curves from the traverse cores ...... 37 24 Boxplots of the acidity and conductivity ...... 38 25 Modelled correlation pattern between the traverse cores ...... 41 26 Acidity events above 3 standard deviations in the traverse cores . . . . 42 27 Conductivity events above 3 standard deviations in the traverse cores . 43 28 Schematic of pH setup in Bern for EastGRIP melting ...... 46 29 Conductivity and acidity measurement from the EastGRIP core . . . . 47 30 Calibration curves from EastGRIP ...... 48 31 Histograms of calibration curves from EastGRIP ...... 49 32 Conductivity from Bern and Copenhagen system ...... 51 33 Correlation between the Bern and Copenhagen system ...... 51 34 Boxplot of the Bern and Copenhagen conductivity ...... 52 35 Diffusion in the conductivity signal ...... 53 36 Conductivity and acidity events above 3 standard deviations in the EastGRIP core ...... 54 37 Wildfire at 63.8 meters depth ...... 57 38 Wildfire at 89.5 meters depth ...... 57 39 NEGIS and EastGRIP ...... 58 40 NEGIS and EastGRIP comparison ...... 60

iv LIST OF TABLES v

41 Absorption cuvette ...... 64

List of Tables

1 Traverse cores ...... 4 2 Climatic impact of volcanic eruptions ...... 14 3 pH reagent ...... 17 4 Sulphate reagents ...... 19 5 Response times of the three different absorption cells ...... 24 6 Calibration parameters of pH standards with different absorption cells . 26 7 Ca standards with Coasol ...... 28 8 Bio-Rad cation exchange columns ...... 29 9 Mean of acidity in traverse cores A4, A5 and A6 ...... 36 10 Correlation of conductivity in traverse cores ...... 39 11 Correlation of acidity in traverse cores ...... 40 12 Acidity events above 3 σ in traverse cores ...... 44 13 Volcanic eruptions in each traverse core ...... 45 14 Correlation of conductivity between Bern and Copenhagen ...... 50 15 Biggest acidity events above 5 σ in the EastGRIP core ...... 56 16 Comparison of volcanoes in NEGIS and EastGRIP ...... 59

v 1. INTRODUCTION 1

1 Introduction

We are all interested in how the weather is going to change throughout shorter time periods of weeks or months. But this is not the complete picture some changes are not visible and happen over longer time periods. Some of them also have a tendency to recur and show a cyclical behaviour, the average of all this is what we call the climate of the Earth. The Earth’s climate system is complex and consist of five main components, the atmosphere, the hydrosphere, the cryosphere, the biosphere and the land lithology. These are all forced by external forcing mechanisms where the Sun is the most important but also the effect of human activities can be seen working as an external forcing. The importance of understanding the Earth’s climate system not only of the present, but also of the past and the future, can not be understated. Most importantly is probably to be able to predict how the climate is going to change in the future, this is done using climate models. To be able to predict what is going to happen in the future, understanding what happened in the past is important. The climate has been changing repeatedly throughout the history of the Earth, knowledge of these changes and how they altered the climate in the past may help with the prediction of what will happen in the future [Ruddiman 2014].

Different climate archives are being used to reconstruct the past climate of the Earth. These archives include lake and marine sediments, tree rings, speleothems, corals and ice cores. The different archives cover different periods of time and contain proxies of different climate parameters they also have very different resolutions. Sediments cover millions of years but often have a very low resolution, tree ring records gets as old as 14.000 years and give an annual resolution, speleothems can be used to reconstruct signals over thousands to hundreds of thousands years. Corals provide proxy data of time periods back to 500 million year ago, the resolution of corals records can be as good as monthly [Ruddiman 2014]. Ice cores have a varying resolution based on the temperature and location of the core. The accumulation rate and thinning of the ice sheet control the thickness of the annual layers, which in Greenland can be counted 60.000 years back. Ice cores cover back to 800.000 years in Antarctica and back to 125.000 years on Greenland [Cuffey and Paterson 2010].

1.1 Ice cores Ice cores are a high resolution climate archive with climate proxy data. Each year snow precipitates onto the ice sheets of Greenland and Antarctica, as more and more snow accumulates the layers from each year begins to compress. This process of accumu- lating snow and compression only happens in areas with insignificant surface melting typically close to the centre of the ice sheet . This imbalance of gaining mass at the centre and losing mass closer to the margins causes the ice flow from the centre to the margins. The reason why this is the case is due to the weight of the overlaying

1 1. INTRODUCTION 2

Figure 1: A simplified ice sheet which illustrates the ice flow towards the edges of the ice sheet. It also shows why the ice divide (I) is a good place to drill ice cores as the annual layers of ice. snow and ice and the flow of the ice. The layers accumulated each year stretches and becomes thinner and thinner the further down through the ice sheet, this can be seen in figure 1. These two above mentioned processes is the reason why the best location for drilling ice cores with long climate records going undisturbed far back in time is close to the ice divide. There should be no summer melting and the layers should be flat stretching only horizontally making it ideal for ice core drilling [Cuffey and Paterson 2010].

Ice cores contain quite a few different proxies, some of them are gasses trapped in the ice, water isotopes and impurities. They have well preserved annual layers that can be resolved 60.000 years back in time and cover time scales back to 125.000 years in Greenland and 800.000 years in Antarctica. This period covers multiple cold glacial stadials and warm glacial interstadials and show the rapid change between the two called Dansgaard-Oeschger events (DO events) in the Greenland ice cores. These events can be seen in a lot of the different proxies, like δ18O, dust, Calcium, Sodium and multiple others [Cuffey and Paterson 2010].

The information gained from the different proxies are of very different parts of the climate system, a short description of some of the proxies are following in the next section. Atmospheric gasses can be measured in small air bubbles trapped in the ice during the compression. These gases can be released from the ice by melting and then they can be analysed and shed light on the composition of the atmosphere in the past. Some of the greenhouse gases measured are carbon dioxide CO2 and methane CH4 both can be used in the estimation of future temperature as they show co-variation with past temperatures. Water isotopes can be used to estimate temperatures back in time by looking at the temperature gradient between the evaporation and precipitation site. δ18O can

2 1. INTRODUCTION 3 be used to determine the temperature at the precipitation site since they are linearly correlated and δD can be used to infer rapid changes at the evaporation site. They can be calibrated to the borehole temperatures measured in the borehole [Johnsen et al. 1989, Johnsen et al. 1995, Dahl-Jensen et al. 1998]. Many different impurities can be found in small concentrations in the ice cores, all of them proxies of various things. The amount of dust particles in the ice can be measured and used to infer about the wind, source area, vegetation cover and precipitation. The amount of dust in the ice cores increased in both hemispheres during the glacial compared to the Holocene. This is suggested to be caused by a reduction in precipitation and an increase in the wind speeds [Steffensen 1997]. Calcium (Ca2+) is one of the impurities arriving with dust, in Greenland this happens in the spring while in Antarctica it is a combination of a winter and a summer peak. The winter peak is sea salts from marine sources and the summer peak is from dust. The seasonal peaks in Calcium can be used for dating ice cores as they can be used to count annual layers in the ice [Cuffey and Paterson 2010]. Then there is Sodium (Na+) which is part of the sea salts in the ice core. Sea salts and sodium have a winter peak this might be caused by brine and frost flowers with high amounts of sea salt forming on the sea ice in combination with stronger winds. Sodium shows increases in the same cold periods as the dust but on a smaller scale [Cuffey and Paterson 2010]. + Ammonium (NH4 ) is an impurity connected to the biosphere it shows emissions from soil, bacteria and burning of biomass. This gives it an annual peak in summer on Greenland and also means it shows a reduction in colder periods unlike most other impurities. The reduction is due to the formation of the Laurentide and Fennoscandian ice sheets over the land masses where the emission of ammonium normally happens. Big forest fires shows up very clearly in ammonium data with a peak much bigger than the summer value [Cuffey and Paterson 2010]. Another quantity measured is the acidity which can be used to identify volcanic eruptions. The volcanic eruptions release a lot of SO2 into the atmosphere which is 2− dissolved to SO4 and then precipitated on the ice sheets giving a very acidic layer. The acidic layers can be used to align different ice cores since they all have the acid peak at the same time. If the eruption is big enough and covers the entire globe it can even be used to align ice cores from Greenland with ice cores from Antarctica [Cuffey and Paterson 2010]. 2− Part of the particles from the volcanic eruptions is sulphate (SO4 ), thus sulphate can also be used to determine when volcanic eruptions happened.

To be able to infer anything about the past climate using ice cores they need to be dated accurately. Without the dating it can not be determined when different events found in the measurements happened and different ice cores can not be compared to each other. Dating of ice cores is done in a combination of counting layers using annual cycles, flow modelling, relative amount of Oxygen over Nitrogen molecules in the air

3 1. INTRODUCTION 4

Figure 2: Map showing deep ice core drilling sites and the intermediate Renland site in Greenland in blue and the locations of the shallow cores drilled on the 2015 traverse from NEEM to EGRIP in red. relative to summer insolation, reference layers such as volcanic eruptions, wild fires and DO events and cosmogenic isotopes such as 10Be and 36Cl [Cuffey and Paterson 2010].

Multiple deep and shallow ice cores have been drilled in both Greenland and Antarc- tica, some of the Greenland drill sites can be seen in figure 2. In this project six shallow ice cores drilled on the 2015 traverse from the deep drilling site NEEM 77.27N 51.03W to the new deep drilling site EastGRIP 75.37N 35.59W have been measured and analysed, locations and lengths can be seen in table 1. The first 350 metres of the EastGRIP deep ice core drilled in the summer of 2016 have also been measured and analysed for this project. The EastGRIP measurements was done in the CFA labora-

Core Lat (deg) Lon (deg) Depth (cm) Elevation (m) A1 77.25N 51.09W 907.7 2484 A2 77.01N 47.28W 1073.5 2620 A3 76.27N 44.27W 1097.2 2771 A4 75.41N 36.28W 1090.9 2760 A5 75.37N 35.58W 1401.8 2701 A6 76.10N 41.05W 1207.1 2708

Table 1: Latitude, longitude, depth in cm (field measurements) and elevation of the 2015 traverse cores.

4 1. INTRODUCTION 5

Figure 3: A simplified schematic of a continuous flow analysis (CFA) system. The ice is melted in the freezer and the melt water is spilt into an inner and an outer stream. The inner stream gets pumped through a debubbler and is then split into multiple detection lines. These lines can be absorption or fluorescence where a reagent and sometimes a buffer is added or conductivity (Cond) and dust (Abakus) which is measured on the sample line (Inspiration from Kjær 2010). tory in Bern Switzerland while the six traverse cores were measured in the Copenhagen CFA laboratory.

1.2 Continuous flow analysis (CFA) Continuous flow analysis is a measurement technique used on ice cores. It is an im- provement to conventional chemical analysis, as it offers less risk of contamination due to reduced handling of the ice core, a higher temporal resolution and less time required to do the measurements. This section contains a general overview of a CFA system based on the Copenhagen systems and differences between the Copenhagen and Bern system, the other system used for measurements in this project will be mentioned.

A CFA system normally contains a melt head in an actively cooled environment. The melt head continuously melts the ice core and separates the sample into two or more streams, a possibly contaminated outer stream going to waste (or to systems less sen- sitive to contamination eg. water isotopes) and an inner clean section used for the sensitive chemical analysis. The inner stream is pumped through a debubbler where

5 1. INTRODUCTION 6 the air trapped in the ice is separated from the water. This is done to not have air bubbles blocking the measurement lines and to keep the flow more steady. The dis- carded air can be used to do continuous measurements of gases if desired. When the air has been removed the sample water is split into multiple measurement lines for detection of the different impurities. There is usually a low flow of about 1 mL/min in the lines because of the small quantities of impurities. The different ions are measured after adding reagent and sometimes a buffer using either absorption or fluorescence techniques [Sigg et al. 1994, Röthlisberger et al. 2000, Kaufmann et al. 2008]. Con- ductivity and dust can be measured on the water stream without adding any reagents or buffers. There are also methods not using absorption or fluorescence, an example is black carbon detection [McConnell et al. 2007]. Sometimes discrete samples are gathered in vials to do discrete measurements using possibly an ion chromatograph. In figure 3 a simplified schematic of a CFA system is shown.

Melt head

The melt head needs to have some crucial features to work optimally. The surface of the melt head needs to be coated in a material that does not react with any of the impurities in the ice. It should also be able to split the sample into a clean inner stream and a possibly contaminated outer stream and should also avoid mixing as much as possible. The first part of not reacting with the impurities is achieved by using materials for the melt head that are chemically inert. This can be achieved in multiple ways including aluminium coated with PTFE [Sigg et al. 1994, Röthlisberger et al. 2000] or by using copper plated with nickel and coating it with a thin layer of gold afterwards [Kauf- mann et al. 2008]. Both the melting campaign of the traverse cores and the EastGRIP core used a gold coated melt head. To split the sample into a clean inner and a contaminated outer section a wall of 0.5 to 1 mm height is placed on the melt head separating the inner and the outer part. There is also less suction on the inner section than needed to drain all the water. This creates an overflow of about 10% from the inner to the outer section, thus lowering the risk of contamination on the inner stream. Typically the melt head is heated to somewhere between 15 and 48 ◦C, the needed temperature depends on the time resolution wanted and how many compounds that are measured. The lower the melt speed the better the resolution but fewer compounds can be analysed due to the amount of water going through the system. Shallow cores typically consist of mostly snow and firn, when melting snow and firn it can be beneficial to add a small disk onto the inner section of the melt head to create a layer of water between the melt head and the disk. This layer of water prevents air from being sucked into the system, and since firn cores have more air pores in them there can possibly be access to ambient air through the pores, so it is important to reduce the risk of getting air in the system. Also for firn melting it is important to have narrow radial slits in the melt head to make the capillary forces in the melt head

6 1. INTRODUCTION 7

Figure 4: Figure showing the melt head used in the Copenhagen and Bern CFA laboratories. Showing the separation of the inner and outer section and the location of the drain channels (DC) and heating cartridges (CH). Figure from Bigler et al. (2011) stronger than in the ice. This is done to prevent percolation of water up into the ice core which would reduce the temporal resolution [Röthlisberger et al. 2000, Bigler et al. 2011]. A schematic of the Copenhagen melt head can be seen in figure 4.

Encoder

When the ice core is placed on the melt head a weight is placed on top of the ice. This is done to stabilize the melt speed which is controlled by the temperature of the melt head. The melt speed can be measured by an optical encoder, the encoder measures the movement of a string connected to the weight on top of the ice [Sigg et al. 1994]. This method works well and gives a high precision when measuring one bag at a time, a bag is a piece of the core with a length of 55 cm. If bags are stacked continuously the weight on top of the ice has to be lifted from the ice. This leaves a period during the stacking where the melt speed can not be measured. Another way to measure the melt speed is to use image recognition. This is done by placing a camera facing the side of the ice core and have it recording a image each second and determine how fast the ice is moving based on the pictures. This removes the problem with stacking since the melt speed is recorded from the side of the ice

7 1. INTRODUCTION 8

Figure 5: Illustration of the debubblers used to separate the air and the water in the sample stream. (a) is an open debubbler as the one used in Bern and (b) is a sealed debubbler like the one used in Copenhagen. Figure (b) from Bigler et al. (2011). core and not the top. Both the Copenhagen and the Bern laboratory uses an optical encoder and in Copenhagen a camera is used aswell [Röthlisberger et al. 2000, Bigler et al. 2011].

Debubbler

The sample stream coming from the inner section is pumped through a debubbler. The debubbler separates the around 10% air trapped in the ice core from the water. There exist different kinds of debubblers, the first one developed is an open debubbler usually made from a pipette tip with the tip cut off. The water stream drips into the top of the pipette tip and the water is then sucked out of the bottom hole while the air is released to the surroundings figure 5 (a). When methods of continuous gas measurements were invented a new type of debubbler was developed since the air from the ice now needed to be saved for measurements. A sealed debubbler was designed by Bigler et al. (2011), it consist of a triangular cell with one inlet and two outlets, one for water and one for gas figure 5 (b). The internal volume of the debubbler is important since mixing can occur inside, thus a smaller volume reduce the mixing in the debubbler. It is easier to control the internal volume in the sealed debubblers since they are contained by the geometry while the open de- bubblers mixing volume varies with the flow rate and amount of air in the sample. In Copenhagen a sealed debubbler is used and the inner volume of it depends on the study.

Detection methods

After the sample has passed through the debubbler and the air and water have been separated, the water and air samples are pumped to different detection systems. These detection systems analyse the samples for various environmental and climate proxies.

8 1. INTRODUCTION 9

The greenhouse gas methane (CH4) is measured in the air sample, else the air is just released to the laboratory. The water stream is split into multiple lines, two measure- ments are almost always done since the methods are non destructive, which means the sample can be used for other measurements afterwards as well. These two measure- ments are the conductivity and dust concentration. After the conductivity and dust measurements the water sample continues through to other detection systems. Commonly these systems use either an absorption or a fluo- rescence method, other techniques include black carbon and ring down spectroscopy of stable water isotopes. An ICP-MS can also be connected to the system for measuring multiple elements on the same line and often discrete sampling of the sample is done as well. The discrete samples reduce time spent on preparation compared to discrete sample taken directly from the ice core. A short introduction to some of the chemical detection systems will be given below.

Conductivity

The conductivity measurement is based on the melt water electrolytic conductivity (MWEC). This gives a total signal from all the ions found in the ice core. What is dominating the conductivity signal varies depending on where the ice core is drilled. In Antarctic coastal ice the conductivity signal is dominated by the sea salts as a lot of Cl− and Na+ is present. While in Greenland the conductivity is dominated by Ca2+ as the dust signal is more prominent than eg. sea salts. The conductivity method has a very high temporal resolution and is as mentioned earlier a non destructive method, which makes it possible to use up stream of other detection systems. If multiple sys- tems have a conductivity meter in front of them, the conductivity data can be used to align the other measurements and make the depth assignment of them easier. 2− Volcanic eruptions will show up as big peaks in the conductivity as the sulphate (SO4 ) from the volcanic eruptions increase the conductivity in the ice greatly [Röthlisberger et al. 2000], thus conductivity can be used together with other compounds to deter- mine when volcanic eruptions happened in the past.

Dust

The concentration and sizes of dust particles in the ice core is measured using an Abakus (from Klotz GmBH). The Abakus works by having the water stream go through a narrow channels where only one particle at a time can pass. The amount of particles passing is measured using a laser (670 nm) shining light orthogonal onto the water stream with a detector on the other side, each time the laser light is cut off a particle has passed, an illustration of the principle can be seen in figure 6. The Abakus is measuring how many particles pass per second, to convert this to number of particles per length unit, a precise measurement of the flow is needed. To get a precise flow measurement a flow meter is usually placed right in front of just after the

9 1. INTRODUCTION 10

Figure 6: Illustration of how the Abakus detects passing particles. Inspiration from Ruth et al. (2003)

Abakus [Ruth et al. 2003]. The size of the particles is determined by detecting the scattered light and comparing the Abakus measurements to a Coulter counter. A Coulter counter is a more precise method of measuring particle size distribution using discrete samples [Simonsen et al. 2018].

Absorption and fluorescence

The absorption and fluorescence methods requires that a reagent and for some chemical ions also a buffer is introduced into the sample stream. This is done to create the reaction that can be measured using absorption and fluorescence. The absorption method works by creating a reaction in the sample stream where it changes colour based on the amount of the desired ions. Then the quantity of light absorbed by the sample is measured and based on this the number of the ions can be determined. The equation used to calculate the absorbance (abs) is Beer-Lambert equation given by:

 I  −log10 = ε · l · c = abs (1) I0

Where the intensity of the incoming light is I0 and the fraction not absorbed by the sample is I, the path length of the wave guide the light passes through is l and is in centimetres and it can be seen that by increasing the path length the detection limit should improve. Also c is the molar concentration in moles per liter (M) and ε is the wavelength dependent molar absorptivity to base 10 in M −1cm−1. The factor ε · l can be determined by introducing standard solutions with a known concentration into the system. Then the difference in the absorption can be determined by comparing the how much light is absorbed with the standard solutions or ice going

10 1. INTRODUCTION 11

Figure 7: Upper row shows absorption and lower row shows fluorescence. Panel a and d is raw date from a 110 cm ice core and parts marked as B is the MilliQ water or blank sample. Panel b and e are show standards used for calibrations and c and f are calibration curves calculated from the standards. Figure from Kaufmann et al. (2008) through versus clean MilliQ water in the system. In figure 7 a-c the calibration steps of the absorption method can be seen with raw data (a), standard solution with know concentration (b) and calibration series (c). Some of the common ions measured using absorption are Sodium (Na+) [Röthlisberger − 2− et al. 2000], nitrate (NO3 ) [Röthlisberger et al. 2000], sulphate (SO4 ) [Bigler et al. 2011, Röthlisberger et al. 2000] and H+ [Kjær et al. 2016].

Fluorescence techniques work by exciting photons to a higher energy state in the molecules. Then when the molecule decays to a lower energy state a photon is emit- ted and the emitted photons energy is different from the absorbed photon, thus the emitted photon can be detected without interference from the excitation process since it happens at different wavelengths. The fluorescence techniques are similar to the absorption techniques in the matter of introducing a standard of known concentration to do calibration. Some of the ion measured by fluorescence are peroxide (H2O2) [Sigg et al. 1994], formaldehyde (HCHO) [Sigg et al. 1994], Calcium (Ca2+) [Röthlisberger et al. 2000] + and ammonium (NH4 ) [Sigg et al. 1994].

11 2. ACIDITY IN ICE CORES 12

2 Acidity in ice cores

The acidity of an ice core is crucial for several reasons. It is part of the ionic budget and thus precise measurements of the acidity content in the ice are necessary for deter- mining the original composition of chemical ions precipitated on the ice sheet. Most important is the connection between high acidity peaks and volcanic eruptions. The sulphate from the volcanic eruptions deposited on the ice sheets leave highly acidic layers, these layer can be used to assign precise ages to the ice using records of known volcanic eruptions in recent times. This is very important for constraining the dating of ice cores. The volcanic eruption layers can also be used to align different ice cores as these layers with high acid concentrations are the same across different ice cores. This is especially important for the dating of central Antarctic ice cores, the amount of precipitation in central Antarctica is much lower than in Greenland, thus annual layers can not be counted. Then the dating from Greenland ice cores can be transferred to the Antarctic cores using volcanic eruptions. This does however require the eruption to be large enough to have an effect on both hemispheres.

2.1 Ionic balance The acidity in the ice is important for the ionic balance as it affects the processes governing the balance. The ionic balance is the balance of anions and cations in the ice, this balance is affected by processes happening after the snow has been precipitated onto the ice sheet. These processes include molecular diffusion in the snow and ice and volatilization of organic acids together with condensation and sublimation. To have a balance in the ions the cations and anions needs to be balanced and ∆C in equation 2 should be zero. Thus knowledge of concentrations of as many ions including acidity in H+ is important to gain knowledge of the ionic balance.

+ + + + 2+ 2+ ∆C = Na + NH4 + K + H + 2Ca + 2Mg − − − 2− − − − (2) −F − Cl NO3 − 2SO4 − CH3SO3 − HCOO CH3COO

2.2 Volcanic eruptions and their impact on climate It is important to have a high precision and reliable record of volcanic eruptions to understand past climate. This is needed because volcanic eruptions can have a signifi- cant impact on the climate, they influence multiple parts of both weather and climate as seen in figure 8 and table 2. One way of achieving such records is from ice cores, where volcanic eruptions show up as big spikes in both acidity and sulphate. Volcanic eruptions introduce large amounts of particles and gases into the atmosphere. The temporal effect of volcanic eruptions on the climate varies. This is because the substances stay in the atmosphere for different amounts of time, some for short periods like chloride and particles, some for a few years like sulphuric compounds and other

12 2. ACIDITY IN ICE CORES 13

Figure 8: Illustration of the parts of the climate system influenced by an explosive volcano. Figure from Fischer (2006)

stay for long periods of time, these include CO2 and N2 [Robock 2000].

The most influential effect of volcanic eruptions is the large amounts of SO2 which − reacts with OH and H2O to form H2SO4 in the atmosphere. This leads to a cooling effect by blocking short wave radiation. The ash particles have a big effect on the di- urnal cycle, albedo and amount of nutrients by making a layer in the atmosphere that blocks both the out going and incoming radiation. This effect is short lived though as the particles will typically be gone from the atmosphere within a few days. The blocking of the radiation has a large local impact but the global effect is minimal [Robock 2000]. The troposphere and stratosphere are affected by sulphate aerosols and sulphuric com- pounds released into the atmosphere. The troposphere is cooled due to higher albedo, this lead to a decrease in evaporation and a reduction in precipitation. The decrease is more pronounced in the tropics. In the stratosphere the temperature is increased due to absorption of infrared radiation, the temperature increase is higher in the trop- ics than at the poles. This gradient in the temperature increase leads to changes in the wind pattern in the stratosphere, these changes leads to warming in the Northern Hemisphere during winter [Robock 2000]. Also in the stratosphere, the sulphate takes part in a chemical reaction creating chlorine which is damaging the ozone protecting

13 2. ACIDITY IN ICE CORES 14

Effect Mechanism Onset Duration Blockage of short wave and emission of long Reduction of diurnal cycle Immediately 1-4 days wave radiation Blockage of short wave radiation, reduced Reduced tropic precipitation 1-3 months 3-6 months evaporation Summer cooling of NH tropics Blockage of short wave radiation 1-3 months 1-2 years and subtropics Stratospheric absorption of short wave and Stratospheric warming 1-3 months 1-2 years long wave radiation Winter warming of NH Stratospheric absorption of short wave and one or two 1/2 year continents long wave radiation, dynamics winters Global cooling Blockage of short wave radiation Immediately 1-3 years Global cooling from multiple 10-100 Blockage of short wave radiation Immediately eruptions years Dilution, heterogeneous chemistry on Ozone depletion, enhanced UV 1 day 1-2 years aerosols

Table 2: List of different impacts on the weather and climate of explosive volcanic eruptions. Table modified from Robock (2000). the surface from UV radiation [Robock 2000].

As mentioned earlier the detection of volcanic eruptions is important for dating and cross dating ice cores. Identifying the eruptions can be done using acidity, sulphate or volcanic ash (tephra), the tephra can be used to determine which volcano the ash is from by comparing the geochemical composition of the ash to ash which is known to be from a specific volcano. These records of acidity, sulphate, DEP and ECM can then be used to constrain the dating or to cross date multiple ice cores. The high accuracy of the dating in Green- land ice cores due to the possibility of counting annual 60.000 years back, can then be used to find precise ages of volcanic eruptions older than the records of known eruptions. This can then be used to constrain the ages of other ice cores where the same eruptions are present. Using these reference layers the GICC05 time scale has been extended to cover most of the deep ice cores drilled in Greenland [Svensson et al. 2006, Rasmussen et al. 2013]. Having a universal time scale for the Greenland ice cores makes it possible to compare high resolution time series of other climate parameters of different ice cores.

An index of estimated strength of volcanic eruptions based on acidity and sulphate measurements from ice cores exist. It is called the ice core volcanic index (IVI) [Gao et al. 2008] this can be used as an alternative to the often used volcanic explosivity index (VEI). The high resolution temporal resolution of the ice cores makes IVI able to identify what has previously been thought as one eruption is actually multiple erup- tions. The location of the ice cores means that the IVI is influenced more heavily by high latitude eruptions [Robock 2000].

14 2. ACIDITY IN ICE CORES 15

2.3 Determination of pH A variety of methods exist for the determination of pH, these include a pH meter which takes the concentration of ions and turn that into a electrical signal and then can be calibrated using standards of known pH. The use of colour sensitive indicator dyes, where the indicator dyes change colour when the pH changes. The dyes are usually sensitive to a range of 2 pH units, so multiple dyes are required to cover a broad part of the pH spectrum. Another method is titration where a standard solution of known concentration is slowly added to the sample until it reaches an equivalence point of known pH. Then the amount of acid/base added to the sample is known and the pH of the sample can then be calculated.

Methods for determining the pH also exist for melt water from the ice. Using any of these methods the problem of ambient or dissolved CO2 in the ice needs to be taken into account. There are multiple methods including determining the conductivity of the melt water which is similar to the ECM and DEP methods in that it measures other things than the acidity. There is also a method for finding the ionic balance, this can be done by determining the concentration of ions using CFA absorption and fluorescence methods or by ion chromatography (IC). Another method by Legrand et al. (1982) uses titration of discrete samples, the problem of CO2 is fixed by remov- ing the CO2 from the sample by lowering the pH of the sample. Both Pasteris et al. (2012) and Gfeller (2011) came up with methods for detecting pH using an electrical probe, and they controlled the CO2 problem by calibrating the sample with a known concentration of CO2. A CFA method for determining pH use indicator dye by Kjær et al. (2016), the next section will go through this method as it is the one used and optimized in this thesis. Some methods for direct determination of H+ concentration on snow and ice are reg- ularly used. These include dielectric profiling (DEP) and electrical conductivity mea- surements (ECM). Of these methods only ECM determine acidity only, DEP measure + not only the H ions but also all other present ions especially NH4 and both of them require correction for density since the measurements are influenced by the air in be- tween the snow and ice crystals.

2.3.1 Dielectric profiling The DEP method determines the capacitance and conductance of the ice by sending an alternating current through the ice between two electrodes. The influence in DEP is mostly from acidity H+ with the effect of sea salts (Cl− and Na+) being seven times lower and there should not be an influence from Ca+. To correct for density the pore volumes and the H2SO4 concentration needs to be known [Wolff et al. 1997; Barnes et al. 2002].

15 2. ACIDITY IN ICE CORES 16

2.3.2 Electrical conductivity measurements ECM determines the conductivity in the ice, this is measured by dragging two 1000 V electrodes along a flat surface of the ice prepared with a sharp knife. Volcanic erup- tions show up very clearly in the signal as the acid dominates the signal. The only cation found to have an effect on the ECM measurement except for H+ is Ca+ and in glacial samples from Greenland with a lot of dust it is not easy to determine the H+ signal. The air in the sample reduces the conductivity and this can be corrected for if the density of the ice is known [Hammer et al. 1980, Wolff et al. 1997].

2.4 Continuous determination of acidity using optical dye method A method for continuous measurement of acidity in ice cores has been developed by Kjær et al. (2016), the method can be seen in figure 9. The method is an optical method that uses indicator dye chosen to match the pH measured in ice cores (4.49 to 6). The spectra of the dye should change based on the changes in the pH of the sample. To create the reagent a 1:1 mixing ratio of the indicator dyes bromophenol blue (from yellow at pH 3.0 to blue/violet at 4.6) and chlorophenol red (from yellow at pH 4.8 to violet at 6.7) (figure 10) is mixed with Brij L23 and diluted into MilliQ water, the volumes/masses used can be seen in table 3. The combination of a sample flow rate of 0.9 mL/min to 0.15 mL/min of reagents was found to give the best concentration of dye for the detection. The lower amount

Figure 9: Illustration of the CFA method for acidity detection by Kjær et al. (2016). Sample is being pumped from the debubbler (not shown) and spilt into the pH sytsem (Sa) and other measurement systems (DO). Dye indicator reagent is added (Dye), it is mixed in a 65 C◦ heat bath and an accurel (Ac) removes air bubbles before detection in the absorption cell. Figure modified from Kjær et al. (2016)

16 2. ACIDITY IN ICE CORES 17

Substance Volume/Mass Bromophenol blue 0.025 g Chlorophenol red 0.025 g Brij L23 (30%w/w) 100 µL MiiliQ water 500 mL

Table 3: Table of composition of the reagent used in the Kjær et al. (2016) CFA sulphate detection systems. of dye to sample also reduces the dilution of the sample. To get a better mixing of the sample and reagent it is mixed in a one metre long mixing coil kept at 65 C◦ to avoid possible influences from variations in the temperature. During the heating in the mixing coil air bubbles might form, these air bubbles are removed by sending the sample through a six cm long accurel membrane, this is a gas permeable membrane in which the air can escape but liquid is confined. The reason the Brij L23 is added to the reagent is that of lowering the risk of air bubble getting stuck in the absorption cell if they get past the accurel. The absorption cell has a 2 cm light path length. The light source used is a white LED (6000 mcf, 18◦ dispersion, FIA lab Inc. USA) and the spectrometer used to measure the intensity of the light is an Ocean Optics USB 2000. The best wavelength for measurements is

Figure 10: List of different commonly used indicator dyes, showing the colour variation and pH range. The dyes used for this method is bromophenol blue (3.0 yellow to 4.6 blue/violet) and chlorophenol red (4.6 yellow to 6.7 violet). Figure from Cha (2014)

17 2. ACIDITY IN ICE CORES 18

Figure 11: Schematic of the CFA system for sulphate detection developed by Röthlis- berger et al. (2000) In the top left is a selection valve where it is possible to choose between sample, standard solution (St) or baseline (B) Then a cation exchange column (CEC) is used to remove Ca from the sample and reagent and NaOH is added before detection. Figure from Röthlisberger et al. (2000)

589 nm and with a second wavelength at 450 nm. The two measurement wavelengths respond oppositely to variations in pH but have the same response to flow changes. Thus a comparison of the two wavelengths can be used to analyse if there has been any changes in the flow.

2.5 Continuous determination of sulphate Sulphate is another way to detect volcanic eruptions and the strength of them using ice cores. This can be done in various ways, two different CFA methods exist, or de- tection can be done using ion chromatography or by using inductively coupled plasma mass spectrometry (ICPMS). The following will be a description of the two available CFA methods. The first CFA method was developed by Röthlisberger et al. (2000), schematic of the method can be seen in figure 11. The method is based on a reagent consisting of a 1:1 mixture of methylthymol blue (MTB) and barium chloride (BaCl2) mixed with hydrochloric acid (HCl) and ethanol, the concentrations used in the reagent can be seen in table 4. A competitive reaction between sulphate and MTB with the barium can be measured at 608 nm and it gives a decrease in the absorption with an increase in sulphate. Other cations will interfere with the reaction of sulphate, to avoid this a cation exchange column (CEC, 1 cm, 3 mm i.d., Dowex 50WX4, Na+ form, 100-200 mesh, Fluka) is used. The CEC needs to be regenerated daily, this is done using a 20% NaCl solution to flush through the column. The reaction with MTB and barium only happens at high pH, thus a NaOH solution (0.066 M in ethanol 44%) is added before the absorption cell. A narrow teflon coil is used after the detector to create a high back pressure to reduce formation of air bubbles in the detector. The lamp used for the absorption is a phosphor coated mercury lamp with interference filter. The limit of detection (LOD) achieved with this setup is 20 ppb but during measurements the LOD was higher at a 100 ppb. The detection limit is highly sensitive to the 1:1 mixing

18 2. ACIDITY IN ICE CORES 19

Substance Conc./Volume Röthlisberger method reagent Methylthymol blue 0.09 mM BaCl2·2H2O 0.09 mM HCl 6 mM Ethanol 86% Bigler method reagent DMS-III 80 µM BaCl2 56 µM KNO3 (1 M) 5 mL Chloroacetic acid (1 M) 10 mL Sodium chloroacetate (1 M) 10 mL Ethanol absolute 700 mL

Table 4: Table of composition of the reagent used in the Röthlisberger et al. (2000) and Bigler et al. (2007) CFA sulphate detection systems. ratio of MTB and BaCl and slight deviations will result in a worse LOD. The flow rates also influence the detection limit, thus small variations in the flow will also lead to a worse LOD. This detection limit is higher by 2-10 times of the lowest concentrations expected in Greenland. The method shows a linear behaviour up to at least 2000 ppb, which is lower than the values expected to be found in ice cores. The method has a short response time of 20 seconds. It has successfully been used by Bigler et al. (2002) on the Greenland firn cores B18, B20, B21 and the entire glacial period of the NGRIP core. The lowest concentrations could not be detected but volcanic eruptions were successfully determined.

The other CFA method is developed by Bigler et al. (2007) this method can be seen in figure 12. This method uses dimethylsulfonazo III (DMS-III) as an indicator to react

Figure 12: CFA sulphate detection system developed by Bigler et al (2007). It includes a CEC for removal of cations, a debubbler to remove excess air and a barium sulphate reactor column. Figure from Bigler et al. (2007)

19 2. ACIDITY IN ICE CORES 20 with the sulphate. This method also uses a cation exchange column CEC, 15 cm, 1.6 mm i.d., Dowex 50WX8, Na+ form, 75-150 mesh, Fluka) to remove the inferring cations such as Ca2+ and Mg2+. It also uses a reactor column with barium sulphate particles of 15 cm length and with a inner diameter of 1.6 mm. This reactor column increases the efficiency and reproducibility of the mixing and reaction of sample and reagent. The wavelength found to give the maximum absorbance was by integrating the signal over the interval 654-663 nm. This gives a limit of detection of about 70 ppb which is higher than the desired limit for Greenland ice cores. The linear behaviour of the method has an upper limit of about 3000 ppb which is still to low to include all expected signals for Greenland ice cores. Both methods work for continuous determination of sulphate and thus volcanic erup- tion, but the LOD is to high to get low concentration features. None of the methods are very robust and they are both time consuming. But they can still be used in com- bination with acidity measurements to get a more precise determination of volcanic eruptions.

20 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 21

3 Optimizing the CFA techniques for acidity and sulphate

Work done using the continuous detection techniques for acidity and sulphate have shown that both techniques can be somewhat optimized. The acidity technique has problems with air bubbles, the accurel membrane is not enough to remove all the air bubbles formed during the reaction between the sample and reagent. This leads to air bubbles getting to the absorption cell where they some time get stuck in the light path and lower the signal of the absorption. The sulphate techniques both have problems with flow changes during measurements. These flow changes lead to changes in the absorption and is thus altering the calibration sensitivity. The columns used in both techniques is most likely the cause of these flow changes due to particles accumulating in them blocking the sample stream.

3.1 Continuous detection of acidity One of the main methods for detection of time and strength of past volcanic eruptions in ice cores is the continuous detection of acidity. The method for determining acidity is the continuous detection technique developed by Kjær et al. (2016). This technique works very well but it has at least one problem, and that is air bubbles. The reaction between the indicator dyes and sample creates air, this production of air is amplified by the heat bath which heats the sample plus reagent stream to 65 C◦ to improve mix- ing. The accurel membrane is part of the system to remove this air, but the accurel can not always remove all the air bubbles. This can cause problems in the absorption cell, it is possible for the air bubbles to get stuck in the light path when they are going through the cell. When an air bubble gets stuck it blocks some of the light, and thus lowering the signal. In between the publication of the original technique and this project an attempt to fix this problem was implemented in the system. The accurel membrane was replaced by a multi channel vacuum degasser (IDEX HEALTH & SCIENCE LLC.), the vac- uum degasser works by the same principle as the accurel membrane by removing gas through a gas permeable material. The vacuum degasser does a few things better than the accurel membrane, the gas permeable membrane in combination the vacuum created by a vacuum pump allows for higher efficiency in the degassing process than the accurel membrane can give. The gas permeable membrane is sensitive to being squeezed and in the vacuum degasser the membrane is hidden in a box, which means it can not be squeezed, while the accurel just laying on the laboratory table is at risk of squeezing. If the membrane gets squeezed it will not hold the liquid of the sample stream completely and will begin to leak. No quantitative test of the effect of the vac- uum degasser has been made, but based on experience of experimenters the vacuum degasser does reduce the amount of air bubbles reaching the absorption cell.

Even with the vacuum degasser air bubbles still reach the absorption cell and some-

21 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 22

Figure 13: Cross section of an absorption cuvette with a flow-through cell, with a 1 cm path length. times gets stuck lowering the absorption signal. This is not optimal as this changes the signal and if the bubble is not noticed quickly a lot of data can be lost. For this project, a new kind of absorption cell is tested. Instead of the z-cell (figure 9) an absorption cuvette flow-through cell like the one seen in figure 13 is used. The cuvette will not fix the problem of bubbles reaching the absorption cell, but air bubbles should not get stuck in the cuvtte like they do in the z-cell. One down side to the cuvette is that its light path is only 1 cm compared to the 2 cm of the z-cell, thus the cuvette should have only half the sensitivity of the z-cell given by Beer-Lambert equation 1. If the absorption cuvette is to be used it needs to not have air bubbles get stuck in the light path, have a sensitivity of at least half of the 2 cm z-cell, have a response time better or the same as the 2 cm z-cell and the detection limit should be at least as good as the 2 cm z-cell detection limit. To test the sensitivity and the response time standard series where done. Four standards were made and tested on not only the cuvette but also the 2 cm z-cell and a 1 cm z-cell to compare. Three series of four standards were done on different days for all three cells with different strengths of the standards. Test 1 had the standard concentrations of 1.0 µM, 2.1 µM, 4.1 µM and 8.2 µM, while test 2 and 3 had the concentrations 2.5 µM, 4.9 µM, 9.8 µM and 19.4 µM. The measurement of the 2 cm z-cell for test 2 went badly. This could be due to problems during the standard series run, it could possibly be an air bubble stuck in the detection cell lowering the signal. Due to this it can not be compared to the other cells. The standard of test 3 with the cuvette can be seen in figure 14 as an example on a standard series.

22 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 23

Figure 14: pH standard series during test 3 using the cuvette as the absorption cell. The concentration of each standard is marked above the corresponding plateau.

The amount of air bubbles getting stuck in the detection cell is a hard thing to do a quantitative test of without melting actual ice cores. Thus this part will not be tested until actual measurements are done as ice cores are hard and expensive to acquire. A possible artificial test could be to pump two lines one with water and one with air. If this has to come close to recreate what is seen in actual ice cores to amount of air pumped in should not be too high. Using this method it should be possible to test whether air bubbles will get stuck in the cuvette.

3.1.1 Response time The response time of the system is a measure of the temporal resolution of the detec- tion technique. The temporal resolution is important to understand the limitations of the technique, the better the resolution the more features will be measured and this is important for doing continuous measurement of ice cores. The response time is determined as the time it takes to go from 5 % above the current plateau to 95 % of the next plateau of the measured signal. Thus the better the response time is the steeper the slope between plateaus are and narrower peaks can be detected when measuring. The determination of response time is done on standard series, so as an example from figure 14 it is the time to go from 5 % above the 2.5 µM level to 95 % of the 4.9 µM level. The time resolution found using the response time can also be used to calculate the depth resolution of the technique.

23 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 24

Absorption cell Test 1 Test 2 Test 3 1 cm z-cell 32 ± 1 s 34 ± 2 s 32 ± 1 s 2 cm z-cell 44 ± 3 s 44 ± 3 s Cuvette 35 ± 3 s 36 ± 1 s 35 ± 1 s

Table 5: The peak response time (5-95 %) of the different absorption cells for the three test. Bad measurement of the 2 cm z-cell for test 2.

The response time was determined for all three absorption cells and for all three tests. It was determined between all standard concentrations (0-1.0 µM, 1.0-2.1 µM, 2.1-4.1 µM, 4.1-8.2 µM and 8.2-0 µM and the same was done for the tests with stronger stan- dards. The results show no trend in the response time with increasing concentrations of the standards, in table 5 the peak response time of each absorption cell for each test is given. The 5-95 % peak response times of the different cells show that the 2 cm z-cell is about the same as the response time reported by Kjær et al. (2016) of 45 seconds. The 1 cm z-cell and the cuvette have lower peak response times of about 34 seconds for the 1 cm z-cell and 36 seconds for the cuvette and thus both gives a better temporal resolution than the 2 cm z-cells, while the 1 cm z-cell gives a slightly better resolution than the cuvette.

3.1.2 Sensitivity A parameter that gives an indication how well the system performs, is the detection limit. It is the lowest concentration that can be detected with statistical certainty. The detection limit is dependent on the noise of system and is normally taken as three times the standard deviation of the baseline signal. The standard deviation of the baseline of each detection cell was determined for all three tests and they were found to be the same within the uncertainties and thus the detection limit of the cuvette matches that of the 2 cm z-cell reported by Kjær et al. (2016).

The sensitivity of a detection technique is a measure of how well it can distinguish between small differences in the concentration of the sample. The sensitivity is con- trolled by the noise of the measurements and the slope of the calibration curve. Thus if two methods have the same slope the most sensitive method is the one with the highest precision and vice versa if they have the same precision it is the method with the steepest slope that is the most sensitive. Above it was shown that the precision of the systems is the same and thus the sensitivity depends on the slope of the calibration curve. The calibration curve is calculated using the relationship:

I abs = −log( ) (3) Ibase

24 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 25

Figure 15: Calibration curves of the standard series from the three test and the three absorption cells. The top panel is the 1 cm z-cell with test 1 (blue), test 2(orange) and test 3 (green). Middle panel is the 2 cm z-cell with test 1 (blue), test 2(orange) and test 3 (green). Lastly in bottom panel is the cuvette with test 1 (blue), test 2(orange) and test 3 (green).

Where abs is the absorption, I is the standard intensity and Ibase is the baseline in- tensity. The results can be seen in figure 15 and the intercept, slope, χ2 and the χ2 probability in table 3. The slope of the 1 cm z-cell and the cuvette should be half that of the 2 cm z-cell as the light path is twice as long in the 2 cm z-cell. It can be seen that in the case of test 1 and test 3 this is true as the slopes of the 1 cm z-cell and cuvette within the uncertainties are half the size of the 2 cm z-cell. It can not be compared for test 2 as the measurements were bad.

Based on this a change to the cuvette should be made as it has a better response time, an expected sensitivity of half that of the 2 cm z-cell and a similar detection limit. In theory it should also reduce the amount of air bubbles getting stuck in the detection cell.

25 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 26

Test 1 Test 2 Test 3 1 cm z-cell Intercept 0.3 ± 2.4 · 10−3 1.7 ± 3.6 · 10−3 −1.5 ± 2.2 · 10−3 Slope 3.9 ± 0.5 · 10−3 2.8 ± 0.4 · 10−3 2.2 ± 0.3 · 10−3 χ2 0.022 0.321 0.502 Probability 0.999 0.956 0.918 2 cm z-cell Intercept 1.1 ± 2.8 · 10−3 −1.7 ± 3.9 · 10−3 Slope 6.6 ± 0.8 · 10−3 4.6 ± 0.4 · 10−3 χ2 0.188 0.147 Probability 0.980 0.986 Cuvette Intercept −0.5 ± 2.4 · 10−3 0.7 ± 3.7 · 10−3 −1.1 ± 2.4 · 10−3 Slope 3.7 ± 0.7 · 10−3 2.7 ± 0.3 · 10−3 2.1 ± 0.2 · 10−3 χ2 0.155 0.047 0.111 Probability 0.984 0.997 0.991

Table 6: The parameters of the calibration of the pH standard series. Including the intercept and slope of the calibration curve. The χ2 value and the χ2-probability is also given. Bad measurement of the 2 cm z-cell for test 2.

3.1.3 Acidity spectrum When changing to the cuvette instead of the 2 cm z-cell it is important to check the absorption as a function of the wavelength as it shows at what wavelength/wavelengths the optimal signal is measured. It is expected to be at the same wavelengths as for the 2 cm z-cell but a test is made to be sure it is. This is done by measuring the intensity of the light absorbed by the spectrometer at all wavelengths. The pH absorption as a function of the wavelength for two different standard concentrations can be seen in figure 16. It can be seen that just as for the 2 cm z-cell there are two different places where measurements can be done, these are found to be at 451 nm and 584 nm. These are close to the reported wavelength of 450 nm and 586 nm from Kjær et al. (2016).

3.2 Continuous detection of sulphate The sulphate continuous detection technique is another method that can be used to determine the timing and strength of past volcanism. Two methods exist the one de- veloped by Röthlisberger et al. (2000) using methylthymol blue (MTB) as the reagent (figure 11) and the method developed by Bigler et al. (2007) using DMS-III as the reagent (figure 12). There are advantages to both methods, the DMS-III technique has the big advantage that the reagent is more stable than the reagent used in the MTB technique. The reagent used in the MTB method has been shown to have a

26 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 27

Figure 16: The pH absorption as a function of wavelength, similar to Kjær et al. (2016) two points suitable for measurements are found, one at 451 nm and one at 584 nm. lower sensitivity already after one day and also having increased the baseline drift, and test of a four to seven day old reagent shows it is not able to stabilize [Jensen 2014]. Thus the MTB reagents needs to be remade daily while the DMS-III reagents can last multiple days. The DMS-III technique uses two column while the MTB technique only uses one. Optimally no columns would be used as they can cause changes in the flow if they get blocked up by particles and both of these techniques are highly sensitive to flow changes, thus the MTB method is better in this aspect. Calibration made of the systems by Jensen (2014) shows that the MTB method has a much steeper calibration than the DMS-III method, thus the sensitivity of the MTB method is higher than the sensitivity of the DMS-III method. One last parameter that separates the two methods is the limit of detection (LOD). Jensen (2014) tested the LOD of both techniques and could not reproduce the LOD of 70 ng g−1 reported by Bigler et al. (2007). Using the MTB technique the LOD found was however 61 ng g−1, this is lower than both the reported working LOD by Röthlisberger et al. (2000) of 100 ng g−1 and the LOD of the DMS-III method. Based on this the choice was made to work on the MTB technique as it had fewer columns, higher sensitivity and a lower LOD. These qualities are valued over not hav-

27 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 28

Figure 17: Results of the Ca standard with Coasol test. Ca standards (20 ppb, 50 ppb and 200 ppb) without Coasol in orange and Ca standard (20 ppb and 50 ppb) with 27.08 mL Coasol in green, the spike in the end of the first standard is due to air. The standard with 6.25 mL of Coasol was measured but due to a lot of air bubbles getting into the system no usable data was collected. ing to prepare a new reagent daily.

3.2.1 Coasol As mentioned above the columns in the detection system can cause flow problems if particles begin to accumulate in the columns slowing down the flow or a big spike of particles can make a temporary flow change. To get rid of this problem an attempt was made to not use the cation exchange column and try to use a chemical reaction

Standard conc. Amount of standard Amount of Coasol 20 ppb 25 mL 6.25 mL 20 ppb 30 mL 27.08 mL 50 ppb 23 mL 6.25 mL 50 ppb 31 mL 27.08 mL

Table 7: Composition of the Ca standards with Coasol.

28 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 29 to remove the cations interfering with the sulphate measurements from the sample. The most important cations to remove are calcium (Ca2+) and to a lesser extent mag- nesium (Mg2+). The concentration of magnesium in the ice cores from Greenland is very small and can be ignored for now, but there are high concentrations of Ca2+ that needs to be removed.

It has been hypothesized that the drilling liquid Coasol, used while drilling the ice cores to prevent the borehole from closing, could possibly remove calcium when it is present in the ice core. This has been tested by making four Ca2+ standards (two 20 ppb and two 50 ppb) and adding Coasol to them (table 7), and leaving them for the reaction removing the Ca2+ to work. The standards with Coasol was left for six months before testing, then the Ca2+ standards was measured to see if the Coasol removed the calcium. For the measurements first a normal set of Ca2+ standards were run (20 ppb, 50 ppb and 200 ppb), then the Ca2+ standards with 6.25 mL of Coasol and then the standards with 27.08 mL of Coasol, the results can be seen in figure 17. In orange is the Ca2+ standard without Coasol and in green the Ca2+ standard (20 ppb and 50 ppb) with 27.08 mL Coasol, the peak between the two standards is due to air bubbles in the system. The last standards with 6.25 mL of Coasol was measured but due to a lot of air bubbles getting into the system no usable data was collected. Even with the loss of some of two of the standards it is clear to see from the Ca2+ standards with Coasol in figure 17 (green) that the Coasol did not remove the Ca2+. Instead it looks like it has increased the signal in Ca2+ as both of the standards are higher than the standards with the same concentration and no Coasol. So this method is not the solution to removing the Ca2+ in the sample, other methods have to be tested.

3.2.2 Cation exchange column The type of cation exchange column used in sulphate detection technique has been known to cause flow issues when measuring ice cores with high dust concentration. Therefore it is of interest to try and find a different kind of CEC to test whether the flow is better in one of those. Various kinds of cation exchange columns exist, for this study the Bio-ScaleTM Mini UNOsphere S and Rapid S Cartridges 1 ml columns made by Bio-Rad were tested, details can be seen in table 8.

Bio-ScaleTM S Bio-ScaleTM Rapid S Size 1 mL bed volume 1 mL bed volume Dimensions 40x5.6 mm i. d. 40x5.6 mm i. d. Ionic capacity 260 µeq/mL 140 µeq/mL Median particle size 80 µm 100 µm Binding capacity 60 mg IgG/mL 60 mg IgG/mL Recommended flow rate 50-1200 cm/hr 50-800 cm/hr

Table 8: Specifications of the Bio-Rad cation exchange columns

29 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 30

Figure 18: Results of the different cation exchange columns ability to remove Ca. Upper left the three standards (25 ppb, 50 ppb and 200 ppb) without any CEC, upper right previously used CEC, lower left Bio-Rad S and lower right Bio-Rad Rapid S. Small jumps in baseline is most likely due to an electrical problem or flow change.

An important thing to test is how well the columns remove the Ca2+ from the sam- ple. This is done by adding the columns including the CEC used before to the Ca2+ detection system one at a time and running Ca2+ standards through the system and measuring the concentration. The concentration of the Ca2+ standards are 25 ppb, 50 ppb and 200 ppb, and the same standards were used for all three columns. The results can be seen in figure 18, with the upper left being the three standards (25 ppb, 50 ppb and 200 ppb) without any CEC, upper right previously used CEC, lower left Bio-Rad S and lower right Bio-Rad Rapid S. All three columns have completely removed the Ca and left only baseline. The small jumps in the baseline probably due to electrical effects or flow changes and does not have an effect on the actual measurements.

All three columns can be used to effectively remove Ca2+, but the flow through them also needs to be steady if they are to be used in the detection technique for sulphate. To test if the flow changes during measurements of ice, a test was designed using one of the Bio-Rad columns and then pumping some discrete samples taken from the NGRIP ice core (bag 4937 T, high dust concentration) and from the Renland ice core (bag 403+404 and 527+528, low dust concentration, but large particle size [Simonsen et al.

30 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 31

Figure 19: Results of the Bio-Rad S cation exchange columns flow. Left column is the dust concentration and the right column is the flow rate in blue and a running mean of the flow rate in orange. From top to bottom it is the flow of MilliQ water with no column, MilliQ water with column, NGRIP bag 4937 T, Renland bag 403+404 and Renland bag 527+528.

2018]). The column chosen for the test was the Bio-Rad S as it has the smaller median particle size, thus the flow should be better in this. The previously used column is not tested as it is known from use in the past that it causes flow problems and that is why it should be replaced. The results of the test can be seen in figure 19. Left column is the dust concentration and the right column is the flow rate in blue and a running mean of the flow rate in orange. From top to bottom it is the flow of MilliQ water with no column, MilliQ water with column, NGRIP bag 4937 T, Renland bag 403+404 and Renland bag 527+528. As expected the flow is constant when there is no column and when there is a column and it is still MilliQ water the flow is constant until a big peak of dust (possibly left over in the system from measurements) came through then the flow went slightly up then slowly decreased again but it became stable at a higher level than before the dust peak. For the NGRIP 4937 T with a high dust concentration the flow shows a constant slow decrease until the end where it seems to stabilize in the last few minutes. Renland bag 403+404 the flow is constant all the way through and the jump in the flow in the end is due to going back to MilliQ water, the change in flow between the MilliQ water and sample is most likely due to flow difference between the selection valves in the CFA system. For Renland bag 527+528 the flow is again constant even with some quite big spikes in the dust close to the end. For these bags

31 3. OPTIMIZING THE CFA TECHNIQUES FOR ACIDITY AND SULPHATE 32 there are MilliQ water both before and after. Based on this the Bio-Rad S cation exchange column seems to work acceptably for low dust concentrations, while if there is higher dust concentrations the column seems to have some problems with the flow. A big peak in dust made a jump in the flow rate as well with quite a long stabilization period afterwards. Consistent higher dust values all seems to cause a problem with the flow rate slowly decreasing. If the Bio-Rad columns are to be used more testing should be done to be certain the behaviour shown here is consistent.

32 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 33

4 Ice core measurements: Traverse cores

The continuous detection techniques of acidity and sulphate have been optimized with the goal of making them even better for use in measuring chemical species using continuous flow analysis (CFA). Both techniques were connected to the Copenhagen CFA system and used during NEEM to EastGRIP traverse core melting campaign in September 2017 and January 2018. This section is describing the setup of the pH detection technique for the traverse melting campaign and the results obtained.

Measurements of sulphate were tried on the traverse cores A2, A3 and A6 using the method of Röthlisberger et al. (2000) with the optimization discussed in the Optimiza- tion chapter. The technique was connected to the existing CFA system using the parts and chemicals used by Jensen (2014). During the measurement it was clear something was not working, as no signal was seen at all just a steep negative drift and no changes in the absorption was seen during standard runs. The mixing coils where exchanged for shorter ones which removed the drift, now a drop from baseline happened when sample was running but nothing was seen in the signal just a flat line. A test with very strong standards (122.6 mg/L H2SO4) was done and this gave a signal, so it is suspected the limit of detection on the system was to high to see any signal from the ice cores, more on this in the discussion. Due to the technique not working during the traverse measurements it was decided not to bring it to Bern for the EastGRIP melting campaign.

4.1 Measurements The six shallow traverse cores were drilled on the traverse from NEEM to EGRIP in 2015. Three of them were drilled on the west side of the ice divide (A1, A2 and A3), one on the ice divide (A6) and two on the east side of the ice divide (A4 and A5) figure 2 and table 1. All of the cores were drilled using a hand powered drill and logged in

Figure 20: Schematic of the optimized acidity system flow paths and instruments.

33 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 34 the field and then brought back to Copenhagen where they have been measured in September 2017 (A1, A4 and A5) and in January 2018 (A2, A3 and A6).

The acidity technique from Kjær et al. (2016) was already part of the Copenhagen CFA system with the vacuum degasser also connected. Thus only the optimization in form of the cuvette instead of the z-cell had to be installed. A schematic of the acidity method can be seen in figure 20, it has the 65 C◦ heat bath with the mixing coil, the vacuum degasser and the absorption cuvette in the end. The rest of the system is as described in the continuous flow analysis chapter, other impurities measured include, 2+ + + Calcium (Ca ), Ammonium (NH4 ), Hydrogen peroxide (H2O2) and Sodium (Na ).

To be able to do analysis on the cores they have been dated. The dating was done + by annual layer counting of the H2O2 and Na . The H2O2 has a summer peak and winter trough and Na+ has a winter peak. Using this a year was defined as summer + peak to summer peak in H2O2, with a winter trough in H2O2 and winter peak in Na and interpolated between the peaks and troughs. The cores where drilled in summer of 2015 so the ages was counted backwards from this. Dating ice cores by annual layer counting based on seasonal signals should be done

Figure 21: Conductivity measurements from the six traverse cores on an age scale. From top to bottom it is A1-A6.

34 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 35

Figure 22: Acidity measurements from the six traverse cores on an age scale. From top to bottom it is A1-A6. with care. The position of the seasonal peaks can be estimated wrongly due to smooth- ing of the signal which makes a possible clear summer peak into a more round shape where it can be hard to exactly determine the peak. The smoothing can be caused by post depositional effects like snow erosion and re deposition. Another problem is that not all proxies gives a significant seasonal peak every year which would lead to errors in the dating. This is why multiple proxies are normally used when doing annual layer counting. One last thing that can also lead to errors in the dating is surface melting as that would lead to percolation down through the snow [Zens 2018].

The main reason for measuring the acidity in the traverse cores is to use the volcanic peaks in the acidity to test the spatial variation between the cores. The acidity mea- surements are compared to the conductivity measurements as the conductivity follows the acidity and thus big peaks in the acidity can be confirmed using the conductivity. The conductivity measurements on an age scale can be seen in figure 21 and the acidity measurements can be seen in figure 22. Comparing the measurements of conductivity and acidity it can be seen that they overall show the same features. Differences can be due to the fact that the conductivity is also influenced by other ions than H+. It is also clear that the six cores cover very different time periods. A1 covers about

35 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 36

A4 (µM) A5 (µM) A6 (µM) 2015-2010 4.16 ± 0.04 3.32 ± 0.07 3.59 ± 0.06 2010-2000 3.78 ± 0.02 3.39 ± 0.02 3.78 ± 0.03 2000-1990 4.15 ± 0.03 5.12 ± 0.03 4.42 ± 0.04 1990-1980 5.14 ± 0.04 4.85 ± 0.04 4.14 ± 0.04 1980-1970 5.74 ± 0.04 4.65 ± 0.04 1970-1960 3.29 ± 0.02 4.46 ± 0.05

Table 9: Mean values in 10 year intervals of the acidity in traverse cores A4, A5 and A6, with 1 σ uncertainties.

17 ± 1 years, A2 about 27 ± 1 years, A3 about 27 ± 0 years, A4 about 35 ± 1.5 year, A5 about 54 ± 2 years and A6 about 53 ± 1 years. It can be seen from looking at the average values of the acidity of multi year periods seen in table 9, that the mean acidity values are higher in the sixties, seventies and eighties than they are in later periods (A4, A5 and A6). This is expected due to the industrialisation of North America and Europe which saw a peak in the 1970, and then slowly decreased until today [Herron 1982].

4.1.1 Standard calibrations During a melting campaign the acidity detection technique and all other techniques are calibrated by running standards series consisting of two standards in the case of acidity. This is done multiple times a day, in the beginning, after each run of ice (3-4 metres) and in the end of the day. To make the transition between baseline (MQ water) and sample clear a piece of MQ ice of about 2 cm is melted at the beginning and end of each run. This ice is cleaner than the MQ water due to impurities being frozen out, this leads to a drop in concentration in most detection techniques. An example of an acidity standard series with four standards instead of two was shown in figure 14 in the Optimization chapter. The standard series made during the melting campaign consisted of two standards with the concentrations 9.8 µM and 19.4 µM. All the calibration curves calculated from the standard series of all six traverse cores are shown in figure 23. The calibra- tion curves of each core have a separate colour and the light grey area is the standard deviation of all the calibration curves. It can be seen that the calibration curves of each core are quite similar while there is some difference between the different cores. This is important as it shows that the technique is stable and consistent. The variation seen between the curves from the same core is most likely due to new standards being made before each calibrations and even small differences in the concentration of the standards will change the curves. The reason for not using the same standards for all calibrations is that prolonged exposure to CO2 from the laboratory air will change the concentration in the standard. So keeping the standard for an entire day would lead to worse calibrations due to the unknown concentration in the standards.

36 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 37

There are larger variations seen between the calibration curves of the different cores especially A4, A5 and for one of the calibrations A2 having a slightly steeper calibra- tion curves. This could possibly be due to having a newer reagent as a new reagent was made before the melting of these three cores, while the other cores where using a reagent at least two days old. From this the variation of the calibration curves for all six traverse cores can also be found. This is taken as 1 σ of the slope of the calibration fits and it is ± 19 %, a quite high variation, but considering that there is four months in between the measurements of the first three cores and the last three cores and some changes to the setup has been made, it is not too bad. Looking at the different cores by them self the variation between the calibration curves is quite a bit lower. The variations are between ± 1 % and ± 5 % with A5 having the lowest and A2 and A4 with the largest variations. These are low variations which is good as means the calibration curves for each core are very similar.

Figure 23: Calibration curves of all standard series from all six traverse cores. A1 in blue, A2 in orange, A3 in green, A4 in red, A5 in violet and A6 in brown. The light grey area is the standard deviation of the calibration curves. A1, A4 and A6 were measured in September 2017 while A2, A3 and A6 were measured in January 2018.

37 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 38

Figure 24: Boxplots of the acidity and conductivity measurements. Marked in orange is the median, the edges of the box is 25th and 75th percentiles and notches mark 95% confidence intervals on the median.

4.1.2 Spatial variation The spatial variability of the traverse cores can be tested in multiple ways both using box plots and the linear correlation between the different cores. This has been done for both the conductivity and the acidity. The boxplots of the acidity and conductivity can be seen in figure 24, the data used is only taken for years where all datasets are available eg. the comparison only uses the data covering from 2015 to 1997 which is the period covered by A1. It can be seen that the medians tends to be higher on the east side of the ice divide (A4, A5 and A6). This could be due to accumulation differences as the west side of the ice divide receives almost twice the amount of snow of the east side. The correlations have been tested on the logarithm of the monthly medians. This has been chosen for multiple reasons, taking the logarithm of the data is done to lower the influence of the very big peaks found in both conductivity and acidity as they tend to skew both medians and means. The median was chosen over the mean of the monthly data as is less influenced by the big peaks. The data is quite noisy and thus taking the monthly medians instead of just the calibrated data reduce the influence of the noise. The correlations are only taken for years where both datasets are available.

38 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 39

The correlations of the conductivity measurements can be seen in table 10. None of the cores have any strong correlation with each other most of them are within the uncertainties very close to being completely uncorrelated. Even though there are no strong correlations it is still possible to see some features in the correlations. The A1 core only have some correlation with the A2 core these are two of cores on the west side of the ice divide while it is not correlated or anti correlated for the rest of the cores. Thus features in the conductivity might be different on either side of the divide. This could be due to the influence of dust on the conductivity and the wind brings in the dust from the west also the fact that the accumulation rate is higher on the west side of the ice divide than on east side could also be part of this. A2 which is closer to the ice divide shows lower correlation than all the other cores, this could be explained by the height the different cores were drilled at. A1 was drilled at a quite a bit lower altitude (2484 m) than the others (>2600 m) this might be another reason why A1 is not even slightly correlated with the other cores except for the one on the same side of the ice divide. While all the other cores show slight correlations between each other. The A6 core have some of the highest correlations seen in the conductivity with A4 and A5, this is most likely due to the three cores being at close to the same height and all on the east side of the ice divide. Interestingly the correlation between A4 and A5 which are drilled close to and at the EastGRIP site respectively show no significant correlation even though they are drilled very close to each other. This might be due to differences in the post depositional effects and accumulation rate of being on the edge of the north east Greenland ice stream (NEGIS) where A4 is and being in the middle of the ice stream as A5 is. A2 also show some correlation to A4 which is hard to explain as they are located on opposite sides of the ice divide and with about 100 metres difference in height. One important thing that might explain why there is no strong correlations is the dating of the cores. If the dating is just slightly of in some or all of the cores it could lead to lower correlations. Errors in the dating are likely as it sometimes can be hard to determine when as peak is an annual peak of just something else.

A1 A2 A3 A4 A5 A6 Cond R2 R2 R2 R2 R2 R2 A1 1.0 0.19 ± 0.07 -0.01 ± 0.07 -0.01 ± 0.07 -0.09 ± 0.07 -0.11 ± 0.07 A2 1.0 0.15 ± 0.06 0.28 ± 0.05 0.14 ± 0.06 0.10 ± 0.06 A3 1.0 0.13 ± 0.06 0.07 ± 0.06 0.10 ± 0.06 A4 1.0 0.14 ± 0.05 0.22 ± 0.05 A5 1.0 0.31 ± 0.04 A6 1.0

Table 10: Correlations between the monthly median conductivity of the six traverse cores.

39 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 40

A1 A2 A3 A4 A5 A6 Cond R2 R2 R2 R2 R2 R2 A1 1.0 0.03 ± 0.07 -0.19 ± 0.07 0.03 ± 0.07 0.11 ± 0.07 -0.06 ± 0.07 A2 1.0 -0.04 ± 0.06 -0.10 ± 0.06 0.02 ± 0.06 -0.13 ± 0.06 A3 1.0 -0.04 ± 0.06 0.06 ± 0.06 0.01 ± 0.06 A4 1.0 -0.01 ± 0.05 0.01 ± 0.05 A5 1.0 0.04 ± 0.04 A6 1.0

Table 11: Correlations between the monthly median acidity of the six traverse cores.

The correlations of the monthly median acidity in the traverse can be seen in table 11. Again no strong correlations are present in fact in this case there are only four of the calculated correlation coefficients that are different from 0 within the uncertainties. And three out of these four show very weak anti correlation between A1 and A3, A2 and A4 and A2 and A6 while the last one show a very weak correlation between A1 and A5. No clear pattern is seen in these correlation coefficients and there seems to be no correlation between the acidity in the six traverse cores.

This is interesting as based on the correlation pattern map based on the global at- mospheric reanalysis from the European Centre for Medium-Range Weather Fore- casts (ECMWF), provided by Martin Olesen from the Danish Meteorological Institute (DMI) there should be some correlation between the cores, (figure 25). The regional climate model used is constrained by a global climate model based ERA-Interim re- analysis with a 5.5 km spatial resolution. The map of the correlation pattern is based on records of the averaged annual accumulation which is the precipitation minus the evaporation in the time period from 1979-2014 (the satellite era).

The correlation map shows correlations of accumulation between the cores, thus the map does not show the correlation of acidity and caution needs to be taken when comparing acidity measurements to the maps. The correlation map suggests that there could be a strong correlation between the three cores west of the ice divide (A1, A2 and A3) and the same is seen for the cores east of the divide (A4 and A5). While the A6 core which is located on the ice divide show that no strong correlation should be expected with any of the other cores. The strongest correlation should be seen between A4 and A5 as they are located very close to each other and show very similar patterns in the reanalysis map. The correlations of the conductivity show some of these patterns as well, A1 and A2 correlate slightly, the same for A2 and A3. While there is no clear correlation between A4 and A5, however A6 shows low correlation with both A4 and A5. The correlation or rather the lack of correlations in the acidity does not match at all with the reanalysis map as nothing is correlated in the acidity. This could be due to the large peaks of volcanic eruptions where some eruptions might not be seen in all the cores or due to

40 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 41

Figure 25: Modelled correlation pattern between the traverse cores based on ERA- Interim reanalyzes, based on annual average accumulation. Darker grey areas represent high correlation, yellow is no correlation and orange/brown is anti-correlation. A6 is placed according to its location on the traverse (Maps made by Martin Olesen, DMI, personal communication, 2018) (Figure from Zens [2018])

41 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 42 the errors in the dating.

4.1.3 Volcanic eruptions The acidity records obtained from ice core can be used to date and cross date ice cores due to the peaks from volcanic eruptions. The eruptions at least in more recent times come with a precise dating from other sources and this can be used to precisely set the age of the ice core at depth with volcanic eruptions.

Quite a few of the acidity peaks in the traverse cores can be attributed to volcanic eruption in the northern hemisphere. However it can not be excluded that some of the peaks during the industrial era are of anthropogenic origin. To determine which peaks in the acidity are volcanoes, the high H+ concentrations have been found by taking the values exceeding a rolling four year 3 σ (99.8 %) probability interval, this can be seen in figure 26. Where the acidity data (blue) from each traverse core on an age scale is given with a four year running mean (orange) and with the four year running mean added the four year running standard deviation (green). All values exceeding the four year running standard deviation is considered to be from either volcanic eruption or

Figure 26: Acidity records of the six traverse cores in blue, the 4 year running mean in orange and the 4 year running mean plus 3 σ of the 4 year running mean in dashed green. Light grey bars indicate events above 3 σ.

42 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 43

Figure 27: Conductivity records of the six traverse cores in blue, the 4 year running mean in orange and the 4 year running mean plus 3 σ of the 4 year running mean in dashed green. Light grey bars indicate events above 3 σ. extreme wildfire events. Comparing the acidity peaks above 3 σ with the conductivity peaks above 3 σ in figure 27, it is evident that it is the peaks at the same ages are matching the acidity peaks. The peaks in the acidity and conductivity have been matched to other records of volcanic eruptions and the results can be seen in table 12, with the event, location and timing in the left column, the year found in the traverse cores in the middle and the magnitude of the H+ in the right column. Some of the events are seen in multiple cores like Bárðarbunga, Grimsvötn 2011, Eyjafjallajökull, Grimsvötn 1998, Redoubt and Cleveland 1987. While the other eruptions are only seen in one of the cores (table 13).

One of the event above 3 σ is a wildfire event from 2002 [Kjær 2016]. Wildfire events can be seen in the acidity as the wildfires produce organic acids such as formic acid. However for most biomass burning events the acid signal from the formic acid is neu- tralized by the ammonium that is also produced by the burning [Legrand et al. 2016]. The event seen in the A2 record is most likely from the 2002 Rodeo-Chediski fire in Arizona (467066 acres) and/or the Florence/Sour Biscuit Complex Fire in Oregon (499750 acres). These are both big wildfires which covered large areas of land and would have produced a great amount of formic acid [Kuenzi et al. 2008, United States

43 4. ICE CORE MEASUREMENTS: TRAVERSE CORES 44

Event Year of exceeding 3σ H+ Bárðarbunga, Iceland (2014/2015) 2015(winter) 7.1-13.2 Grimsvötn, Iceland (2011) 2011(spring) 6.7-8.6 Eyjafjallajökull, Iceland (2010) 2010(spring) 5.6-6.2 Sarychev Peak, Russia (2009) 2009(summer) 7.3 Grimsvötn, Iceland (2004) 2004(fall) 7.3 Possible wildfire (2002) 2002(summer) 6.4 Grimsvotn, Iceland (1998) 1999(winter) 7.6-9.0 Cleveland, Aleutian Islands (1994) 1994(winter) 11.2 Redoubt, Alaska (1989) 1990(winter) 8.7-10.3 Cleveland, Aleutian Islands (1987) 1987(fall) 7.9-10.7 El Chichon, Mexico (1982) 1982(fall) 13.1 Sheveluch, Russia (1964) 1965(winter) 8.7

Table 12: Events seen in the different traverse cores with a H+ signal above 3 σ. Left column is the confirmed events from other records, the middle column is the date they where measured in the traverse cores and the right column is the magnitude of the H+ peak [Smithsonian Institution 2018].

Government Accountability Office 2004].

It is interesting that the Bárðarbunga from the end of 2014 and beginning of 2015 is seen in all cores but in A4. An increase is seen in both the acidity and conductivity in A4 where Bárðarbunga is seen in all the other cores, though the peak is not big enough to go above the 3 σ limit so it might be that Bárðarbunga is seen in A4 as well. This also looks to be the case for some of the other eruptions, but for some of them it could also just be the annual signal in the acidity with peaks in the spring. Other eruptions that might be seen in more records are the 2011 Grimsvötn and the 1989 Redoubt eruptions. Some temporal variability is seen, in multiple cores the events are found at slightly different ages all within a few months of the actual eruption. This could be due to post depositional effects such as winds moving the newly precipitated snow, to diffusion in the snow and firn or most likely errors in the dating of the ice cores. This can be used to adjust the age scale and thus align the eruptions so they are matching across all the cores they are detected in. Quite a bit of spatial variability is seen in the detected events as it is only the 2015 Bárðarbunga and 2011 Grimsvötn eruptions that are seen in all the cores, all of the other events show up in only a few of the records. One thing to notice is that the Eyjafjallajökull eruption is only seen in the cores on the west side of the ice divide and not in any of the other cores. No other patterns are discernible in the events and thus there is quite some spatial variability in the traverse cores.

44 5. ICE CORE MEASUREMENTS: EASTGRIP 45

Event A1 A2 A3 A4 A5 A6 Bárðarbunga (2014/2015) x x x x x Grimsvötn (2011) x x x x x x Eyjafjallajökull (2010) x x Sarychev Peak (2009) x Grimsvötn (2004) x Wildfire (2002) x Grimsvotn (1998) x x x Cleveland (1994) x Redoubt (1989) x x x Cleveland (1987) x x El Chichon (1982) x Sheveluch (1964) x

Table 13: Table of which volcanic eruptions and wildfire events are above 3 σ in the different traverse cores. If marked by a x the event is seen in the core.

5 Ice core measurements: EastGRIP

The EastGRIP drill sited is located on North Greenland ice stream (NEGIS) at 75.37N 35.59W, within the Northeast Greenland National Park figure 2. The camp site was set up in 2015 after the traverse with the main dome and equipment from the NEEM drill site. The deep drilling at EastGRIP is on going and have in end June 2018 hit ice from the last glacial at about 1250 metres depth and is planned to reach bedrock at 2550 metres. The acidity detection technique was brought to the Bern laboratory in Switzerland and used during the EastGRIP melting campaign in February and March 2018. Dur- ing the melting campaign the first 350 metres starting at 14 metres depth of ice from EastGRIP was melted continuously and measured on various different measurement setups, including Black carbon, Calcium, Sodium, Ammonium, Dust, Conductivity, Hydrogen peroxide, Nitrate, total Iron, Iron II, Acidity, water isotopes and discrete samples. The part of the system brought and managed by the Copenhagen team con- sisted of a conductivity meter, the acidity detection technique and discrete sampling.

5.1 Measurements The setup of the Copenhagen part of the CFA system looked slightly different to what it does in Copenhagen figure 28. The setup in Bern included a conductivity meter in front of the acidity technique. The conductivity can be used to align the acidity data to the other measurements made during the campaign as it should match the conductivity measurements from the Bern system. The incoming sample stream from the melt head to the Copenhagen system was shared with the Italian iron setups, the

45 5. ICE CORE MEASUREMENTS: EASTGRIP 46

Figure 28: Schematic the acidity system in Bern during the EastGRIP melting cam- paign. water isotopes and two discrete sampling lines. Due to the layout of the Bern laboratory and placement of the peristaltic pumps a wrap around loop using the same pump had to be used to keep a steady flow for the conductivity meter. It was a long line from the main pump to the pump running the Copenhagen system and thus the sample was pumped through the conductivity meter then back through the pump before getting to the acidity detection system. A manual with a detailed description of how to prepare and run the system including calibration and troubleshooting was written. It goes through all the steps needed to be done to run the system, how to make the reagents and standards and how to react if certain problems arise. It also has a more detailed schematic of the setup than the one shown in figure 28. It is include in Appendix A.

The calibrated data of the measurements of the conductivity and acidity of the top 350 metres on a depth scale of EastGRIP ice core is shown in figure 29. As expected sim- ilarities are seen between the conductivity and the acidity, especially the large peaks looks very similar in the two records. Some very large events are present in the acidity and will be discussed later in this section.

5.1.1 Standard calibrations Calibrations were done during the EastGRIP melting campaign just as they were done during the traverse melting camp. The calibrations were done five times a day, every morning, three times during the day and in the evening after the last run. Between each calibration six bags of 55 cm ice were melted (changed to eight bags at the end of the campaign). Also for this campaign MilliQ ice was used in the beginning and end of each run. The concentration of the two standards used for each calibration were 9.8 µM and 19.4 µM. New standards were prepared before each calibration to avoid

46 5. ICE CORE MEASUREMENTS: EASTGRIP 47

Figure 29: Conductivity (left) and acidity (right) measurements of the upper 350 metres of the EastGRIP ice core.

47 5. ICE CORE MEASUREMENTS: EASTGRIP 48

effects on the standard concentration of the CO2 in the lab. All 131 calibration curves determined from the standard series during the melt campaign are shown in figure 30, the light grey area is the uncertainty of all the slopes.

Very little variation are seen in the calibration coefficients almost all of them is very close to the same value. This is a good sign as this indicates that the calibrations have been very stable during the campaign. However a few of the coefficients are a bit smaller/larger and one is much larger than the others, the ones that only differ slightly are fine as they are all with in the uncertainty of all the other coefficients. The one that is much larger than the rest is a result of a standard series that went badly. Based on the notes in the standard log and logbook work was being done on the iron detection system which were very close to the absorption cuvette and the cuvette was very likely bumped during this standard series which would lead to a bad series. This calibration curve has not been used for calibration of the data, instead the calibration curve obtained from the standard series after this particular run of ice was used. The variation (1 σ) of the calibration coefficients have been determined after the bad coefficient has been removed and was found to be ± 6.3 %, in contrast if the bad coefficient was not removed the variation is ± 8.3 %. Thus after removing the bad calibration curve the variation of the calibrations is quite low and the calibrations throughout the melting campaign have been stable. The distribution of the calibration coefficients have been checked in figure 31. The

Figure 30: Calibration coefficients of all standard series from the EastGRIP melting campaign. The light grey area is the standard deviation of the calibration curves.

48 5. ICE CORE MEASUREMENTS: EASTGRIP 49 upper panel shows the distribution of the coefficients with the bad coefficients and it can be seen that the gaussian fit is bad and that the coefficients are not normally distributed. The bad coefficient has not been used and can thus be removed and the the picture of the distribution is quite different. The distribution without the bad coefficient can be seen in the lower panel of figure 31 and for this distribution the gaussian fit is better and the coefficients are normally distributed, as well as having quite a bit less variation.

Figure 31: Histograms of the calibration coefficients of all standard series from the EastGRIP melting campaign. Top panel including the bad calibration coefficient of 4.5 and bottom panel without it. The text box includes the number of coefficients, the mean and standard deviation, the χ2 value, degrees of freedom (DOF) and probability of the gaussian fit, the number of entries, mean and standard deviation determined from the fit.

49 5. ICE CORE MEASUREMENTS: EASTGRIP 50

5.1.2 Bern and Copenhagen conductivity comparison The conductivity measurements of the Bern and Copenhagen parts of the system were used to align them to each other as the conductivity signal should in theory be identical in the two systems. To test if the signals in reality actually were similar the correlation between the two conductivity records was determined. Just by looking at the two records plotted on top of each other it is clear to see that they do not correlate 100 % (figure 32). In various places the blue record from the Copenhagen system can be seen behind the orange from the Bern system. The amount of blue seen behind the orange seems to increase with depth and it is thus interesting to determine the correlation of not only the full record but also for sections to examine whether the correlation between the two records gets worse with time. The correlations has been determined for the full records, and the records have also been cut into fifths and the correlation has been determined between those fifths. The results are shown in figure 33 and table 14. From the figure and the correlation values it can be seen that the correlation between the two system decrease with depth. The decrease is quite significant as the last 20 % has close to half the correlation that the first 20 % have. As the melting campaign began from the top of the core (14 metres) this also mean that the correlation between the two systems decreased with time during the cam- paign. The lower correlation in the end might lead to the alignment of the acidity record with the depth scale from Bern being harder to get correct the further down the ice core. This might not be a problem though as long as the time delay between the melt head and the conductivity meter in the Copenhagen system did not change. If the delay time stayed the same this can be used in combination with the alignment from the early parts of the core with higher correlation to get a good alignment in the end as well.

Another test done between the two correlation systems is a boxplot which can be seen in figure 34. This shows that the two records also have different medians. The Copen-

Depth Correlation between Bern and CPH conductivity 14 - 350 m 0.740 ± 0.001 14 - 81.2 m 0.866 ± 0.001 81.2 - 148.4 m 0.730 ± 0.002 148.4 - 215.6 m 0.730 ± 0.002 215.6 - 282.8 m 0.713 ± 0.002 282.8 - 350 m 0.573 ± 0.002

Table 14: Correlations of the conductivity between the Bern system and the Copen- hagen system. The correlation has been tested for the full length (14-350 meter) and for 20 % intervals.

50 5. ICE CORE MEASUREMENTS: EASTGRIP 51

Figure 32: The conductivity record of Bern system (orange) and Copanhagen system (blue) plotted on top of each other (top panel) and the Bern conductivity minus the Copenhagen conductivity in blue and a zero line in orange (bottom panel).

Figure 33: The correlation between the Bern and Copenhagen system. Upper left is the full record, upper middle is the first fifth of the record, upper right is the second fifth of the record, lower left is the third fifth of the record, lower middle is the fourth fifth of the record and lower right is the last fifth of the record.

51 5. ICE CORE MEASUREMENTS: EASTGRIP 52

Figure 34: Boxplot of the two Copenhagen (left) and Bern (right) conductivity records. hagen (right) conductivity has a slightly higher median than the Bern conductivity and thus the Copenhagen system generally measured higher conductivity values. The differences between the two records might be explained by contamination. The line going from the melt head to the Bern conductivity meter was significantly shorter than the line going to Copenhagen conductivity meter. With a very long line there is the risk of particles getting stuck in the line and contaminating sample going through. The risk also increase with the length of the campaign and time between the change of tubing on the line. If this has happened it could easily explain why there is a difference between the two systems and if the tubing has not been changed it could also explain why the correlation gets worse with time.

Contamination of the sample is not the only problem a long line leads to. When sample has to move through a long line before getting to the detection technique there is a risk of diffusion happening. This would lead to a smoothing in the signal and peaks would be lower compared to a measurement made closer to the melt head. A selection of the biggest peaks in the conductivity records has been chosen and plotted for both the Bern and Copenhagen in figure 35. It can be seen in the figure that for all the peaks the magnitude is on average smaller by 12 ± 1 %. This effect is most likely also having an effect on the correlation between the two records. This however also means that a similar decrease in magnitude of the big peaks is expected in the acidity record. How big the decrease is can not be determined from the conductivity

52 5. ICE CORE MEASUREMENTS: EASTGRIP 53

Figure 35: The largest peaks in conductivity from both the Bern (blue) and Copen- hagen (orange) systems. as the diffusion might have a different effect on the acidity. Since there was no other acidity measurements closer to the melt head the decrease can not be determined, but it is most likely present in the data and should be taken into account if comparisons with other records are to be made.

5.1.3 Volcanic eruptions The part of the EastGRIP cores that have been measured covers 336 metres from 14-350 metres depth. This covers quite some time back in the past, unfortunately how far is still not known as an age scale for the EastGRIP ice core has not been made yet. This makes the task of determining which volcanic eruptions caused the peaks seen in the acidity data more difficult.

A comparison to other ice cores can be made, but the same eruptions will not be found at the same depth in the ice core. This is due various effects, first the ice cores have not been drilled at the same time and thus for newer ice cores more snow will have accumulated on top than for older ones. The snow accumulated on top in between the drilling of two cores with lead to discrepancies in the depth at which the same volcanic eruptions are found. Another important factor is the accumulation rate at the different drilling sites. If the accumulation rate at one drilling site is higher than that of another site then the depth increases at the two sites at different rates. Thus even if you drill

53 5. ICE CORE MEASUREMENTS: EASTGRIP 54

Figure 36: Conductivity (left) and acidity (right) record of the EastGRIP core in blue, the one meter running mean in orange and the one meter running mean plus 3 times the one meter running standard deviation in dashed green.

54 5. ICE CORE MEASUREMENTS: EASTGRIP 55 two ice cores at the same time but at different locations you most likely will not find the same eruption at exactly the same depth. The flow of the ice sheet at the locations of drilling also matters. When the ice flows the annual layers are being thinned, and if the amount of thinning is not the same at the sites, it can cause differences in the depth that an eruption is found at. This could be a factor at the EastGRIP drill site as the flow of the ice is up to ten times greater at EastGRIP compared to other drill sites.

Even with the problem of not having the age scale it is still possible to match vol- canoes to the big peaks. Big peaks stand out so clearly and are few in comparisons to the small peaks, this makes it possible to pick out the peaks originating from the largest known volcanic eruptions. This is even used to make the age scales, as the age of known volcanic eruptions can be used to constrain the layer counting. However it is only the big eruptions that can be determined on the depth scale, the peaks of the smaller eruptions are much harder to determine the origin of.

An attempt to identify the large volcanic eruptions in the EastGRIP cores has been made. To do this the same method as the one used on the traverse cores has been applied, that was to determine which peaks in the acidity have high H+ concentra- tions. This was done by taking the values exceeding a rolling one metre 5 σ (99.99 %) probability interval. The same has been done to the conductivity to compare, the results of both can be seen in figure 36. The big peaks above 5 σ in conductivity and acidity is matching just like it was in the traverse cores. However there is quite a difference in the small peaks, where the conductivity has more peaks above 5 σ. In the acidity there are 22 events over 5 σ limit while the conductivity has 63 peaks above. This could be due to the fact that the conductivity is influenced by the dust as well or it could be signal from biomass burning events such as wildfires. But the conductivity confirms the big peaks in acidity which can be tried to match to volcanic eruptions.

One of the largest recent eruptions is the 1783 Laki eruption, this should show as a really large peak in both the acidity and conductivity and can be used as a reference when trying to determine the origin of the other peaks. The Laki eruption is found at 45.5 metres depth in the EastGRIP and from knowing that, the origins of the other peaks have been determined, the results can be seen in table 15. All eruptions after the Laki eruption are very uncertain, as it gets very hard to estimate an age of the ice when getting further down through the ice without using actual layer counting or age modelling. What was done here was to try and base it on the biggest Icelandic volcanic eruptions as they should always show up in ice core from Greenland, and then try and fill the gaps between them with the largest recorded eruption and other large eruption from Iceland. It wont be possible to tell how correct this is until an age scale is made for the EastGRIP core.

55 5. ICE CORE MEASUREMENTS: EASTGRIP 56

Event (Year AD) Depth at EGRIP H+ (µM) yr/m Katmai, Alaska (1912) 23.8 m 11.9 10.0 Krakatoa, Indonesia (1883) 26.3 m 15.6 5.0 Tambora, Indonesia (1815) 40.3 m 8.5 6.2 Laki, Iceland (1783) 45.5 m 28.8 4 Katla, Iceland (1625) 85.1 m 8.7 6.5 Bárðarbunga, Iceland (1477) 108.0 m 14.1 7.4 Katla, Iceland (1416) 116.2 m 15.2 2.3 Oraefajokull, Iceland (1362) 139.3 m 13.1 13.5 Hekla, Iceland (1300) 143.9 m 20.2 7.9 Unknown 165.9 m 8.2 - Katla, Iceland (934) 190.5 m 16.7 2.0 Mount Churchill, Alaska (847) 234.6 m 8.2 14.0 Pago, Papua New Guinea (710) 244.4 m 13.6 12.1 Rabaul, Papua New Guinea (540) 258.5 m 22.9 3.9 Lake Ilopango, El Salvador (450) 281.7 m 13.5 4.5 Katla, Iceland (400) 292.9 m 9.7 11.0 Akutan, Alaska (340) 298.4 m 9.5 14.7 Katla, Iceland (290) 301.8 m 11.6 -

Table 15: Biggest acidity events seen in the EastGRIP core with a H+ signal above 5 σ. First column is the proposed event, the second column is the depth they were measured in the EastGRIP core, the third column is the magnitude of the H+ peak and the fourth column is years per metre between the eruptions.

Some rather large peaks are seen in conductivity at depth where no peak is seen in the acidity. One of these peaks is at 41.2 metres depth, here a peak is seen the acidity as well but it is not above the 5 σ limit. This peak is suspected to be the unknown volcanic eruption from 1810 as it is in between the 1816 Tambora and 1783 Laki eruption. Another peak in the conductivity that is thought to be of volcanic origin is the peak at 47.4 metres depth. This is suspected to be the 1760 Katla eruption, as it follows shortly after the Laki eruption. The reason there is no peak in the acidity is due to a mistake during the measurements where the absorption cell was moved during mea- surements which caused a change in the baseline and the loss of the volcanic signal in the acidity. Multiple other peaks in conductivity with no counter part in acidity are also found but most of these are expected to be caused by wildfires. The three conductivity peaks at 63.8, 89.5 and 93.8 metres depth are confirmed by ammonium records, provided by the Bern laboratory, to be wildfires, as can be seen in figures 37 and 38.

56 5. ICE CORE MEASUREMENTS: EASTGRIP 57

Figure 37: Bag 110 - 133 of the conductivity, sodium, calcium, dust, ammonium, nitrate and peroxide records from the Bern part of the system. A big peak in conduc- tivity, nitrate and ammonium can be seen at 63.8 metres depth, this is an indication of a large biomass burning event. Depths in figures are 0.55 cm to larger due to a mis- take in the depth assignment, the mistake has been taken into account in the analysis (Figure provided by Camilla Maria Jensen).

Figure 38: Bag 110 - 133 of the conductivity, sodium, calcium, dust, ammonium, nitrate and peroxide records from the Bern part of the system. A big peak in con- ductivity, nitrate and ammonium can be seen at 89.5 and 93.8 metres depth, this is an indication of large biomass burning events. Depths in figures are 0.55 cm to larger due to a mistake in the depth assignment, the mistake has been taken into account in the analysis (Figure provided by Camilla Maria Jensen).

57 5. ICE CORE MEASUREMENTS: EASTGRIP 58

5.1.4 Comparison with NEGIS shallow core In the summer of 2012 a 67 metre shallow firn core (NEGIS core) was drilled very close to the drill site of the EastGRIP core. The NEGIS core was drilled at 75◦37.61’0N, 35◦56.49’0W (EastGRIP: 75.37N 35.59W), the NEGIS core covers about 400 year in the time period 1607–2011. Quite a few things were measured in the NEGIS core including dielectric profiling (DEP), conductivity and acidity. The NEGIS core can be compared to the upper part of the EastGRIP core to see if the same features are seen. They are drilled very close to each other so the big peaks should be present in both cores. In figure 39 the DEP, conductivity and acidity of the NEGIS core are shown together with the conductivity and acidity from the EastGRIP core. The peaks in the two cores are not found at the same depth as expected as they were drilled three years apart from each other. The big peak of Laki is clearly seen in all records and it is nicely aligned in both the NEGIS and EastGRIP cores. The acidity measurements of the NEGIS core looks quite different to the EastGRIP acidity, this is because during the NEGIS melting campaign the Kjær et al. (2016) technique was still under development. It does not seem to detect all the big peaks and there are many peaks that are not seen in the conductivity or the DEP. Due to this it will not make sense to compare the two acidity records against each other. However the conductivity of both cores can be compared, and they can also be compared to the DEP as it looks very similar to the

Figure 39: NEGIS DEP record (top), conductivity (second from top), acidity (middle) and EastGRIP conductivity (second from bottom) and acidity (bottom), all plotted on a depth scale. The NEGIS cores was drilled in 2012 while the EastGRIP in 2016.

58 5. ICE CORE MEASUREMENTS: EASTGRIP 59

Volcano NEGIS depth EastGRIP depth Offset Katmai, Alaska (1912) 22.7 m 23.8 m 1.1 m Krakatoa, Indonesia (1883) 27.3 m 26.7 m -0.6 m Tambora, Indonesia (1815) 39 m 40.3 m 1.3 m Unknown (1810) 40 m 41.3 m 1.3 m Laki, Iceland (1783) 44.3 m 45.5 m 1.2 m Katla, Iceland (1760) 46.6 m 47.5 m 0.9 m Lanzarote, Spain (1730) 50 m - - Pacaya, Guatemala (1670) 59 m - - Komagatake, Japan (1640) 62 m 63.1 m 1.1 m

Table 16: Volcanic eruptions seen in the NEGIS core compared to at what depth they are seen in the EastGRIP core. conductivity. The DEP has been used to determine the origin of the big peaks in the NEGIS core [Vallelonga et al. 2014], which can be compared to the assignment done for the EastGRIP core above.

The volcanic eruptions found in the DEP of the NEGIS and the depths which they are found at are given in table 16, in this table the depths of the same eruption found in the EastGRIP core is given as well. Most of the peaks are off by somewhere about 0.9-1.3 metres, this is due to the difference in the time of the drilling. Two of the peaks found in the NEGIS DEP are not found in either the EastGRIP conductivity or acidity and the Krakatoa eruption is found at almost the same depth in both .The two peaks not found in the EastGRIP core might be due to a low signal, which seems likely as the two eruptions do not really give a signal in the NEGIS conductivity either. The Krakatoa eruption being found earlier in EastGRIP core is hard to explain, it might be that it has been placed at the wrong depth in one of the records. Based on the measurements it seems most likely to match the EastGRIP depth as there is a much more clear peak present than the peak in the NEGIS DEP and conductivity.

To compare the conductivities of the two records, the depth of the EastGRIP cores has been adjusted so the peaks are aligned in the two cores. Four sections including the biggest peaks have been chosen for the comparison and the result can be seen in figure 40. Most of the peaks match nicely, but a few of them are a bit off. First of as also seen above the Krakatoa does not match in the two cores, also the peak of the unknown eruption in 1810 is not a perfect match but it is very close and it could possibly be due to different post depositional effects. The Katla eruption in 1760 is also slightly misaligned again most likely due to post depositional effects, while the Komagatake eruption is nicely aligned. Comparing this to the acidity of EastGRIP

59 5. ICE CORE MEASUREMENTS: EASTGRIP 60

Figure 40: Comparison of the volcanic eruption in the NEGIS and EastGRIP cores. The depth of the EastGRIP core has been adjusted to align the peaks in the two cores. Upper left panel show Katmai and Krakatoa, upper right show Tambora and the unknown eruption, lower left show Laki and Katla and lower right show Komagatake. gives the same result except for the missing Katla peak in the acidity. Interestingly the conductivity in the EastGRIP core generally has higher values except for some of the big peaks where the values are lower. This could be due to the fact the NEGIS core was drilled in a dry borehole with no drill liquid while the EastGRIP core is drilled in a wet borehole where drill liquid is used to keep the borehole open. This drill liquid (Coasol/Estasol) might have an effect on the conductivity causing it to have higher values when it is present at the drilling.

60 6. DISCUSSION 61

6 Discussion

The reason for wanting to optimize both the sulphate and the acidity detection tech- niques is to improve the records showing volcanic eruptions. Having multiple methods recording the events of volcanic eruptions is good for validating that it is actually a volcanic eruption and not something else. The optimization is done to try and improve factors such as sensitivity, stability, detection limits or the requirements for equipment and/or chemicals making the technique better and easier to use in the field. Based on the results of using the acidity method the optimization did improve the technique for some of these parameters but it introduced at least one other problem to be discussed later in this chapter. The optimizations to the sulphate detection technique also looked promising but using the technique for measurements failed and a discussion of why will come in the following section.

6.1 Sulphate optimization The problem to be fixed with the optimization in the sulphate detection technique was flow changes during measurements. The problems with the flow was most likely caused by the columns in the system. Thus as a start the technique by Röthlisberger et al. (2000) was chosen as it only has one column compared to the technique by Bigler et al. (2007) which uses two columns. The column to be optimized in the Röthlisberger et al. (2000) technique was the cation exchange column which removes the cations interfering with the sulphate mea- surements. The problem was that particles build up in column slowly blocking the flow and causing flow changes. The existing column was exchanged with Bio-ScaleTM Mini UNOsphere S and Rapid S Cartridges 1 ml columns made by Bio-Rad. Tests using these columns showed they removed the interfering calcium ions and the flow through the column was very good for low dust concentrations while a small negative drift was seen in the flow in the test with higher dust concentrations. Thus it was deemed suitable for measurements on ice cores.

The sulphate detection technique was tested on the traverse cores A2, A3 and A6. The tests were not a success, nothing was seen in the sulphate signal it was either just a flat line or a negative drift with no features looking like real signal. Also a lot of problem with back pressure was encountered. Even the standard series did not show any signal, a test was done using a lot stronger standards (122.6 mg/L H2SO4). This resulted in a response so big it went above the upper limit of detection in the system and showed that the technique did work. Based on the this it is suspected the reason for not seeing any signal in the ice cores is due to the detection limit being too high and thus being above the highest concentrations seen in the ice. During the measurement multiple things was done to try and fix the technique. The lengths of the mixing coils were shortened which fixed the drift in the signal and also

61 6. DISCUSSION 62 the problems with high back pressure, but this just gave the flat line with nothing but noise. The shorter mixing coils also reduced the amount of air bubbles produced by the reaction between the reagent and sample. The lines were reduced in length to try and lower the effect of diffusion and new reagent and buffer was made using the same recipe to see if this would help. Nothing of the above helped and the sulphate measurements of the traverse cores ended up being a failure. The limit of detection being to high is thought to be caused by the use of old chemistry. All the chemicals used to make the reagent and buffer was at least four years old as they were used in the spring of 2014 last before this project. They may be even older as some of them could have been used before this. The chemicals being this old could cause them to not work optimally and as the detection technique is very sensitive to the 1:1 ratio of MTB to barium chloride this could be the reason for the techniques detection limit being worse than that reported by Röthlisberger et al. (2000) and being to high to actually measure the concentration found in ice cores. Another thing that may have caused some instabilities in the system was that the setup made for melting of the traverse cores used all the old lines, connections and mixing coils from 2014. These might have been dirty and should in hindsight all have been remade using fresh tubing.

6.2 Acidity optimization The problem with the acidity detection technique was air bubbles getting stuck in the detection cell and blocking the signal. The air bubbles getting stuck is most likely due to the geometry of the z-cell used for the absorption detection. To fix the problem the z-cell was changed with an absorption cuvette which is being used in other absorption detections techniques like the one used to detect nitrate and sodium [Röthlisberger et al. 2000]. Tests of running standard series using the cuvette showed it had a similar detection limit, provided the same temporal resolution and with a better response time than the z-cell. However due to having a light path of only one centimetre to the two centime- tres of the z-cell the sensitivity of the cuvette is only half that of the z-cell. How it handled air bubbles was not tested in the standard series as it can be hard to recreate the pattern of air bubbles created during actual measurements. However a test that quantitatively can show how well different absorption cells handle air bubbles would be good to develop and use. As of right now how well cells handle air bubbles is solely based on experience from the experimenters and this is not a very scientific measure and thus some test showing that this experience actually can be recreated would be good. This could be done by connecting two lines, one with water and one with air and pump the combined water/air stream through the absorption cells. The problematic part of this is to create a ratio of air to water and sizes of the air bubbles that resembles that of measurements on ice. If this ratio is not recreated it could lead to results that do not match with what would be seen during real melting.

62 6. DISCUSSION 63

The ratio between air and water should be mostly water with occasional air bubbles, thus the pump settings should be set to pump very little on the air line.

The acidity detection technique was used during both the traverse melting campaign and the EastGRIP melting campaign. During both campaigns the technique produced good data and had no problems with air bubbles getting stuck during the more than 100 hours of melting ice. This is a good indication that the cuvette works better than the z-cell, at handling the air bubbles. However a problem not seen before while using the z-cell arose during the measure- ments using the cuvette. Sudden drops in the baseline began to happen, especially during standard series. This was mostly seen during the measurements in Bern during the EastGRIP campaign, it only happened twice during the traverse campaign. Dur- ing the setup period in Bern it happened a lot and it was determined that it was due to movement of the optical cable going from the absorption cell to the spectrometer. The reason this happened more during the EastGRIP campaign than during the traverse campaign is due to the fact that the acidity technique shared a table with the two iron techniques in Bern. Both the iron techniques were still somewhat experimental, and thus work was being done on the technique during the campaign. With the two iron techniques being so close to the acidity technique and sharing a pump as well, the work on the iron techniques often required handling of lines located close to the optical cable to the acidity. This caused the cable to get bumped quite often and causing the signal change, luckily this was mostly during calibration runs where a new standard series could be run after the baseline change. This is also the reason the problem was not seen that often during the traverse campaign as nothing was done around the acidity technique. Different things were done to try and fix this problem, a new optical cable was tested but with the same result as before. Also a new spectrometer was tested but again with no effect. As the problem was not fixed by this as much as possible was done to prevent the optical cable from moving. It was tightened as much as possible to the table and in a position with as low risk of being touch as possible. With this setup the amount of times the optical cable was touched was lowered significantly and mostly during calibrations. During the processing of the data these drops in baseline were handled by aligning the data after the drop to the data before the drop. This was done by taking the mean right before and right after the drop and then lifting all the data after the drop to match the data before and the data from right when the drop happened was discarded. The reason to align it with the data before is to be able to use the calibration made before the run. The conductivity measurements were used to check that no major events happened during the drop and to make sure the mean before and after could be used for the alignment. If it happened during a calibration, a new standard series was made with a baseline matching that of the following measurements.

Later after both of the measurement campaigns were done, the problem with the

63 6. DISCUSSION 64

Figure 41: The absorption cuvette used in the acidity detection technique. The small lighter circle which is circled by a red circle is the hole which the light can pass through. dropping baseline is thought to have been identified. After a closer inspection it has been found that the hole for the cuvette in the cuvette holder for keeping the cuvette in place is slightly too big for the cuvette. This would make it possible for the cuvette to move if the cuvette holder or anything attached to the cuvette holder like the optical cable is being touched. If the cuvette moves it will change the amount of light going through the cuvette. The light only has a small hole to pass through in the cuvette, the hole can be seen in figure 41. With such a small hole even the slightest movement of the cuvette will cause a change in the light passing through into the optical cable and leading to a drop in the absorption.

During the recent SubACE melting campaign in Copenhagen the acidity method was used and the problem of the moving cuvette was fixed by placing a piece of paper in the cuvette holder together with the cuvette to prevent it from moving. This worked as no problems with drops in the baseline happened during this two week campaign. A more permanent solution to the problem would be to make a holder for the cuvette that has a more tight fit preventing the cuvette from moving. The new holder should also try to minimize the distance between the optical cable and light source to give a

64 6. DISCUSSION 65 more stable signal. Optimally it would also be place in a box which would keep all other light than what is coming from the light source out, to avoid the ambient light to interfere with the measurements.

The problem of the conductivity measurements of the Bern system and Copenhagen systems from the EastGRIP not matching each other is bad for the alignment of the acidity with all the measurements from the Bern system. The alignment is important as if the acidity measurements are off compared to the rest of the measurements then the interpretation of the data gets harder to do as peaks in other species that normally show up the same time as peaks in conductivity now will be seen at a slightly different time. As explained above the differences might be due to the very long line going from the Bern system to the Copenhagen system, in which particles can build up over time and cause changes in the conductivity. This could be fixed in multiple ways. The line be- tween the two system could be made shorter which would reduce how long the sample has to travel before the measurement and this would lower the risk of contamination. However due to the layout of the laboratory in Bern this solution is not a possibility unless the acidity detection technique were to be built into the Bern system. The other thing that can be done is to do regular exchange of the tubing going between the Bern and Copenhagen systems. This would get rid of the tubing when particles begin to build up and replace it with clean tubing which should lead to the two con- ductivity signals being more alike. This is also a really easy fix to do as it would only take a few minutes every to every other week.

6.3 Spatial variability The low correlations found in the conductivity and acidity records of the traverse cores can most likely be explained by post depositional effects such as winds moving the newly precipitated snow and diffusion in the snow and firn and/or errors in the dating of the cores. The noise from the post depositional effects are most likely due to sastrugi forma- tion which are sharp irregular grooves or ridges formed on the snow surface by wind erosion [Gfeller et al. 2014]. Since the sastrugi is formed by wind erosion the wind speed at the drilling site is a big factor as the higher the wind speed the larger the noise effect of sastrugi formation. The noise from the sastrugi is also influenced by the accumulation rate at the drill site and higher accumulation leads to less noise. The average wind speed at EastGRIP the past year has been 8 knots which is 355 km/day [http://alice.egrip.camp/] while the average wind speed at Humboldt and Camp Century (weather stations closest to NEEM) has been significantly lower with a maximum of 125 km/day [Steffen and Box 2001]. There is also quite a difference in the accumulation rates, at NEEM the annual mean accumulation is estimated to be 0.226 metre water equivalent (m w. eq. a−1) while at EastGRIP it is estimated to 0.10 m w. eq. a−1 [Buizert et al. 2012, Vallelonga et al. 2014]. This shows that there

65 6. DISCUSSION 66 is a lot of variation in the wind speed and accumulation between the drill locations of the traverse cores and thus the effect on the noise of the signal due to sastrugi formation is very different for each core. The combination of different effects on the noise from post depositional effects and possible errors in the dating of the cores show that the conductivity and acidity records can not be used to reconstruct atmospheric variability in the traverse cores.

The difference found between the NEGIS and EastGRIP conductivity records are not many, but some are present. Focusing on the volcanic eruptions in figure 40 it can be seen that most of the eruptions match very well between the cores. The Krakatoa eruption is most likely not seen in the NEGIS record and if it is, it is very badly aligned to the EastGRIP record which would be hard to explain as all the other erup- tions match quite well. The unknown and Katla eruptions not matching the that well can be explained by either post depositional effects or most likely by errors in the depth estimation in one of the records. Looking at the smaller features in the records a lot of variation between the two records is seen. In some sections quite similar peaks and troughs are seen while in other they look very different but in general the two records seems to follow the same trends. In sections where the peaks and troughs look different it is most likely due to a combina- tion of post depositional effects and errors in the depth assignment while in sections where the peaks and troughs looks the same but are found a slightly different depths it is most likely due to the post depositional effects. In general the records can be compared when looking at larger events such as vol- canic eruptions while smaller events such as seasonality and annual signals can not be compared.

66 7. CONCLUSION 67

7 Conclusion

In this project the two continuous flow analysis methods for sulphate and acidity have been optimized and used for measurements on the six ice cores from the 2015 traverse from NEEM to EastGRIP and the first 350 metres of the EastGRIP ice core.

The sulphate technique was optimized to reduce the problems with flow changes af- fecting the measurements. This was done by replacing the home made cation exchange column with Bio-ScaleTM Mini UNOsphere S and Rapid S Cartridges 1 ml columns made by Bio-Rad. Tests were performed to determine if the Bio-Rad columns were able to remove the ions interfering with measurements of sulphate and how the columns handled the flow when measuring ice samples. The Bio-Rad columns proved to be just as capable of removing the calcium ions as the old CEC, as none of them left any measurable amount of calcium. The flow was found to be very stable for the Bio-Rad columns when there were low amounts of dust in the ice samples but they had a slight negative drift during measurements of higher dust concentrations. The sulphate detection technique was used during the melting of the A2, A3 and A6 cores. But at no point during measurements was any signal observed in the sulphate. It was tested using both the Bio-Rad columns and the old column which has been proven to work by Jensen (2014), the detection limit was simply too high. The lack of signal is suspected to be caused by old chemistry, all of the chemicals used to make the reagent and buffer were from 2014 or earlier. This might have lead to some differences in properties of the chemicals and as the Röthlisberger et al. (2000) sulphate technique is very sensitive to the 1:1 ratio of MTB to barium chloride this might explain why the detection limit was not as low as expected.

The optimization done to the acidity technique was to replace the absorption cell from a 2 cm z-cell to a 1 cm cuvette. This was done to remove the problem of air bubbles getting stuck in the absorption cell. Tests of the response time, limit of detection and sensitivity were made using both the cuvette and two z-cells with different light path lengths (1 cm and 2 cm). These test showed that the cuvette has the same limit of detection as the 2 cm z-cell. The sensitivity of the cuvette is half that of the 2 cm z-cell as expected from Beer-Lambert equation 1 due to having half the path length. However the response time of the cuvette has been reduced from the 45 seconds of the z-cell to 36 seconds. This lets the cuvette better show narrow peaks, while the lower sensitivity will lead to a loss of small scale variations. No test were done to see if air bubble would get stuck as that clearly would be shown during measurements of actual ice core.

The acidity detection technique was used during the melting of all the traverse cores and produce good data from which the spatial variation could be tested and large

67 7. CONCLUSION 68 volcanic eruptions could be detected. There turned out to be high spatial variation as none of the cores had any significant correlations in neither acidity or conductivity. However some of the detected volcanic eruptions were seen in multiple cores. The 2015 Bárðarbunga and the 2011 Grimsvötn eruptions were seen in all six cores except for A4 where Bárðarbunga was not seen. The other eruptions found in the traverse cores where present in three or less cores without any spatial patterns of which cores. Some of these eruptions include the 2010 Eyjafjallajökull and 1989 Redoubt eruptions which were seen in multiple cores.

The acidity detection technique was also brought to Bern for measurements during the EastGRIP melting campaign. During the setup in Bern a problem causing the baseline to drop was encountered, a problem that could be fixed in processing but caused a loss of some data. This was due to the optical cable being touched and at the time this was thought to be the problem and it amount of times it happened was reduced slight changes to the setup. Later it was found that the problem most likely is due to movement of the cuvette in the holder, as the slot for placing the cuvette is slightly too big and thus the cuvette will move around when the system is touched. This should be improved on in the future by making a holder for the cuvette with a more tight fit to avoid the movement. Even with the problems a nice acidity and conductivity record was achieved. These were used to determine very large events (> 5 σ) in both acidity and conductivity. These events were caused by volcanic eruptions and in some cases for the conductivity big wildfires. Some of the eruptions found in the EastGRIP core were Katmai in 1912, Krakatoa in 1885, Tambora in 1815, Laki in 1783 and quite a few other large eruptions back in time. Some diffusion causing 12±1 % lower values in the Copenhagen conduc- tivity was found by comparing the Bern conductivity to the Copenhagen conductivity measurements. This diffusion is most likely due to the very long line between the Bern and Copenhagen systems and should be taken into account when interpreting the data. When comparing the two conductivity records to each other it was also found that the correlation between decreased with time. Making the alignment of the acidity record with the Bern records harder. This is most likely caused by build up of particles in the long line between the Bern and Copenhagen system. These particles would then influence the conductivity of the sample and as more build up the effect would get bigger causing the Bern and Copenhagen conductivity records not to correlate.

68 REFERENCES 69

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Appendix A

This appendix is the manual written for running the Copenhagen part of the system in Bern laboratory during the EastGRIP melting campaign. The campaign lasted multiple weeks and the person running the system was changed during campaign, thus the manual was written to make it easier for the new person to run the system in the same way as the previous person. It includes maintenance of the system, how to do a standard series and how to prepare the standards, start up and shut down of the system, what to do to before, during and after melting ice and also a troubleshooting section. All this is documented with pictures to make it easier to understand. The manual was revised by Helle Astrid Kjær, to make sure nothing was forgotten.

74 In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944 Manual for Bern EGRIP pH and conductivity measurements Written by Kasper Holst Lund, 9th January 2018. Reviewed by Helle Astrid Kjær 12th of January

Thanks for helping collecting discrete samples and running the pH dye line for the EastGRIP campaign. The pH can be used to identify volcanoes and see the anthropogenic contamination. The discrete samples will be used for Sea ice reconstruction and dust analysis.

Remember to pay attention to changes both in the pH and discrete sampling lines, but also to changes in the remaining system. Note there is no such thing as too many notes in the logbook- so keep writing 

Do not hesitate to ask other people in the laboratorie or to call either Helle (+45 50528004) or Kasper (+45 29824944) if you are in doubt about anything.

Final word of advice-Have fun!!

REGULAR MAINTENANCE

Daily: Morning: – Check that the approximately 30x15 mL vials for this days ice melting are labelled and ready for both Venice sampling (ICP) and Copenhagen sampling (CC). If not label them. Evening: – Copy data to USB from ”C:/Users/cfa/Desktop/CFA/14 Data/EastGRIP. Unplug mouse USB and use that port – Check if pump tubings needs to be changed – Label at least 30 vials for each discrete sample for the next day and pack them in the plastic back you took them from, with another plastic back around to seal them, label plastic bags with start and end vial. – Check amaunt of reagent left in the bottle and refill if necesarry. Remake reagent in case you use one-remember to write in reagent log.

Monday and Wednesday mornings – Change pH sample and pH reagent pump tubing prior to startup of system (The ones colour coded pink only needs changing when they stop working). Double check you have the right color (sizes). Only loosen one line at the time. You find spare pumptubing in the white cardboard box in zarges box 511. – Change reagent – remember to write in reagent log – Prepare a new reagent (There should always be one spare) – remember to write in reagent log In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944

START UP

1. Turn on the laptop (user: cfa, password: impurities) 2. Check if there is MQ in the sample bottle in the back of the table in the middle (labelled ”Milli-Q”) 3. Check if there is MQ in the reagent bottle in the back left of the table (labelled ”Reagent MQ”) 4. Set valve 1 on pH line to the standards position (on table left of pump) 5. Set valve 2 on pH line to the MQ position (on table left of pump) 6. Plug in heat bath in the power chord on the left hand side of the table. Display should show the room temparature and slowly increase towards 65 degrees C. 7. Turn on vacuum degasser, it is a white box to the right of the computer, with a switch at the top right back. Light should turn on when switched on. 8. Turn on EC meter it is a beige box underneath the vacuum degasser, with a switch at top left back. Display should show a value approximately at 0.1 μs 9. Turn on LED by connecting the LED cable with the power cable. Both cables should be on top of the EC meter to the left of the vacuum degasser. There should be light in the absorption box when it is on. 10. Connect all the pump tubing to the pump (checking with Tobias/Camilla if ok to start O18, with Francois for iron) 11. Turn on pump, using the switch at the back top left. Display should show 27.0 and the light should be blinking at the PUMP% and flow rate light. 12. Check that there is flow in both the sample and reagent line. 13. Open Labview 2013 on the computer (NB-Never use labview 2009). 14. Open DAQ-Remiland2018-EGRIP (If it opens in block diagram (the program behind the interface), press the ”Window” menu and then press ”Show front panel” and close the block In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944

diagram)

15. Go to the ”pH absorption” tab and check that the integration time is 35000 μs 16. Go to the ”instrument communication” and check that pH and conductivity is enabled and Na is disabled.

17. Go to the ”output file” tab an check that the folder path is ”C:/Users/cfa/Desktop/CFA/14 Data/EastGRIP 18. Click the “RUN” button (right pointing arrow) on the toolbar at the top left of the screen. 1. Data should coming in the top and bottom windows. 2. In the ”pH absorption” tab the pH spectrum should be visable in the bottom left. 19. In the ”pH absorption” tab check that the pH channel is set to 300, 670 and 690 (which In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944

should give wavelength of 452nm, 585nm and 592nm. 20. Switch the reagent line from MQ to pH reagent. Within two minutes a decrease in the pH count should be observed.

RUNNING STANDARDS

1. Prepare HCl standards (and NaOH if data below baseline have been observed during an ice run (NB- not if it is just caused by airbubbles. See troubleshooting)) 2. When standards are prepared and the baseline is stabil, you are ready to do a standardseries. 3. Connect the pH standards to valve 2 (the tubes are labelled 1.2 and 2.4). 4. To clean the lines from air, check that all lines including Fe and discrete are connected to the pump. 5. Change valve 1 from ”ST” to ”CFA”. This way whatever is run on valve 1 goes directly to waste, whereas the pH measurements sees whatever comes from the red valve (milliq from our table or CFA milliq or ice from Bern CFA) 6. Change valve 2 to each of the two standards and run for at least 20 s or as long as it takes to empty the lines from air 7. Set valve 2 back to ”MQ” 8. Set valve 1 back from ”CFA” to ”ST” 9. Go to ”output file” and press the ”Standard?” button 10. Press the ”Save” button (turns green when saving) 11. Write filename down in labbook 12. Get a standard log sheet, write filename on log sheet and prepare to note down the baseline and standard values. 1. Run MQ for at least 60 s, or as long as it takes to get a baseline In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944

2. Run standard 1 (2.4) for 120 s by switching valve 2 3. Run standard 2 (1.2) for 120 s 4. Run MQ for at least 120 s, or as long as it takes to get a baseline 13. Press the ”Save” button to stop saving 14. Change valve 1 back to ”CFA”, so you are running on common (Fe, pH, O18) system

STARTING A RUN OF ICE

1. Start saving a new file before each run, with the file “EGRIP-XXX”, where XXX idenify the first bag number. Write the filename in the labbook. Check that a yellow bar appears below the pH window, indicating that data is being saved. 2. Check that valve 1 is set on ”CFA”, so you are running on common (Fe, pH, O18) system 3. Check that red valve on the left side of the table is set on sample (small star next to sample), so that common (Fe, pH, O 18) is recieving water from main CFA 4. Move both (CC-CPH on Bern side, ICP-Venice on local pump) discrete sample lines from waste line to the vial line (after checing that main CFA is running only milliq-ask Tobias or Camilla) 5. When the 5 cm milliQ ice is put on the melthead look at the red light on the Bern system (see picture for location) when that turns green press ”MQ/SPLE” on the labview software. 6. After ~1m 40s the MQ ice signal should arrive with a decrease in the conductivity (normally down to values below 1). 7. When the real ice hits the melter press the button ”new bag” and start the timer counting up. 8. When the real ice arrives (~1 min 40 sec after it is on the melter) the signal in conductivity incresease (~2min), when this is seen in our system, then change both of the discrete vials from waste vials to collection vials and press the ”LOG” button in the Labview program. Write the vial number (should match the current bag on the melter) and computer clock time of changing in the labbook. In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944

9. Look at EastGrip bag list, in the right most column the melt time of each bag is noted. Check the timer to see approximately when to expect the next bag on the melter... In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944

DURING MELTING (5 cm milliq ice, 6 Bags, 5 cm milliq ice)

The discrete vials should be changed every bag. NB! We do not get a notification from the main CFA, so we have to be aware of bag chnages ourselves. To determine when to change the disrete vials /when a new bag is on melter), there is two ways (ideally you use both);

1) Look at EastGrip bag list, in the right most column the melt time of each bag is noted. Set an timer to count up at each bag break and keep track of the time of the expected melting time on the bag sheet. When the timer reaches 2 min prior to the expecetd melting time, go to the freezer window and look at the ice in the bottom. When you see the bag break on the melter, restart the timer. When the timer reach 1 min and 35 sec change both the discrete vial to the bag and press the ”LOG” button and write vial number and computer clock time in the labbook. 20 min melting time should be equivalent of a little more than 10 mL wate in the discrete vials.

2) Also you can keep an eye on the ”Approx ice length” field on the Bern CFA laptop on the tables to the left. When that nmber matches the numbers on the note (5, 60, 115, 170, 225, 280 and 325) on the pH labtop it should be close to a bag change. So go to the freezer window and look at the ice in the bottom. When you see the break wait 1 min and 35 sec and then switch both discrete vials and press the ”LOG” button and write vial number and computer clock time in the labbook.

3) NB! If you are certain you have missed a bagbreak, immediately change the vial

When there is only 2 bags left to melt you can prepare the next set of standards (but still remember your vials!!)

AT THE END OF AN ICE RUN

1. At the end of the 6th bag. Melting of 5 cm milliq ice will start. Press the MQ/SPLE Button. Also again start the timer. After only 1min switch collection vials to waste vials and press ”log”. We switch early to ensure we do not get milliq ice into our collection vials. 2. Look at the green light on the Bern system (see picture for location) when that turns red, note the time in the logbook. 3. When the baseline of both pH and cond is stable and have run for ~5 min, press the ”Save” button to stop saving.

SYSTEM SHUTDOWN

1. Stop saving the data 2. Ensure that the end-of- day standards have been run. 3. Disconnect pH reagent lines from their reagent bottles and connect the lines to the“Reagent MQ” bottle to clean lines. 4. Let the tubing flush with MQ for at least 5 minutes. 5. Stop the labview software. 6. Turn off the instruments: ◦ Unplug heat bath ◦ Vacuum degasser In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944

◦ EC meter ◦ Disconnet LED 7. Stop the pump and release the tension off the pump tubing (check with O18 people and Fe people before doing so) 8. Check pump tubing on all pH and discrete lines, if squeezed or broken change them (New pump tubing in white box in zarges box) 9. Transfer data files to USB stick. Unplug mouse USB and use that port 10. Turn off the computer 11. Label 2 x 30 vials for the next days ice melting

TROUBLESHOOTING

Ice melting stopped at weird time (eg. Ice lifted due to being stuck) If the ice is for some reason stopped in the middle of a run. 1. Press the MQ/SPLE Button, when ice is lifted from melthead. Note in logbook. Again start the timer. After only 40 sec switch collection vials to waste vials and press ”log”. We switch early to ensure we do not get last contamination/milliq water in our collection vials. 2. Look at the green light on the Bern system (see picture for location) when that turns red, note the time in the logbook. 3. Label the vials that collected the melt water until the run stopped with an A added to the bagnumber (eg. 055A) 4. When the baseline of both pH and cond is stable and have run for ~5 min, press the ”Save” button to stop saving. 5. Start a new file labelled the EGRIP-XXXB. (eg EGRIP-055B) 6. Note in logbook how much of ice was left and is now ready on the melter again (eg. How long is core section XXXB). 7. Note if milliq is added to the run prior to core piece B. 8. Label a new vial (unlabbeled ones can be found in Zarges box 511) EGRIP-XXXB 9. Follow normal start procedure of how to start a run. (If the ice is now lifted again, follow procedure using the number C, D E etc. )

Spectrometer Issues Can't see spectrometer in Labview tab ”pH absorption”. (can happen if USB from spectrometer has been pulled out) – In the ”Instruments Comm” tab check that the pH USB address is “USB::Ox2457::0x101E::NI-VISA-10003::RAW”. Choose it. (note numbers can be slightly different if another USB port is used) If nothing like the above appear in the drop-down list – Check the spectrometer USB cable is connected to the computer. – Open Hardware settings and check the devices list. The spectrometer should be listed as USB2000 within the NI-VISA folder – If that does not exist find the spectrometer under ocean optics in the devices list. Reinstall drivers using this driver found in the folder "C:\Users\cfa\Desktop\CFA\DAQRenland2015\Spectrometer" In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944

Spectrometer not reading the expected spectrum – Check that LED is plugged in and LED lamp is working – Check that the optical cable is sitting at a good position – Check the optical cable is reacting by putting it drectly towards a ceiling lamp. If it isn’t change the optical cable – Increase integration time, you do this by stopping the labview program from running, Going to the ”pH absorption tab”, and changing the integration time. Then start running again. If you like this integration time better (should never be above 500.000 uS). Stop the labview program from running and at the spectremeter integration time field. Right click with the mouse and choose ” data operations” and choose ”Reinitialize this value to be the default”, save the labview program. This way Labview remembers the new integration time for next time. Write down in the logbook that the int. Time was changed. In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944

– Change spectrometer (Rember to check wavelengths and int. Time after a change)

Incorrect wavelengths – Quit the software – In ”pH absorption” tab change the pH channels array in input (Higher if wavelength is too low and lower if too high) – Run program again – Repeat this til you get the correct wavelengths – When right wavelengths are found, save them by right clicking in the ”pH channel array” field. Choose ”Data operations” and choose ”set current value as default”. Save the labview program.

Sudden change of baseline - If large change, likely the reagent has run empty. Replace reagent and remember to write down in the raegent log and prepare a new one. - If small change in baseline (eg. A couple of 100 counts) likely someone touched the spectrometer or the optical cable. The spectrometre and the optical cabe is very sensitive to touching. Try to ask people not to touch them, avoid touching them youself unless necessary. If in the middle of the run continue to the end, extra careful not to touch optical cable and spectrometer. Then run a new set of standards to have something that fits the new baseline. Then you can try to fix baseline and reading counts, if you find it is necessary. If you make changes run the standards again in a new STD file. Note down carefully all changes.

Air in system – Check that you have not run out of reagent. – Check that vacuum degasser is on – Check lines going in and out of the flow cell (they need to be going straight up) – Check all connections and fitting to see if any of them are loose. If you suspect they are untight, and you do not know how to fix it, ask someone experienced to help you (camilla, tobias, Francesco) eg . by making new lines or tighten nut using white ”plaster”.

LED not working – Check that the LED is plugged in – Unplug LED and carefully unscrew it from the flow cell – Check LED is working, if it is not remove broken LED lamp – Get a new LED lamp (LED SUPER WHITE 6000 MCD) from the brown box in the zarges box – Cut the legs to a fitting length (eg. By comaprong to old LED, remember to keep one longer leg) – Attach new LED lamp, long leg to positive (red wire) – Connect LED back to flow cell and plug in – If there is no light try flipping the LED lamp so the long leg goes to the black wire

Data below baseline – Check if the decrease below baseline in pH goes down at all three wavelengths – If this is the case it is caused by a flow change or an air bubble – If air bubble and low data persists go through the ”Air in system” troubleshooting – Do not make NaOH standards in this case In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944

– If the green and red wavelength goes down but the yellow goes up (or stays straight) – Run NaOH standards at next calibration

Can't find pH Labview program

REAGENT PREPARATION

Always wear gloves. Always clean up any stains on table, pippette etc.

The pH reagent runs with aprox 0.14 mL/min and thus 1 L should last at least 3 whole days. A new reagent is prepared immediately after the reagent on the system is changed to ensure we always have a spare ready. In the plastic bag marked ”Reagent pH” you will find everything you need, it is located in the zarges box. Use the 250 mL beaker to measure 650 mL of MQ water and transfer this to the reagent bottle. Further meeasure off additional 50 mL of MQ water and pour it into the bottle labelled "pH dye cleaning". Add to the reagent bottle 0.025g (±0.001g) Bromophenol blue and 0.025g (±0.001g) Chlorophenol red to the reagent bottle– these should be already premaesured and can be found in green-lid plastic tubes in the plastic bag labelled with the dye name. To get all the dye out of the small vials and into the reagent bottle, add to the dye bottles 1 mL of MQ from the "pH dye cleaning bottle to the dye vial, shake it and pour it into the reagent bottle, do this at least five times. Add the remaining MQ from the "pH dye cleaning" bottle to the reagent bottle (total milliq in reagent now 700 mL). Note that the precise mixture of the dye will have a huge influence on the sensitivity, so it is absolutely necessary to transfer the entire contents of the green-lid tubes into the bottle. When the dye vials are empty put them in the platsic bags labelled "Used Bromophenol Blue/Chlorophenol Red vials". Add 100 uL Brij to the reagent using a pipette. Place the now readymade reagent on a magnetic stirrer for ideally 24 hours. Remember to note down in the ”Reagent log” when the reagent was made, and out a poster on the In case of any questions do not hesitate to call Helle: +45 50528004 Or Kasper +45 29824944 reagent to also indicate this.

STANDARD PREPARATION

Always wear gloves. pH HCl standards are made fresh before each calibration, and run for each calibration. NaOH standards are only made if you see signal below baseline.

First dilution • Intermediate HCL: Put 600 uL of HCL (0.1 M) in 60 mL of water • Intermediate NaOH: Put 600 uL of NaOH (0.1 M) in 60 mL of water (only if needed, check baseline of previous run)

Second dilution • St1 - HCl: 2400 uL intermediate HCL in 120 mL MQ • St2 - HCl: 1200 uL intermediate HCL in 120 mL MQ

• St1 - NaOH: 1200 uL intermediate NaOH in 60 mL MQ • St2 - NaOH: 600 uL intermediate NaOH in 60 mL MQ

To get 120 mL milliq water weigh the bottles on the scale and set the scale to zero, then add water until the scale reads 120 g. Do this for each of the ST bottles. You can not assume they have the same weight when empty. NB! Never take the line out of the bottles!! EGRIP Fe total/Fe II/pH/discrete Venice CFA setup Holocene ice (0-350m) 2.5 cm/minute melt rate Updated: 2 Jan 2018

From main CFA milliQ -SPLE/milliQ -local

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bl/bl bl/bl pH ST line

pH ST1 bl/bl V1 pH V2

bl/bl ST2 Fe II pH sample bl/bl 65C degasser Abs bl/bl gr/or Fe tot pH reagent gr/or O18 Discrete collection