REYST LEI‹ARLÍNUR

Indra Suryata

REYST report 04-2010

Indra Suryata Carbon Footprint A

ssessment and Its R

eduction Efforts R

EY

ST report 04-2010

Carbon Footprint Assessment and Its Reduction Efforts:

The Case of Blue Lagoon Company

REYKJAVÍK ENERGY GRADUATE SCHOOL OF SUSTAINABLE SYSTEMS

Reykjavík Energy Graduate School of Sustainable Systems (REYST) combines the expertise of its partners: Reykjavík Energy, Reykjavík University and the University of Iceland.

Objectives of REYST:Promote education and research in sustainable energyAttract talented graduates into the important field of sustainable energyProvide industry and academia with qualified experts in engineering, business and earth sciences

REYST is an international graduate programme open for students holding BSc degrees in engineering, earth sciences or business.

REYST offers graduate level education with emphasis on practicality , innovation and interdisciplinary thinking.

REYST reports contain the master’s theses of REYST graduates who earn their degrees from the University of Iceland and Reykjavík University.

REYST LEI‹ARLÍNUR

REYST LEI‹ARLÍNUR

 

Carbon Footprint Assessment and Its

Reduction Efforts: The Case of Blue Lagoon Company

Indra Suryata

MSc in Sustainable Energy and Engineering

Supervisors: Halldor G. Svavarsson Sigurbjörn Einarsson Ása Brynjólfsdóttir

Reykjavík UniversitySchool of Science and Engineering/REYST

January 2010

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Carbon Footprint Assessment and Its Reduction Efforts: The Case of Blue Lagoon Company 30 ECTS thesis submitted in partial fulfilment of a Master of Science degree in Sustainable Energy and Engineering Copyright © 2010 All rights reserved School of Science and Engineering/REYST Reykjavík University Menntavegur 1 IS-101 Reykjavik Iceland Telephone: (354) 599-6200 Bibliographic information: Indra Suryata, 2010, Carbon Footprint Assessment and Its Reduction Efforts: The Case of Blue Lagoon Company., Master thesis, Reykjavik Energy Graduate School of Sustainable Systems, Reykjavik University & University of Iceland. ISBN XX Printing: ver. 1 Reykjavik, Iceland, 28 January 2010

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ACKNOWLEDGEMENTS

I would like to express my gratitude to Edda Lilja Sveinsdóttir, the director of REYST School, REYST board members and REYST academic council members for having offered me the opportunity to attend this school and for their guidance throughout the entire school period. I am indebted to my supervisors, Dr. Halldor G. Svavarsson, Sigurbjörn Einarsson and Ása Brynjólfsdóttir for having been there the whole way and providing a friendly and supportive environment for me to accomplish my research along with much guidance. The lecturers at the University of Iceland, Reykjavik University and REYST School provided a great learning experience and I sincerely thank them. The staffs of Blue Lagoon Company with whom I interacted in the course of working on my project have been a great inspiration and special thanks are due to them. My colleague at work, Grzegorz Maliga, and the rest of the students whom I had useful topical discussions are really appreciated. I would also like to thank the organizations that provided financial support; the REYST School and the Blue Lagoon Company. This work is dedicated to my family for their encouraging efforts and full support during the study and to all the scientists who capably work long hours and collectively labored in all effort to bring comfort and control to all our lives.

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ABSTRACT

In general, energy efficiency has shown inconceivable results, and is likely to show more success stories ahead in delivering valuable carbon and cost savings for business. However, the effort to mitigate the climate change will require more fundamental changes to the way that business delivers products and services to the end customer. This report will describe a practical approach to reduce carbon emissions in the Blue Lagoon Company, by understanding and optimizing emissions across full product supply chain. It is believed that supply chain intervention approach is a new ways of reducing carbon emissions, just as companies have been using supply chain analysis to deliver financial benefits for many years. The thesis may be divided into two parts, one major part which deals with life cycle analyses of product in respect to green houses gas emission and one minor part which explores the possibilities of CO2 mitigation from Svartsengi geothermal power plant by microalgae which grow naturally at the Blue Lagoon site. A system has been designed for the reduction process and parameters for growth were varied to optimize the process. Based on these studies, the following is concluded:

Business energy efficiency and low-carbon energy supply have played, and will continue to play, an important role but more fundamental solutions are also needed. Managing the carbon footprint of products across the supply chain is just such a solution.

Managing the carbon footprint of a product means minimizing the carbon emissions required to deliver that product to the end consumer. The carbon footprint of a product is the carbon dioxide emitted across the supply chain for a single unit of that product.

In the case of Blue Lagoon pilot project of 200 ml Silica Mud Mask, the largest (63%) carbon emitter in the supply chain was found to be the processing phase. This phase involves the mixing and packaging processes which consume large amount of electricity.

The 200 ml Blue Lagoon Silica Mud Mask emits 137.73 grams-CO2e in emissions caused by each material and process across the product’s life cycle, and therefore the final product carbon footprint.

CO2 fixation by using fast-growing blue green microalgae proved to provide a very promising alternative for mitigation of CO2.

Fixing CO2 from industrial exhaust gases such as geothermal power plant’s flue gases is feasible.

The carbon dioxide fixation rate for Blue Lagoon blue-green microalgae is approximately 18% vol. (only 18% vol. of the supplied CO2 is absorbed by microalgae, while the remaining CO2 gas is has escaped from the system).

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TABLE OF CONTENTS

INTRODUCTION…………………………………………………………………. 1

i. Background – The Blue Lagoon Company………………………... 1 ii. Product carbon footprinting………………………………………... 2

iii. Carbon sequestration ………………………………………………. 5

PART I 1 CARBON FOOTPRINT ANALYSIS AND APPLICATIONS…… 6 1.1 The assessment approach………..…………………………………. 6 1.1.1 PAS 2050…………………………………………………... 6 1.1.2 ‘Use phase’ emissions……………………………………… 7

1.2 Product(s) analyzed………………………………………………… 7 1.3 The detailed methodology…………………………………………. 8

1.3.1 Step 1: Building a process map…………………………….. 8 1.3.2 Step 2: Checking boundaries and prioritization……………. 10 1.3.3 Step 3: Data Collection…………………………………….. 12 1.3.4 Step 4: Calculating the footprint…………………………… 16 1.3.5 Step 5: Checking uncertainty………………………………. 22

1.4 Summary of Part I………………………………………………….. 23

PART II 2 CARBON EMISSION REDUCTION by means of microalgae

cultivation………………………………………………………….. 26 2.1 Carbon fixation processes………………………….. ……………... 26 2.2 Microalgae………………………………………………………… 26 2.3 Growth method…………………………………………………….. 28

2.3.1 Raceway ponds……..……………………………………… 28 2.3.2 Photobioreactors…………………………………………… 28

2.4 Experimental……………………………………………………….. 30 2.4.1 Parameters optimization……………………………………. 31 2.4.2 Utilization of geothermal power plant’s CO2……………… 35 2.5 Summary of Part II…………………………………………………. 41

RESULTS AND CONCLUSIONS……………………………………………….. 44 REFERENCES…………………………………………………………………….. 46 APPENDIX A: Poster presented at Icelandic Chemical Conference……………… 48

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LIST OF FIGURES 1. The heart of Blue Lagoon's operation is at the Blue Lagoon,

Iceland's most unique and popular attraction……………………………… 1 2. Five steps in calculating product carbon footprint……………………………… 7 3. The 200 ml Blue Lagoon silica mud mask is the product chose for the pilot

project of carbon footprinting……………………………………………… 8 4. Typical stages in a product’s life cycle………………………………………….. 8 5. Schematic diagram of Blue Lagoon silica mud mask production and

distribution process………………………………………………………… 10 6. High level process map diagram for the life cycle of Blue Lagoon silica

mud mask………………………………………………………………….. 11 7. Common activity data…………………………………………………………… 14 8. The basic formula to calculate the carbon footprint for a given activity………... 16 9. Simplified mass balance sheet for the production of 200 ml Blue Lagoon

silica mud mask……………………………………………………………. 17 10. Sections of the process map for footprint calculation purposes………………. 18 11. High level carbon footprint calculations for the raw silica mud production

process………………………………………………………………………18 12. Carbon footprint calculations for the silica mud mask processing including

production of chemicals other than raw silica mud, production of packaging materials, mixing process and packaging process…………… 20

13. High level carbon footprint calculation for distribution process………………. 20 14. Carbon footprint calculation for use phase of 200 ml Silica Mud Mask

product……………………………………………………………………... 21 15. Carbon footprint calculation for disposal phase of 200 ml Silica Mud Mask

product……………………………………………………………………... 22 16. Share of contributions for carbondioxide emissions in a life cycle of a

200 ml Silica Mud Mask product………………………………………….. 24 17. A conceptual flowchart for the complete “recycling” of CO2 for solar

energy capturing……………………………………………………………. 27 18. Set of equipments for microalgae project by using photobioreactors…………. 29 19. Reservoir tank of the photobioreactors………………………………………… 29 20. Photobioreactors used at Blue Lagoon R&D lab………………………………. 30 21. Diagram of small scale reactor with total volume of 10 liters………………. 31 22. Growth characteristics dependent on pH level………………………………… 32 23. Growth characteristics dependent on temperature…………………………….. 33 24. Growth characteristics dependent on salinity level……………………………. 34 25. Growth characteristics dependent on irradiance level, μE/m2sek……………... 35 26. General setup for CO2 collection process……………………………………… 36 27. Schematic flow chart of geothermal biomitigation experiment by utilizing

blue green microalgae……………………………………………………… 37 28. Laboratory scale bioreactor used in the experiment…………………………… 38 29. Diagram of small scale reactor with total volume 10 liters……………………. 38 30. Diagram of Beer–Lambert absorption of a beam of light as it travels through a

cuvette of width ℓ…………………………………………………………... 39

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31. Correlation between absorbance transmissivity and dry weight of biomass….. 39 32. a) Turbidimeter during the experiment. b) Two solutions with different density

which resulted in different turbidity readings……………………………… 40 33. Absorbance and turbididity correlation for blue green algae………………….. 40 34. Growth comparison curve for Blue Green Algae……………………………... 41 35. Growth comparison curve for Diatom Algae………………………………….. 41 36. Microalgae continuous production process……………………………………. 43 LIST OF TABLES 1. Artificial sea water chemical species……………………………………………. 37 2. Some microalgae strains studied for CO2 bio-mitigation……………………….. 42 3. The calculated CO2 fixation rate for blue-green microalgae……………………. 44

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INTRODUCTION The thesis is divided into two parts. The first part will explore the experience of Blue Lagoon Company in implementing carbon footprint project of its product, while the second part will involve the experimental project of geothermal CO2 bio-mitigation technique by utilizing blue green microalgae. i. Background – the Blue Lagoon Company In late 1976, the Suðurnes Regional Heating Corporation started their first operation of supplying hot water into the nearby municipalities. In the same year, the lagoon was formed as a result of discharging geothermal brine into the surface. The idea was to let the geothermal brine percolate to the ground, in which the current trend would be to inject the brine into the injection wells due to environmental concerns. Not long after, in early 1980s, people started bathing in the lagoon. Since then, the Blue Lagoon has attracted hundreds of thousands of visitors yearly and has become one of most famous Icelandic tourism icons (Figure 1.)

Figure 1. The heart of Blue Lagoon's operation is at the Blue Lagoon, Iceland's most unique and popular attraction [Blue Lagoon Ltd., 2009].

The average temperature of the lagoon’s waters is 34°C, and its average pH is 7.5; the salt content is about 2.5% vol. The biology of this water could support bacterial development; however, there is no trace of bacteria associated with human usage of the lagoon. The composition of the lagoon water itself appears to be disinfecting in content and possess of healing capabilities. The two types of algae present in the silica mud of the lagoon are Leptolyngbya erebi var. thermalis and genus Cyanobacteria. These, in combination with the microorganism Roseobacter, occur in numbers that depend little on outside conditions. The unique, healing qualities of the combinations of organisms, algae,

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and geothermal conditions of the water continue to be studied for direct influence on immune system healing and joint mobility [Blue Lagoon Ltd., 2009]. The Blue Lagoon Company has made a distinctive concept of products and services either based on Blue Lagoon geothermal seawater’s active ingredients (minerals, silica and algae) or the close proximity to the seawater and its raw natural surroundings. In view of current global issues about climate change, the company has also set targets to reduce the greenhouse gas emissions and developed year-on-year milestones to achieve those targets. The Blue Lagoon is looking to be a company that looks at all its operations, including offices, factories, process plants, logistics and freights, packaging, business travel and etc. In other words, Blue Lagoon deliberately chooses to be climate neutral in its operations, without losing sight of the commercial aspects of business. As a start, Blue Lagoon Company is initiating a carbon footprint project for its products and services. As a pilot project, the company chooses one product for carbon accounting project, and then goes further with the remaining products and services in future. Moreover, the company has also started a carbon reduction project by utilizing the microalgae which naturally thrives within the Blue Lagoon area. ii. Product carbon footprinting Literally, carbon footprinting is the calculation of total set of greenhouse gas emissions caused by an individual or organization, event or product. It should be expressed in carbon dioxide equivalent [Carbon Trust, 2007]. Product carbon footprinting offers a unique view of green house gases (GHG) emission, taking a single product from raw materials through manufacturing, distribution, use and disposal/recycling, and calculating the emissions created as a result of all related activities and materials. It can also be applied to the delivery of a service. This view is critical for two reasons. First, in many developed countries, GHG emissions arising from consumption of goods and services is greater than the emissions actually produced in the country – thus these countries fall under ‘net importer’ of GHG emissions, and this trend is increasing. To ensure global reduction targets are met, it is critical to understand the full picture of carbon emissions driven by consumption, regardless of where the emissions occur. Second, consumers recognize their role in contributing to climate change and are beginning to demand more information on the impact their purchasing decisions and behaviors have on emissions. A consumption-based view of emissions helps us understand not just what the emissions are across the economy, but why they exist. Product carbon footprint provides the information these consumers need to make more informed choices. It also acts as the starting point for business looking to reduce the emissions associated with their products and unlock resulting cost savings, as well as providing a basis for developing future low-carbon products.

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However, no single, consistent method for calculating product carbon footprints has existed until recently [Carbon Trust, 2007]. Measurement and communication standards In late 2008, the Carbon Trust association launched Publicly Available Specification (PAS 2050) which was the first standard method for calculating life cycle of GHG emission(s) of products. The Carbon Trust association has also created a Code of Good Practice to standardize communications and reduction claims and the Carbon Reduction Label™ to provide a trustworthy way for companies to inform their product footprint publicly. PAS 2050 establishes a standard approach to calculate life cycle GHG emissions which was developed by BSI British Standards and co-sponsored by the Carbon Trust and UK Department for Environment, Food and Rural Affairs. PAS 2050 was partly made to address many of the complex issues driven by the integration of product life cycle assessment and GHG emissions accounting. However, some of the issues were difficult to address, such as recycling and allocation, but the carbon footprint experts managed to handle these uneasy issues in the PAS 2050 consistently. In addition, the Carbon Trust association has developed the Carbon Reduction Label™ in order to provide companies who comply with these standards as ways of credibly communicating their product carbon footprints. The Carbon Reduction Label™ can also be used across a range of different channels including website, CSR report, brochures, point of sale and on the product itself. The Carbon Reduction Label™ also states the company’s commitment to reduce product emissions over time, and it can include an explanation of the footprint, a comparison to footprints of alterative products in the similar category and additional tips for consumers on how they can reduce the product’s emissions by changing the way they use it. Value for business It is unquestionable that many companies have already begun to see the real benefits by carbon footprint assessment. The main true driver of product carbon footprinting is to identify the GHG emissions, often revealing some unpredictable outcomes. It therefore enables better targeted, more effective emissions reduction and cost savings initiatives, which may or may not fall under the company’s direct control. In fact, several companies who have already used the draft PAS 2050 method have already reduced product-level GHG emissions by up to 20%. Considerable cost savings have also been achieved due to energy and waste efficiency measures across the supply chain [Carbon Trust, 2007]. In many cases, carbon footprinting in products also helps companies strengthen the relationships with suppliers, particularly if it reveals cost savings opportunities up the supply chain.

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In addition, implementing product carbon footprints could also improve company’s general business or management practices in unforeseen ways, such as developing interactive tools to improve sourcing decisions. Other benefits of communicating product carbon footprints Many companies who decide to communicate their product carbon footprints have realized some other added benefits, which include more carbon- and cost savings, product differentiation and general brand enhancement. Product carbon labeling can boost emissions reduction efforts in a couple of ways. First, the public commitment to reduce emissions over time helps create a sense of urgency across the supply chain, creating momentum to follow through with emissions reduction measures. Second, by putting credible information in the hands of consumers, companies who label help consumers reduce their own impact on climate change. Equipped with information on alternative product footprints and how their behaviors during the use phase affect product emissions, consumers are empowered to reduce emissions themselves. Implementing the carbon reduction label also helps companies differentiate their products based on their commitment to reduce emissions and general willingness to pioneer credible carbon labeling. Based on many public surveys [Carbon Trust, 2007], consumers are beginning to demand ‘low carbon’ products and the information they need to make informed choices. Opportunities for companies to lead or to be left behind It is estimated that product carbon footprinting, reductions and communications will offer significant opportunities for companies. Product carbon footprinting is a fast growing industry of its own, with opportunities for companies who act now to seize an advantage. Some of the trends that are expected to accelerate over the next few years, internationalization of the standards and communications/labeling of products, growth of support services to speed and ease implementation and increasing consumer demand for product carbon information and lower carbon products. Based on the results from the 20 leading companies that have used the standards for carbon footprinting, a fast growing product carbon footprinting ‘industry’ will translate into substantial reductions in GHG emissions, and associated cost savings, no matter where the emissions are generated [Carbon Trust, 2007]. Consumers and businesses are better informed and they will be able to make more informed choices in regard to the products they buy, and how they use and dispose them, further contributing to global emissions reductions and creating opportunities for companies to differentiate their products and brands. Understanding emissions at a product level is, therefore, key to addressing the global problem of climate change and for companies to capture the associated business opportunity this transition offers.

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iii. Carbon sequestration There are several methods of CO2 mitigation which have been studied; they are generally classified under two categories: (1) chemical reaction-based approaches and (2) biological CO2 mitigation. The first method is popularly achieved by cyclic carbonation/de-carbonation reactions in which carbon dioxide gasses will react with solid metal oxide (MO) to achieve metal carbonate. The chemical reaction can be expressed in Equation 1 as follow:

(Eq. 1) In the event of metal oxide reaches its ultimate conversion, metal carbonate can be thermally restored to metal oxide and CO2 by heating the metal carbonate above its calcination temperature. The calcination reaction itself can be expressed as the reverse of Eq. 1 as follow:

(Eq. 2) In reality, the calcinations reaction process in a fossil fuel fired utility would require a carbonation reactor and a regeneration reactor. Lime (calcium containing compound) is the primary component of this chemical reaction-based CO2 mitigation, and probably it is the most popular solid adsorbent due to its reasonably low cost. The CO2 fixation process by chemical reaction-based is commonly consisting of three procedures: separation, transportation and sequestration. In average, the cost of carbon dioxide separation and compression to 110 bars for transportation is estimated to be $30-50 per ton of CO2, and transportation and sequestration are estimated to cost about $1-2 per ton per 100 km and $1-3 per ton of CO2, respectively [Gupta and Fan, 2002] [Shi and Shen, 2003]. Thus, it can be prematurely concluded that this method of fixing the CO2 is relatively expensive and energy consuming, thus the mitigation benefits become marginal. For that reason, it is necessary to come up with a cost effective and sustainable strategy to control the expanding emission. On the other side, another method of carbon fixation is through biological CO2 mitigation. Biological CO2 mitigation has attracted much attention as an alternative strategy mainly due to its production of biomass as the byproduct during the photosynthesis process. This biological CO2 mitigation can be done by plants and other photosynthetic microorganisms. Nevertheless, the potential for increased CO2 capture in agriculture by plants has been estimated to contribute only 3–6% of fossil fuel emissions. This low value is largely due to the slow growth rates of conventional terrestrial plants [Wang et. al., 2008]. In this project, microalgae are used to observe the feasibility of fixing the carbon gasses from the nearby geothermal power plant. Microalgae have the capability to fix carbon dioxide while capturing solar energy with efficiency up to 50 times greater than that of agricultural plants, with the same coverage area. [Wang et. al., 2008].

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PART I 1. CARBON FOOTPRINT ANALYSIS AND ITS APPLICATIONS Managing the carbon footprint of products across the supply chain is the next step for business to take in the effort to reduce carbon emissions and mitigate climate change. There are several issues driving business to take action, including:

Increases in direct energy costs and the energy costs of suppliers Existing and planned legislation which penalizes high energy consumption and

rewards emissions reductions Changing consumer attitudes to climate change, presenting forward-thinking

companies with an opportunity to develop and market low-carbon products.

As we move to a more carbon-constrained world, business will ultimately have to meet customer needs in a way that generates fewer carbon emissions. Business energy efficiency and low-carbon energy supply have played, and will continue to play, an important role but more fundamental solutions are also needed. Managing the carbon footprint of products across the supply chain is just such a solution. 1.1 The assessment approach Traditional energy efficiency and carbon management initiatives analyze the operations of single companies or even single sites. The supply chain approach extends this analysis to cover specific processes from multiple sites and multiple companies operating in a single supply chain. This allows the full carbon footprint for each product to be created. In this particular project, a relatively new and reliable assessment method is used which is called PAS 2050. This Publicly Available Specification (PAS) has been prepared by the British Standards Institution (BSI) to specify requirements for assessing the life cycle greenhouse gas emissions of goods and services. The development of this PAS was co-sponsored by the Carbon Trust association and the Department for Environment, Food and Rural Affairs (Defra). 1.1.1 PAS 2050 PAS 2050 is based on process Life Cycle Assessment (LCA), an approach which is commonly used in supply chain analysis to identify opportunities to reduce waste and increase efficiencies across an entire product system. PAS 2050 was made to meet the demand for a supply chain oriented approach to carbon accounting by providing a robust and consistent method for product GHG assessment. Furthermore, it is a set of specifications for the assessment of the life cycle greenhouse gas emissions of goods and services, which then allow companies or organizations within the supply chain and the users of goods and services to better understand the carbon implications of their actions. The set of specification was built extensively on existing

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standards and approaches, especially in relation to established life cycle assessment standards; however it provides greater certainty around the requirements for product specific GHG emissions assessment. The product carbon footprinting method described in PAS 2050 is based on the five main steps listed in Figure 2 below. 1.1.2 “Use phase” emissions Evaluating the emissions occurring from the use phase of a product is significant, particularly for products requiring energy during use such as light bulbs, personal computer, shampoo or even refrigerated juice. However, it is also challenging, as there is no real certainty over how many products will be used and little chance that every product will be used in the same way for each user. On the other hand, excluding the use phase emissions could lead to perverse outcomes. For instance, Apple® Computer Company has just recently reported their life cycle analysis of their product lines, and reported that more than half of greenhouse gas emissions Apple® accounts for are produced when the consumer plug in the products and start using them. Figure 2. Five steps in calculating product carbon footprint. For this reason, PAS 2050 requires use phase emissions to be included in the product carbon footprint. The assessment specified is to establish a ‘use profile’ which describes the assumptions used to quantify use phase emissions. The use phase profile must be made public if the company chooses to communicate its product carbon footprint. 1.2 Product(s) analyzed As this carbon footprinting project is relatively new to Blue Lagoon as a company, thus as a start, a rather simple yet representative product was chosen to be the pioneer. The chosen product is Blue Lagoon 200 ml Silica Mud Mask (Figure 3) which is one of the best known products of the Blue Lagoon company. The Silica Mud Mask contains 93% vol. of its ingredients from Blue Lagoon’s silica mud, thus it will be easy to gather the data for carbon calculation purposes.

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Figure 3. The 200 ml Blue Lagoon silica mud mask is the product chose for the pilot project of carbon footprinting [Blue Lagoon Ltd., 2009].

1.3 The detailed methodology PAS 2050 utilizes a process life cycle assessment approach to calculate the GHG emissions associated with goods or services, allowing the companies to identify ways to minimize emissions across the entire product system. As previously mentioned, there are five basic steps in calculating the carbon footprint of any good or service:

1. Building a process map (flow chart) 2. Checking boundaries and prioritization 3. Collecting data 4. Calculating the footprint 5. Checking uncertainty (optional)

1.3.1 Step 1: Building a process map Having a full understanding of the process flows behind the life cycle of a product is an essential initial step in assessing product GHG emissions. For some products, the supply chain may be very straightforward, however in some other products; mapping exercise may reveal previously unrecognized complexity. In general, there are five stages in product’s life cycle as shown in Figure 4 below.

Figure 4. Typical stages in a product’s life cycle. In the case for 200 ml Blue Lagoon silica mud mask, it is recommended to break down the process map into several criteria as follows:

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1. Define the functional unit – the appropriate functional unit is driven by how the product is typically consumed. The functional unit for Blue Lagoon silica mud mask is 200 ml, as the normal size for one pack of the product.

2. List the ingredients and proportions Sea Water/Maris Aqua (Blue Lagoon Geothermal Seawater) – 73.72% vol. Silica, Silt (Blue Lagoon Geothermal Silica Mud) – 19.5% vol. Ethoxydiglycol Oleate – 2.5% vol. Cetearyl Isononanoate – 2.5% vol. Polyacrylamide – 0.45% vol. C13-14 Isoparaffin – 0.25% vol. Laureth-7 – 0.08% vol. Phenoxyethanol – 0.72% vol. Methylparaben – 0.16% vol. Ethylparaben – 0.04% vol. Propylparaben – 0.02% vol. Butylparaben – 0.04% vol. Isobutylparaben – 0.02% vol.

3. List the activities involved in producing and consuming Blue Lagoon silica mud mask Produce and transport raw materials

o Collect geothermal brine and process to silica mud paste o Collect geothermal brine and process to saline water o Produce other chemicals as the additives for preservation o Produce packaging materials

Mix (process) ingredients and transfer to container for packaging Distribute finished product Retail Use Dispose of waste

4. Reflect on what might have been missed Have all raw materials been traced back to their origin, including intermediate

processes? o The main raw materials of this product (Blue Lagoon geothermal

seawater and silica mud) are basically a waste of geothermal power plant which produces electricity and heat to the community. Therefore, carbon emission is only accounted in the electricity and hot water usage of the process (using geothermal power) while the silica mud production is accounted as zero emission. The data for the remaining materials, which is the additives for the product, are collected from secondary data.

Were any by-products created during manufacturing? o There is a limitation of access for any by-products produced in the

mixing and packaging process. It is assumed to have no by-products until further information is gathered.

Have all waste streams and emissions been accounted for?

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o Waste stream in the Blue Lagoon and consumer-use phase is taken into account, while waste from the mixing and packaging process is handled by a supplier which provided Blue Lagoon with carbon emission data. Therefore, it is assumed that emissions from the supplier have been taken into account.

Has the transport of waste been accounted for? o Transport of average trip to the landfill has been accounted into the

calculation. Have multiple distribution stages been accounted for, including all transport

links and storage conditions? o The product is being sold in many countries; therefore, the distance of

transportation used for the calculation is based on weighted-average of number of sales in each country.

Was energy consumed during the consumer use phase? o The energy consumed is by utilizing heated water to wash/rinse the

skin. The amount of heat used is based on experiments and interviews. Once a full picture of the steps in the product’s life cycle has been built (Figure 5 below), the next step is to confirm boundaries and prioritization. 1.3.2 Step 2: Checking boundaries and prioritization

Figure 5. Schematic diagram of Blue Lagoon silica mud mask production and distribution process.

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The system boundaries simply defines the scope for the product carbon footprint, for which life cycle stages, inputs and outputs should be included in the assessment. The first task is to build a high-level process map to determine the relevant boundaries for carbon footprint analysis (Figure 6). The map is divided into five categories as follow:

Raw Materials: All inputs used at any stage in the life cycle. This category includes all the process related to raw materials which in this case include the mining/extraction of the geothermal water from the power plant, the production of other chemical ingredients, production of packaging raw materials and also all the transportation related in the process.

Manufacture: All activities from collection of raw materials to distribution. In the case of Blue Lagoon silica mud mask process; this category will include the mixing process of all the ingredients into a final product, the packaging process and also its transportation needs.

Distribution/Retail: All steps in transport and relate storage. Additionally, this will also include all the retail storage and display process.

Use: Any energy required during use phase, which in this case includes the use of heated water to consume the product.

Disposal: All steps which relates to disposal transport, storage and processing.

Figure 6. High level process map diagram for the life cycle of Blue Lagoon silica mud mask. The key principle for system boundaries is to include all “material” emissions generated as a direct or indirect result of the product being produced, used and disposed of or

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recycled. A material contribution is a contribution from any one source resulting in more than 1% of the total anticipated life cycle emissions of the product. The PAS 2050 allows immaterial emissions to be excluded with any single source resulting in less than 1% of total emissions. However, the total proportion of immaterial emission sources cannot exceed 5% of the full product carbon footprint [Carbon Trust, 2007]. In this step, some activities are not included into the carbon footprint calculation such as:

Human inputs to processes Transport of consumers to retail outlets

To decide whether an emission source should be included in the calculation (i.e. single source resulting in more than 1% of the total anticipated life cycle emissions of the product), it helps at this point to do a high-level footprint analysis using estimates and readily accessible data. This analysis includes the full life cycle of the product but relies on estimates and generic data to build a high-level footprint. Significant sources of emissions can then be replaced by more specific and better quality data. As a preliminary calculation, a generic web-based carbon footprint calculator published academic work or other LCA studies with similar product can be used as an initial rough calculation to determine the most contributing factor to the footprint analysis. For the silica mud mask product, it has been determined from a carbon footprint web-based calculator that transportation for distribution and mixing of all the ingredients are the two most contributing factor for the analysis, thus these two factors has the highest priority compared to other activities in the process. A range of data may be available for each material, but the data should be sufficient to allow for prioritization of further data collection. Armed with a better sense of where – and where not to focus, the next step is to collect more detailed data specific to the product being foot printed. For a high level analysis it may be sufficient to stop here and use this carbon footprint figure to identify emissions ‘hot spots’; however, this would not be rigorous enough to achieve full compliance with and certification against PAS 2050, for external claims or for most product or process comparisons. 1.3.3 Step 3: Data Collection The data collection step is commonly guided by the high-level process map shown in previous section. While collecting the data, it is advised to keep it under the requirements and recommendations of PAS 2050, which then will enable assessment of the carbon footprint in more detail. All data used in the carbon footprint assessment must meet the PAS 2050 data quality rules. This assures accurate, reproducible and more readily comparable carbon footprints.

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Good quality data helps to build a footprint that represents a ‘typical’ product’s life cycle over a defined time period, recognizing variations in geography, distance and materials. The compliance of data quality to PAS 2050 should be judged according to the rules described in the specification. Below is the list of some main rules with its corresponding to the silica mud mask project:

How specific is it to the declared reporting period? o The collected data is based on the activities which has been an on-going

process with no major change for the last few years. How specific is it to the product’s relevant geography?

o All data collected are based on the local geography of the activity, such as, electricity in Denmark and in Iceland, for production processes.

How specific is it to the product’s relevant technologies and processes? o In the production of the raw materials, there is no high-tech equipment in

use. Meanwhile, the mixing process of all the ingredients uses somewhat higher high-tech equipment to ensure the quality of the final product.

How accurate is the information used (e.g. data, models and assumptions)? o Most of the measurements are taken from the exact figure, such as the

electricity usage, while the transportation activities are mostly average data due to fluctuation in product’s demand.

How precise is the information? i.e. measure the variability of the data values. o As previously mentioned, all the activities related to electricity usage are

taken directly from the meter, while the total transportation is taken from the averaged and rounded values.

How complete is it? i.e. is the sample size sufficiently large and representative of all potential sub-categories of the product?

o Nearly all the activities are consistent throughout for the last few years. Therefore, most of the data is taken at a given time only, which is a good representation for the repetitive activity.

What percentage of the data used was actually measured vs. taken from a general database?

o A small portion of transportation vehicle is taken from the database for its fuel consumption rate, in addition to landfill carbon release, while rest of the data is taken from actual measurement. Only about 15% of all the data is taken from carbon emission database.

How consistent is it? o As stated previously, nearly all the activities in the production of silica

mud mask is consistent for the last few years. Therefore it is assumed that the activities will remain constant for the next few years as well.

What sources are used? o Data collection was partially contributed by Blue Lagoon’s suppliers such

as in the transportation and distribution, and also the mixing and packaging company.

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Data types Generally, there are two types of data that are necessary to calculate a carbon footprint: activity data and emission factors. Activity data refers to all the material and energy amounts involved in the product’s life cycle (material inputs and outputs, energy used, transport, etc.), while emission factors provide the link that converts these quantities into the resulting GHG emissions: the amount of greenhouse gases emitted per ‘unit’ of activity data (e.g. kg GHGs per kg input or per kWh energy used). Activity data (Figure 7) and emissions factors can come from either primary or secondary sources:

Primary data refers to direct measurements made internally or by someone else in the supply chain about the specific product’s life cycle

Secondary data refers to external measurements that are not specific to the product, but rather represent an average or general measurement of similar processes or materials (e.g. industry reports or aggregated data from a trade association)

Figure 7. Common activity data. Primary activity data PAS 2050 requires that primary activity data be used for all processes and materials owned, operated or controlled by the footprinting organization. For retailers or other organizations that do not contribute a significant amount to the product’s emissions, primary activity data is required for the processes and materials controlled by the first (closest) upstream supplier. These data should be relatively easy to measure, and are

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necessary to ensure the carbon footprint result is specific to the chosen product. Primary activity data is not required for downstream sources of GHG emissions (e.g. consumer use, disposal). Primary activity data should be representative, reflecting the conditions normally encountered by the product being assessed. Primary activity data can be collected across the supply chain either by an internal team or by a third party (e.g. consultants). In practice, it helps to speak to at least one person in each part of the supply chain to ensure the process map is correct and that sufficient data is collected. The data may already exist within the organization, or it may require new analysis. In some cases, gathering primary activity data may require installing new ways to collect data, such as measurement meters and sub-meters. Secondary data Where primary activity data is not available, or is of questionable quality (e.g. when appropriate measurement meters are not available), it is necessary to use secondary data derived from sources other than direct measurement. In some cases, secondary data may be preferable to enable consistency and, where possible, comparability:

Global warming potential of greenhouse gases Electricity emissions (in kg CO2e per kWh) from various energy sources Fertilizer/pesticide emissions per kg Fuel emissions per liter Transport emissions per km per vehicle type Waste emissions per kg Agriculture emissions from livestock and/or soils

Consumer use emissions Data describing how consumers use product (the ’use profile’) can be particularly difficult to find. The use phase describes the activities and energy consumed when the product is used by the end consumer. This includes energy associated with storage (e.g. refrigeration, electricity use and etc.) In the case of Blue Lagoon silica mud mask, the use phase includes the usage of heated water to wash the product from consumer’s face skin. The amount of heat required to consume one unit of product is estimated by actual experiments. Records PAS 2050 requires that detailed records of all data sources and any assumptions that are used to carry out the emissions assessment has to be kept. To communicate the footprint

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externally, details of boundaries, use profile and all data sources should be disclosed to ease transparency. Armed with sufficient data, now it is time to put it all together and calculate the carbon footprint of the product. 1.3.4 Step 4: Calculating the footprint The equation for product carbon footprinting is the sum of all materials, energy and waste across all activities in a product’s life cycle multiplied by their emission factors (Figure 8). The calculation itself simply involves multiplying the activity data by the appropriate emission factors.

Figure 8. The basic formula to calculate the carbon footprint for a given activity. Calculating the carbon footprint normally requires a ‘mass balance’ to ensure all input, output and waste streams are accounted for. Mass balance The quantification of the total amount of all materials into and out of a process is referred to as ‘mass balance’. The mass balance step provides confirmation that all materials have been fully accounted for and no streams are missing. The fundamental concept is that total amount flowing into a process should equal total amount flowing out. In practice, it is a useful way to identify previously hidden waste streams: if the mass coming out of a process is less than the combined mass of the inputs, then some other stream – most likely waste – must be leaving the process too. Note that for some complex natural systems, like agriculture, mass balance may not be practical or relevant. It is easiest to calculate mass balances while the data is being collected. First work backwards from the point of purchase: all materials, energy and direct emissions to produce a unit should be included, and all the mass accounted for. Then use a similar process to ensure the full mass of the product is captured in the use and disposal phases. As depicted in Figure 9 below, the mass (volume) balance for 200 ml Blue Lagoon Silica Mud Mask is consisting of 93% vol. Blue Lagoon’s silica mud and salt, while the remaining are chemical additives for fragrances and preservatives. The process itself does not involve any waste by-product; therefore it is a relatively simple mass balance process.

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Footprint calculation The actual calculation involves multiple steps. For reference, each step is numbered in the process map as shown in Figure 10 below and corresponds to a discrete part of the detailed calculation diagram followed after.

Figure 9. A simplified mass balance sheet for the production of 200 ml Blue Lagoon silica mud mask. The calculation is mainly divided into five major sections of the process map. The first section covers the area of raw silica mud production at the Blue Lagoon production facility. Next section involves all the related processes in the production of the remaining ingredients, mixing of all the ingredients and packaging to a final product. The third process is simply all the transportation and distribution related processes. Fourth section includes the usage phase while the last section covers the disposal phase of the product.

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Figure 10. Sections of the process map for footprint calculation purposes. The carbon emission calculation for the first section mainly involves the production of raw silica mud from the nearby geothermal power plant. The process started in the precipitation tanks where the effluent geothermal water is being precipitated to separate the salt water and the precipitated silica in the bottom of the tanks. The precipitated silica is then being transferred to a filter press process where it further reduces the amount of water/liquid in the silica to form a mud/paste. The silica mud is the mixed with water to achieve the level of density required. All these processes involved the usage of electricity for the pumps and the use of other heavy equipment such as electric forklift. Thus, the carbon emissions is calculated based on the total usage of electricity in a given time and amount of raw silica mud being produced, as shown in Figure 11 below. The production of product’s additives and preservatives is not included in this section.

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Figure 11. High level carbon footprint calculations for the raw silica mud production process. Section two covers all the process in the production of other chemical (additives and preservatives) ingredients, mixing and packaging of the product. Similar to the first section, the main contribution of carbon emission in this section is from the usage of electricity and diesel fuel for all the operations involved. Other emissions are related to the production of product’s packaging such as the plastic container and paper for the service packaging. Simplified calculations are shown in Figure 12 below. The third section is limited to the transportation, distribution and storage of the product. Any GHG emissions arising from any transport required during the products – and its raw materials’ – life cycle are included in the carbon footprint assessment. Emission factors for transport should include emissions associated with creating and transporting the fuels required. When products are distributed to different locations and transport distances vary, then the average GHG emissions calculations should be based on the average distribution distance of the product within each country over the chosen time period (unless more specific data is available). As expected, the main carbon contributor arises from emission of vehicles such as the trucks and ships for transporting the product between countries. All the distances and vehicle types are included in the calculation for carbon emissions. Nevertheless, the problem arises because the product is being sold in many countries. The solution, based on PAS 2050, is by having a weighted average for total amounts of products being sold in different countries, and later uses the percentage to calculate the total average distance. Figure 13 below shown the simplified calculation for transportation related emissions.

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Figure 12. Carbon footprint calculations for the silica mud mask processing including production of chemicals other than raw silica mud, production of packaging materials, mixing process and packaging process.

Figure 13. High level carbon footprint calculation for distribution process.

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Figure 14. Carbon footprint calculation for use phase of 200 ml Silica Mud Mask product. Section four is where the usage of the product is being analyzed for its carbon emissions. As general instruction, the usage of Blue Lagoon’s silica mud mask is by applying the product to the skin face, and then rinses it with warm water. Thus, the only emission related to the use phase of Silica Mud Mask is the carbon emitted to generate heat needed to heat the water. As seen in the Figure 14 above, the 200 ml Silica Mud Mask will use, in average, 400 liters of 30°C water. Waste generates emissions when it breaks down in landfills or is incinerated. The PAS 2050 method treats these emissions differently depending on the material and process of disposal, which in this case is by landfill. Some criteria for waste emission calculation are: CO2 emissions from plant-based carbon in the waste are excluded, i.e. given a GWP of 0; CO2 emissions from fossil carbon are included in the product footprint with a GWP of 1. All non-CO2 emissions from any part of the waste are included and assigned the relevant GWP. As shown in Figure 15 below, the last section includes the carbon emissions for the disposal of the product which involves the plastic and paper materials in the 200 ml Silica Mud Mask product. The emission factors are as listed in the PAS 2050 guide.

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Figure 15. Carbon footprint calculation for disposal phase of 200 ml Silica Mud Mask product. 1.3.5 Step 5: Checking uncertainty Uncertainty analysis in product carbon footprinting is a measure of precision. While not prescribed in PAS 2050, companies can benefit from assessing the uncertainty of their carbon footprint as described below. The objective of this step is to measure and minimize uncertainty in the footprint result and to improve confidence in footprint comparisons and any decisions that are made based on the footprint. Uncertainty analysis provides several benefits:

-enables greater confidence in comparisons between products and in decision making -identifies where to focus data collection efforts, and where not to focus -contributes to better understanding of the footprinting model itself – how it works,

how to improve it and when it is robust enough - indicates robustness of the footprint to internal and external audiences.

Best practice in product carbon footprinting, as encouraged by PAS 2050, aims to minimize the uncertainty in the footprint calculation to help provide the most robust, reliable and replicable result. PAS 2050 does not explicitly require uncertainty analysis, although it may be necessary to meet data quality specifications. In practice, it is useful to delegate this task to someone experienced in uncertainty analysis and familiar with the product’s carbon footprint model.

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Reducing uncertainty Once sources of uncertainty have been identified through the process, they can usually be reduced in the following ways:

Replace secondary data with good quality primary activity data, e.g. replace an estimated electricity consumption factor with actual measurements from a line sub-meter

Use better quality secondary data i.e. more specific, more recent, more reliable and/or more complete

Improve the model used to calculate the carbon footprint by making it more representative of reality e.g. estimate each distribution leg individually, rather than a single estimate for total distribution

Additional peer review and/or certification of the carbon footprint 1.4 Summary of Part I Having calculated the emissions for each step, the net amount represents the total GHG emissions caused by each material and process across the product’s life cycle, and therefore the final product carbon footprint – in this case, 137.73 grams-CO2e per box of 200 ml Blue Lagoon Silica Mud Mask. It is too soon to determine whether this product emits more or less than other similar products, since market research need to be conducted prior to answering the question. However, the results indicate that the largest portion of carbon emissions is coming from the processing phase, which is 62.72% of total carbon emission. This portion includes the process of production of non Blue Lagoon ingredients, mixing of all ingredients and packaging of the product. The main contributor is attributed to the production of electricity and diesel fuel consumed in the process mentioned above. A large contribution is due to energy portfolio in Denmark (where the processing company is located) where more than 50% of its electricity generation is sourced from coal based power plants. The figure of carbon emission would have been one tenth of what it is now if the processing plant would have been located in Iceland where all of the electricity generation is based on geothermal and hydropower.

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0

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3.35%

1.04%

62.72%

32.70%

0.19%

Total CO2e emission = 137.73 gr

Figure 16. Share of contributions for carbondioxide emissions in a life cycle of a 200 ml Silica Mud Mask product. Exclusions The following emission sources are excluded from the PAS 2050 life cycle GHG emission assessment.

1. Capital goods These emissions are excluded based on: lack of carbon footprint data currently available to identify sectors where

capital goods emissions are material and cost/complexity of analysis

2. Aircraft emissions uplift factor (factor in multiplying the CO2 emissions by a factor of up to 3.7 to take into account other effects. These include nitrogen oxides, methane, contrails and possible increases in cirrus cloud formation) This is excluded due to considerable uncertainty on the relative size of the impact of non-CO2 emissions from aviation through radiative forcing

3. Offsets These are excluded because PAS 2050 is an assessment of a specific product’s life cycle GHG emissions; any reductions to the footprint should be directly attributable to changes made to the product’s life cycle, not through unrelated activities such as purchase of emissions credits.

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Challenges During the process of carbon footprinting for Blue Lagoon’s product, there are some rather generic challenges that can be highlighted as follows:

Data confidentiality is a key consideration for all companies/suppliers as costs and other commercial information may be needed to perform the calculations. Some companies/suppliers were rather hesitant to provide detailed information. Although for this Silica Mud Mask calculation some cost data were needed, but all suppliers were able to support the project.

The results are not necessarily applicable to the industry as a whole. The studies analyze specific product supply chains with specific companies and processes involved. Because the analyses are specific, it is not possible to make sector-wide recommendations from the results.

The opportunities are typically more fundamental than simple energy efficiency changes and so are likely to be harder to implement.

Potential emissions reduction As mentioned in the beginning of this report, the Blue Lagoon Company has set realistic targets to neutralize its greenhouse gas emissions and developed year-on-year milestones to achieve those targets. The Blue Lagoon is looking to be a company that looks at all its operations, including offices, factories, process plants, logistics and freights, packaging, business travel and etc. In other words, Blue Lagoon deliberately chooses to be climate neutral in its operations, without losing sight of the commercial aspects of business. Referring to the results of carbon footprinting process above, Blue Lagoon Company is currently developing a carbon reduction project by utilizing microalgae which are naturally grown within the area to reduce the emissions emitted from electricity utilization of raw silica mud production. Although the raw silica mud production process only emit 3.35% (Figure 16) of total Silica Mud carbon emission, this microalgae carbon reduction project could later also reduce the emissions generated from the electricity and heat used at the Blue Lagoon facilities. In the end, the company itself aims to be a carbon-neutral company.

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PART II 2. CARBON EMISSION REDUCTION by means of microalgae cultivation There is a growing scientific consensus that rising concentrations of carbon dioxide (CO2) and other greenhouse gases are gradually warming the Earth’s climate. The amount of damage associated with that warming remains uncertain, but there is some risk that it could be large and perhaps even catastrophic. Reducing that risk would require restraining the growth of CO2 emissions — and ultimately limiting those emissions to a level that would stabilize atmospheric concentrations — which would involve costs that are also uncertain but could be substantial. 2.1 Carbon fixation process As previously mentioned, there are several methods of CO2 mitigation which have been studied; they are generally classified under two categories: (1) chemical reaction-based approaches and (2) biological CO2 mitigation. Biological CO2 mitigation itself has attracted much attention as an alternative strategy mainly due to its production of biomass as the byproduct during the photosynthesis process. This biological CO2 mitigation can be done by plants and other photosynthetic microorganisms. Nevertheless, the potential for increased CO2 capture in agriculture by plants has been estimated to contribute only 3–6% of fossil fuel emissions. This low value is largely because of the slow growth rates of conventional terrestrial plants. In this project, microalgae are used to observe the feasibility of fixing the carbon gasses from the nearby geothermal power plant. Microalgae have the capability to fix carbon dioxide while capturing solar energy with efficiency up to 50 times greater than that of agricultural plants, with the same coverage/growing area. [Wang et. al., 2008]. 2.2 Microalgae Microalgae are a unicellular species which exist individually in nature or in chains or groups. Different species has different size which can range from just a few micrometers to a few hundreds of micrometers. Compared with higher plants, microalgae do not have roots, stems and leaves. Just like other plants, microalgae are capable to perform photosynthesis process. This process by microalgae is important for life on earth as they produce approximately half of the atmospheric oxygen and use simultaneously the greenhouse gas carbon dioxide to grow photoautotrophically [Benemann, 1997]. Microalgae have enormous biodiversity with approximately 200,000 – 800,000 species exist, of which about 35,000 species are described. Over 15,000 novel compounds originating from algae biomass have been chemically described. Most of these microalgae species produce unique products like carotenoids, antioxidants, fatty acids, enzymes, polymers, peptides, toxins and sterols. The chemical composition of microalgae is not intrinsic constant factor but varies over a wide range, depending on species and on cultivation conditions. It is possible to accumulate the desired products in microalgae to a

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large degree by changing environmental factors like temperature, illumination, pH, CO2 amount, salinity and nutrients. In view of CO2 mitigation by microalgae, the strategy offers numerous advantages. First, microalgae have much higher growth rates and CO2 fixation abilities as compared to conventional forestry, agricultural and aquatic plants. Second, it has the potential to completely recycle carbon dioxide because carbon is converted to chemical energy through photosynthesis process, which can be converted to fuels using existing technologies, such as transesterification process [Wang et. al., 2008].

Figure 17. A conceptual flowchart for the complete “recycling” of CO2 for solar energy capturing. The chemical reaction-based carbon mitigation strategy, as discussed previously, has disposal problems because both the captured CO2 and the wasted absorbents need to be disposed of. Third advantage is that CO2 biomitigation using microalgae could be made profitable from the production of biofuels and other novel bioproducts, as compared to the chemical reaction-based strategy which is considered energy consuming and costly process, and the only economical incentive is by claiming CO2 credits to be generated under the Kyoto Protocol [Boom, 2001]. Lastly, the biological carbon mitigation by utilizing microalgae could be further made economical and environmentally sustainable, by combining it with other processes such as wastewater treatment. Combining this carbon bio-mitigation process with wastewater treatment will result in significant advantages: (1) microalgae have been shown to be effective in removing nitrogen and phosphorus removal, as well as in metal ion depletion, and combination of microalgae with wastewater treatment will significantly enhance the environmental benefit of this strategy, and (2) it will lead to savings in the consumption of nutrients for microalgae growing process and (3) it will definitely resulted in savings of the precious freshwater resources.

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2.3 Growth method In general, the production cost of microalgae biomass (and thus microalgae growing) is higher than the cost of growing crops. Photosynthetic growth need light, carbon dioxide, water and inorganic salts and the ideal growth temperature is between 20 to 30 °C. For large scale production of microalgae biomass, it generally uses continuous culture during daylight. In this particular method, the amount of microalgae “soup” being withdrawn is the same quantity as the fresh culture being fed. In most cases, the feeding step is stopped during the night, but the mixing of “soup” must continue to prevent settling of the biomass. In general, around 25% of the biomass produced during the daylight may be lost during the night because of respiration. The loss amount mainly depends on the light level under which the microalgae were grown, the temperature during the day and the temperature at night. Nowadays, there are generally two methods of large-scale microalgae production; raceway ponds and tubular photobioreactors. The Blue Lagoon CO2 bio-mitigation project is currently utilizing the tubular photobioreactors method with artificial illumination to replace the sunlight. 2.3.1 Raceway ponds The first microalga’ growing medium is raceway pond, which is made of a closed loop recirculation channel of stream. Mixing and circulation are done by a paddle wheel. In many cases, baffles are placed in the flow channel to guide around the bends. The channels are built in concrete or compacted earth and may be lined with plastic. During the day, the microalgae culture is fed continuously in front of the paddlewheel where the flow is initiated. Microalgae “soup” is usually being harvested behind the paddle wheel, on completion of the circulation loop. To prevent any sedimentation, the paddlewheel should be running all the time. In this raceways method, cooling system is done only by evaporation. As the temperature fluctuates within a diurnal cycle and seasonally, evaporation water loss can be significant. Because of this occurrence, raceways use carbon dioxide much less efficiently than photobioreactors. It is not unusual that unwanted microalgae and other microorganisms contaminate the culture and thus lower the productivity. Raceways pond is commonly identified as less expensive than the photobioreactors, because they cost less to build and operate. The low cost operation and investment is however at least partly compensated with low biomass productivity. 2.3.2 Photobioreactors The second medium for microalgae is photobioreactors which allow essentially culture of single species microalgae for prolonged durations. This method has been successfully used for producing large quantities of microalgae biomass [Ugwu et. al., 2008].

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A tubular photobioreactors usually consist of an array of straight transparent tubes that are usually made of plastic or glass. This tubular array is designed to capture the sunlight or any artificial sunlight. The diameter of the tubes is limited to a certain size because light will not penetrate too deep in the case of dense algae culture, which is necessary to ensure a high level of biomass productivity. Microalgae culture is circulated from a reservoir tank to the solar collector and back to the reservoir tank, continuously.

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Algae harvest by Centrifugal SeparatorOutlet

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Figure 18. Set of equipments for microalgae project by using photobioreactors. The photobioreactors unit is mainly consisting of: Plexiglas tubes, vertical manifolds, reservoir tank, pump and control panel unit (Figure 18.) The rate of circulation of the microalgae culture can be adjusted by selecting a different speed of the centrifugal pump. The carbon dioxide feed point should be located in the pipe section between the pump and the reservoir tank to ensure high mixing ratio of microalgae culture with the carbon dioxide. The flow nature of microalgae suspension should be turbulent to prevent the formation of biofilm on the walls of the tubes which can later slow down the photosynthesis process.

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Figure 19. Reservoir tank of the photobioreactors. The reservoir tank is considered as the most essential part of the photobioreactors system. Inside, there are several parts such as: temperature probe and pH probe to monitor the variables, and also a solenoid heater/radiator to maintain the temperature of the microalgae solution to a desired temperature by flowing either cold or hot water (Figure 19.)

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Figure 20. Photobioreactors used at Blue Lagoon R&D lab. Based on available literature, the maximum rate of oxygen generation in typical photobioreactors is approximately 10 gr-O2.m

3.min-1[Benemann, 1997]. If the level of oxygen is higher than the level of air saturation, most of the time it will restrain the photosynthesis process. To avoid this event, the returned microalgae solution is sprayed from the top of the reservoir tank where it falls down by a distance of about one fourth of the tank’s height. The Blue Lagoon CO2 bio-mitigation project is currently utilizing the photobioreactors method (Figure 20) with artificial illumination to replace the sunlight. The horizontal tubes are stacked vertically to allow maximum exposure to the installed lights and also to optimize the space usage. 2.4 Experimental Microalgae nutrition and its harvesting systems Essentially, growth medium must provide sufficient nutrients for the growth of microalgae. Carbon, nitrogen, phosphorus, and sulfur are simply the most important elements constituting algae cells. Other essential elements include iron, magnesium, trace elements, and in some cases, silicon [Rebolloso-Fuentes et. al., 2001]. It is important to develop balanced media for optimal microalgae cultivation and CO2 fixation [Mandalam and Palsson, 1998]. At the Blue Lagoon photobioreactors system, the concentration of nitrogen, phosphorus and sulfur is approximately 0.15% vol. of total microalgae solution. Harvesting the microalgae is considered to be an expensive and problematic part of industrial production of microalgae biomass due to the low cell density achievable with

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microalgae cultures, which is typically in the range of 0.3–0.5 g dry cell weight per liter and with exceptional cases reaching 5 g dry cell weight per liter. There is no single harvest method that is suited to every case, and therefore, selecting the right technologies and optimizing the harvesting process are important [Molina et. al., 2003]. In the case of Blue Lagoon, the harvesting method is to utilize a centrifugal separation and later use the centrifugal sedimentation, which can yield in dry mass content of 2.5% wt. and 22% wt., respectively Growth parameters Depending on its species, microalgae growth rate may be not the same at different conditions. Some of the most important growing parameters are temperature, salinity, pH-value and level of illumination, have significant impact on growth productivity of algae. In many cases, series of experiments were carried out to examine the optimum condition for microalgae growth. 2.4.1 Parameters optimization During the process of carbon dioxide bio-mitigation by utilizing microalgae, the Blue Lagoon R&D lab has also performed several scenarios of varying the parameters of microalgae growth, such as, pH level, growing temperature, salinity level and photoactive radiation levels. The experiment was carried out in small scale photobioreactor with a total volume of 10 liters. The reactor consists of four 2.5 liters glass bottles placed in water bath as seen in Figure 21 below.

Figure 21. Diagram of small scale reactor with total volume of 10 liters.

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Optimization of pH The pH level depends on the amount carbon dioxide dissolved in the medium. Dissolution of carbon dioxide in water can be written as shown in Equation 3 below:

23

_3

3222

2 COH

HCOH

COHOHCO

(Eq. 3)

Equation 3. Carbon dioxide dissolved in water

The experiment to assess the pH variation was carried out at temperature of 43ºC, salinity 2% vol. and average photoactive radiation level of 180 μE/m2sek. The results are presented in graph (Figure 22).

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Figure 22. Growth characteristics dependent on pH level. From the graph, it can be concluded that the pH level about 7.5 gave the highest growth efficiency for the Blue Lagoon blue-green microalgae. Optimization of temperature As stated in many technical publications, the optimum temperature for microalgae growth is highly dependent on the species being used. For most microalgae species it is recommended that the media temperature be kept near 28ºC. In the case of Blue Lagoon blue-green microalgae, which belong to the group of geothermal algae, the range of temperature occurs at approximately 40ºC. As natural respiration of the algae is not able

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to keep the temperature near this level and additional heat source is used. In small scale reactor a heating element is used to increase the medium temperature, in combination with temperature regulator. The experiment was carried out at pH level of 7.5 with salinity about 2% vol. and photoactive radiation level of 140 μE/m2sek.

Based on the experiments (Figure 23), it can be concluded that the temperature which provides the optimum growth rate is 45ºC, which is a relatively high temperature as compared to other common algae species.

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Figure 23. Growth characteristics dependent on temperature. Optimization of salinity In general, the marine microalgae (i.e. Blue Lagoon blue-green algae) will need seawater supplemented with commercial nitrate and phosphate fertilizers and few other micronutrients to grow. In many cases, fresh and brackish water from lakes, rivers and aquifers can also be used as a growth media. Thus, in general, the growth media is inexpensive. For blue green algae the natural environment is geothermal water with content 70% vol. of seawater and 30% vol. of freshwater. It could be expected that the optimal salinity of media for that kind of algae should be close to the level of seawater. The experiment for salinity effect was carried out at temperature 45ºC, pH = 7.5 and irradiation level of 140 μE/m2sek.

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Figure 24. Growth characteristics dependent on salinity level. The result in Figure 24 show that the highest growth rate for the blue green algae occurred at 2.5% vol. of salt content, which is comparable to the salinity of seawater. The conductivity of 2.5% vol. salt solution is about 50 mS/cm. Optimization of illumination Microalgae are considered as sunlight-driven cell factories that by photosynthesis reaction convert carbon dioxide to potential biomass. For that reason the light plays principle role during algae cultivation process and is considered as the most important parameter. The optimization was carried out by changing the wattage of the light bulbs and varying the distance of the light bulbs to the photobioreactors which resulted in variance of illumination levels to the microalgae culture. Based on previous experiments the optimization of irradiation level was carried out at temperature 45ºC, pH = 7.5 and salinity level 2.5% vol. The experiments revealed that irradiation level of 500 μE/m2sek gives the optimal level of microalgae in respect to growth rate (Figure 25.) However, based on private conversation with Blue Lagoon senior scientist, Sigurbjörn Einarsson, when the costs of electricity is considered during the optimization the optimal irradiation level is estimated at level 200 μE/m2sek.

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800 μE/m^2 sek

1000 μE/m^2 sek

Figure 25. Growth characteristics dependent on irradiance level.

The required irradiation level is provided by placing two 400 W halogen lamps adjacent to the reactors. The heat needed to maintain the desired temperature was provided by heating element which placed in the water bath which then heats up the reactors by convection. In summary, it can be concluded that the microalgae species that is being cultivated (Cyanobacteria/ blue-green algae) has reached the optimum growth with the following conditions:

Salinity concentration of 2.5 % vol. Temperature of 45 deg-C Photoactive radiation of 500 μE/m2sek (200 μE/m2sek when electrical cost is

taken into account) pH of 7.5

2.4.2 Utilization of geothermal power plant’s CO2 The Blue Lagoon Company in partnership with HS-Orka power plant of Svartsengi has initiated a project to show the feasibility of utilizing the flue gas (non condensable gasses) from the geothermal power to feed the microalgae which so far has been cultivated by using commercial carbon dioxide gas. The commercial added value for HS-orka would be the carbon credits achieved by reducing the carbon emission, and for the Blue Lagoon Company this partnership could lower the carbon emission related to the production of Blue Lagoon products, not to mention the cost reduction of purchasing the commercial pure carbon dioxide.

36

The effect of supplying geothermal carbon dioxide was investigated on two types of algae: Blue Lagoon’s blue green algae and diatoms algae. The first task was to collect the CO2 into a gas container tank after initial preparation process. The flue gas, which is released as non-condensable gas from the condenser, contains approximately 2% vol of H2S. The gas collection set up is relatively simple as shown in Figure 26 below. A metal pipe is connected to power plant exhaust gas line. The pipe is then passing through a condenser in a helical form, which is simply a bucket of cold water. The condensed gasses/steam is then separated in a separator tank, before it is connected to a compressor and a gas container. The H2S content and other toxic gasses are monitored during these steps.

Figure 26. General setup for CO2 collection process. After the gas collection stage, the volume of the condensed water from crude gas was measured. In order to fill up the 200 liters gas tank to 8 bars, about 1.5 liters of water was collected. The collected water was analyzed and its measured pH was 4.5. This value, however, does not give direct information about H2S content, because the amount of dissolved carbon dioxide was unknown and CO2 also decreases the pH level. Two chemical sampling analyses (with Drager-Tubes®) were also carried out. First result showed that the water contained about 6 ppm of hydrogen sulfide, but second probe at the same conditions gave 2 ppm level. The level of H2S content has dramatically dropped from 2% to 2 ppm which is suspected of some chemical reactions of the sulfuric gas to the inner material of the gas tank. However, the specific analysis of this occurrence will not be discussed further in this report. The experiment was started by preparing the initial suspension for microalgae growing media. The small reactors of 10 liters in volume were filled with water and added with several chemicals as listed in Table 1 below.

Geothermal Power Plant

Gas Washer and Moisture Separator

CO2 - 97%; H2S-2 %

Compressor Pure CO 2 to Gasholder

Cooling Element

Tap water

37

Chemical species Amount, g/l

NaCL 27.98

MgCl2·6H2O 5.20

MgSO4·7H2O 7.12

CaCl2·2H2O 1.54

KCl 0.78

NaHCO3 0.20

NaSiO3·9H2O 0.30

HEPES 1.19

Table 1. Chemical species of artificial sea water [McLachlan, 1964].

Prior to use, the reactor bottles were sterilized by keeping the bottles at 120 ºC for 25 minutes. The setup, as shown in Figure 27 and 28 below, is mainly consist of four 10 liters-reactors, in which each of them has its own pH probe and feeder for air mixture with CO2.

Figure 27. Schematic flow chart of geothermal biomitigation experiment by utilizing blue green microalgae.

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Figure 28. Laboratory scale bioreactor used in the experiment.

Two types of gases were used for the algae growth: a gas from the geothermal power plant and a pure gas (commercial) as a reference. The algae were cultivated in laboratory-scale reactor (Figure 29) with total volume of 10 liters. The cell density was monitored two times per day in three ways: a) spectrophotometer, b) dry weight and c) turbidity.

Figure 29. Diagram of small scale reactor with total volume 10 liters.

a. Spectrophotometer First measurement was carried out in spectrophotometer, where the absorbance with light of wavelength 620 nm was used. This method is based on light absorption law (Beer–Lambert law), where some components absorb only selected wavelength of light spectra wave and the absorbance value of pick gives an equivalent of cell density.

39

Absorbance transmissivity is considered following Figure 30 and Equation 4

Figure 30. Diagram of Beer–Lambert absorption of a beam of light as it travels through a cuvette of width ℓ (Crouch).

The transmission (or transmissivity) is expressed in terms of an absorbance which for liquids is defined as

oI

IA 10log (Eq. 4)

where I0 and I are the intensity (or power) of the incident light and the transmitted light, respectively. b. Dry weight A volume of 20 ml of suspension was filtered through pre-combusted (550ºC, 2h) and pre-weighted glass fiber filter. Later the filter with biomass was dried at 105ºC and reweighted. As shown in Figure 31, absorbance transmissivity and dry weight has relatively linear correlation which indicated the increase of dry weight as its absorption transmissivity is increasing.

Absorption coefficient to dry mass correlation for Blue Green Algae

y = 0,0088x + 0,004

R2 = 0,8302

0,000

0,005

0,010

0,015

0,020

0,025

0,030

0,035

0,040

0,00 0,50 1,00 1,50 2,00 2,50 3,00 3,50

Spectral absorption coefficient (620 nm)

Dry

mass, g

/20m

L

Figure 31. Correlation between absorbance transmissivity and dry weight of biomass.

Spectral absorption transmissivity (at 620 nm)

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c. Turbidity The cell density was measured in portable turbidimeter shown in Figure 32 below. This method operates on the nephelometric principle of turbidity measurement [Collado-Fernández, 2000].

a) b)

Figure 32.a) Turbidimeter during the experiment. b) Two solutions with different density which resulted in different turbidity readings.

Results shown in Figures 31 and 33 below strongly imply that all the three methods (spectrophotometer, dry weight and turbidity) are valid for monitoring the growth rate of microalgae.

Figure 33. Absorbance and turbididity correlation for blue green algae.

Spectral absorption transmissivity (at 620 nm)

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2.5 Summary of Part II The growth of blue-green and diatom microalgae were monitored for several days and samples were taken every day to measure the cell density in terms of its absorbance level. The results as presented on Figure 34 and 35 below imply that feeding the microalgae with carbon dioxide from geothermal power plant does not lower its growth efficiency, as compared with pure (commercial) carbon dioxide gas. For the blue-green algae the average difference was only 2.41%, which is insignificant. For diatom algae the influence of geothermal gas is more visible, where the average different was 7.48%.

Growth of Coccoid Blue Green Algae Supplied with Different Sources of Carbon Dioxide

0,00

0,50

1,00

1,50

2,00

2,50

3,00

0 20 40 60 80 100 120

Time, h

Cel

l d

ensi

ty (

abs

620n

m)

Pure CO2

CO2 from PowerPlant

Figure 34. Growth comparison curve for Blue Green Algae.

Growth of Diatom Algae Supplied with Different Sources of Carbon Dioxide

0,00

0,20

0,40

0,60

0,80

1,00

0 50 100 150 200 250

Time, h

Cel

l d

ensi

ty (

abs

620n

m)

Pure CO2

CO2 From PowerPlant

Figure 35. Growth comparison curve for Diatom Algae.

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CO2 fixation rate From an economical point of view, it is crucial to identify the efficiency of microalgae CO2 feeding process.

Table 2. Some microalgae strains studied for CO2 bio-mitigation [Wang et.al., 2008]. Carbon dioxide fixed through photosynthesis is converted to different organic cell components including carbohydrates, lipids, proteins, and nucleic acids [Spolaore et. al., 2006]. Although the cell carbon content varies with microalgae strains, media, and cultivation conditions, it changes in a relatively small range, and the law of material conservation allows us to calculate CO2 fixation rate from biomass productivity at given cell carbon content. In Table 2, such calculations were conducted using a reported biomass molecular formula, CO0.48H1.83N0.11P0.01[Chisty, 2007], when direct data on CO2 fixation rate was not available, based on the assumption that CO2 fixed in the form of extracellular products was negligible. The detailed calculation is presented as follow: Biomass molecular formula:

CO0,48H1,83N0,11P0,01

Mbiomass = 12 + 0.48 ×16 + 1.83 × 1 + 0.11 × 14 +0.01×15 = 23.2 gr/mol

896.12.23

44,/2.23,/44

O2

13PNH4COlight)(OH nutrients4CO

22

20.010.111.830.4822

CObiomassCO FmolgrMmolgrM

h

(Eq. 5)

The CO2 fixation rate is given as FCO2 = 1.89 × biomass productivity

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The biomass productivity is simply a portion of microalgae continuous production process as shown in Figure 36 below. Some of microalgae’s growth ingredients such as nutrients, carbon dioxide and salt are supplied continuously into the process to keep the balance production while keeping the microalgae to its optimum conditions.

Figure 36. Microalgae continuous production process. Referring to the biomass molecular formula, carbon dioxide flow rate measurement and continuous microalgae biomass dry weight monitoring, the approximate carbon dioxide fixation rate for Blue Lagoon blue-green microalgae is approximately 18% vol. (only 18% vol. of the supplied CO2 is absorbed by microalgae, while the remaining CO2 gas is has escaped from the system) as shown in Table 3 below.

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Time Time Dry biomass Dry biomass CO2 CO2 CO2 consumption Efficiency Cell densityhr day g g (total) Ltrs g (total) ratio % abs (620)

0 0,00 1000 1,72 2,25919 0,79 1158 2,00 2,27326 1,06 1220 2,10 2,26944 1,83 1312 2,26 2,25351 2,13 1312 2,26 2,22667 2,79 72 235 1312 2,26 10 19 2,079

139 5,79 1867 3,22 1,045142 5,92 1926 3,32150 6,23 94 329 2030 3,50 11 18

Table 3. The calculated CO2 fixation rate for blue-green microalgae. RESULTS AND CONCLUSION As we move to a more carbon-constrained world, business will ultimately have to meet customer needs in a way that generates fewer carbon emissions. Business energy efficiency and low-carbon energy supply have played, and will continue to play, an important role but more fundamental solutions are also needed. Managing the carbon footprint of products across the supply chain is just such a solution. Managing the carbon footprint of a product means minimizing the carbon emissions required to deliver that product to the end consumer. The carbon footprint of a product is the carbon dioxide emitted across the supply chain for a single unit of that product. Part I of the report covers the analysis of carbon footprinting. In the case of Blue Lagoon pilot project of 200 ml Silica Mud Mask, the largest (63%) carbon emitter in the supply chain was found to be the processing phase. This phase involves the mixing and packaging processes which consume large amount of electricity. As the processing phase takes place in Denmark, its electricity generation portfolio (more than 50% from coal) contributes the most of carbon emission in the product’s supply chain. The carbon emitter is then followed by transportation/distribution phase which contributes 33% of all the emission. After a thorough calculation of emissions for each life-cycle step, the net amount represents the total GHG emissions caused by each material and process across the product’s life cycle, and therefore the final product carbon footprint – in this case, is 137.73 grams-CO2e per box of 200 ml Blue Lagoon Silica Mud Mask. Many companies are traditionally quite inward-focused about energy consumption and carbon emissions. The pilot project shows that a company’s willingness to broaden its horizons to work collaboratively with other companies in the supply chain could provide additional opportunities to build influence, create knowledge, reduce carbon emissions and generate financial returns. Part II of the report analyzes the feasibility of CO2 fixation by using fast-growing blue green microalgae species which proved to provide a very promising alternative for mitigation of CO2, the most prominent greenhouse gas. The primary merit of this strategy

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lays in the fact that, via the cultivation of microalgae, CO2 mitigation and valuable biomass production could be combined in an economically feasible and environmentally sustainable manner. The feasibility of this strategy was also enhanced by fixing CO2 from industrial exhaust gases such as geothermal power plant’s flue gases. The results from the experiments imply that feeding the microalgae with carbon dioxide from geothermal power plant does not lower its growth efficiency, as compared with pure (commercial) carbon dioxide gas. The average difference from the two sources of CO2 gasses for the blue-green and diatom algae was only 2.41% and 7.48%, respectively. The experiments also show that the approximate carbon dioxide fixation rate for Blue Lagoon blue-green microalgae is approximately 18% vol. (only 18% vol. of the supplied CO2 is absorbed by microalgae, while the remaining CO2 gas is has escaped from the system).

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APPENDIX A: Poster presented at Icelandic Chemical Conference