LCA of producing dissolving 
pulp from agricultural residue  
  
Master’s thesis in Industrial Ecology  
 

 
 
MANUEL MAMMEN PARAYIL 
 
 
 
 
 
DEPARTMENT OF CHEMISTRY AND CHEMICAL ENGINEERING 
CHALMERS UNIVERSITY OF TECHNOLOGY 

Gothenburg, Sweden 2023 

www.chalmers.se  

 

  

http://www.chalmers.se/


 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

LCA of producing dissolving pulp from agricultural residue 

MANUEL MAMMEN PARAYIL 

 

 

 

© MANUEL MAMMEN PARAYIL, 2023. 

Supervisors: Josefin Neuwirth, Tomas Rydberg, Lisa Hallberg, IVL Svenska Miljöinstitutet 

Examiner:  Diana Bernin, Chalmers University of Technology 

 

 

 

 

Department of Chemistry and Chemical Engineering 

Chalmers University of Technology 

SE-412 96 Gothenburg 

Telephone +46 (0) 31 772 1000 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  



 

LCA of producing dissolving pulp from agricultural residue 

MANUEL MAMMEN PARAYIL 

Department of Chemistry and Chemical Engineering 

Chalmers University of Technology  

 

 

ABSTRACT 
 

The textile industry is wrought with sustainability challenges and the production of raw 

materials have a significant contribution to different environmental impacts. The two major raw 

materials used today for textile fibre production are cotton, and synthetic fibre. Cotton 

consumes a huge number of resources like land and water, while synthetic fibres are derived 

from fossil fuels. There is a need to shift away from them.  

 

Wood based fibres are making a comeback in the textile industry, as they are seen as renewable. 

Wood can be converted to dissolving pulp from which rayon and viscose can be produced. 

However, other industries compete for wood as a raw material, and there is expected to be a 

situation where demand for wood exceeds supply.  

 

This calls for alternate materials, which is the context for this thesis. Agricultural residue such 

as oat husks and wheat straw have shown promising results in producing dissolving pulp. The 

study conducted in this thesis was to assess potential environmental impacts that could arise 

when scaling up the production of dissolving pulp from wheat straw via the soda cooking 

process.  

 

The environmental impacts were assessed using the Life Cycle Analysis tool, where modelling 

was conducted in the software GaBi. The results obtained were also compared to the impacts 

arising from producing dissolving pulp from wood. 

 

The results obtained show that wheat cultivation dominates most of the environmental impacts 

studied followed by the production of chemicals. From a climate change perspective, 

production of chemicals, the use of water and steam from natural gas in the system were found 

to be contributing the highest. Sensitivity analysis done show that changing to steam production 

from biomass and recycling 60% of the waste water could lower climate impacts by 17%. 

 

When comparing with wood-based fibre, there is higher climate change impact and water 

deprivation for dissolving pulp produced from wheat straw. However, in other impact 

categories, like acidification potential and photochemical oxidant formation potential, wheat 

straw-based pulp performs better.  

 

 

 

 

 

 

 

 

 

Keywords: Life Cycle Assessment, GaBi, dissolving pulp, Wheat straw, textile industry.   



ACKNOWLEDGEMENT 

 
The work in this thesis has been carried out as part of the project “CircuCel” (Cirkulär cellulosa 

till framställning av textilfiber), project number 2021-02093 funded by the Swedish innovation 

agency VINNOVA. The work is also linked to and co-sponsored by the project “Calimero” 

(Industry CAse studies anaLysis to IMprove EnviROnmental performance and sustainability of 

bio-based industrial processes), project number 101060546 funded by The European Union. 

 

It has been an amazing and rewarding journey all throughout this master thesis and I thoroughly 

enjoyed carrying out this study. Thank God for all His grace and kindness.  

 

I would like to thank my supervisors at IVL. Josefin Neuwirth for all her time and efforts in 

teaching me the software GaBi and for helping me around challenging problems in modelling 

my system. Gustav Sandin Albertsson and Tomas Rydberg for their support, oversight, and 

encouragement throughout the project. I also thank Maria Hernandez Leal and Benjamin Storm 

for their valuable insights as well. I t thank my examiner Diana Bernin at Chalmers University 

for her support as well.   

 

Thank you, Linnea Nilsson, for providing simulation data and other valuable assumptions. I 

would also like to thank Nanny Thorman with whom part of this thesis was done in 

collaboration with. It was great to learn from each other and was fun to work with you as well. 

I thank all fellow thesis students and colleagues at IVL for a great five months together.  

 

Thank you, Mahesh, for constantly checking in and giving plenty advice throughout the thesis. 

Lastly, I thank my family and close friends in Gothenburg - Jonathan Pearson, Kat Reece, the 

Hilers and the Noréns who have supported me and taken care of me throughout the last two 

years in Sweden.  

 

Manuel Mammen Parayil, Gothenburg, May 2023 

 

 
  



Table of Contents 
1 INTRODUCTION ................................................................................................................................... 1 

1.1 Aim ...................................................................................................................................................... 2 

2 BACKGROUND ..................................................................................................................................... 3 

2.1 Dissolving pulp ................................................................................................................................. 3 

2.2 Chemical pulping processes.......................................................................................................... 3 

2.3 Dissolving pulp from wheat straw via soda pulping process (lab scale) ......................... 4 

2.4 Life Cycle assessment framework .............................................................................................. 5 

2.4.1 Goal and scope ......................................................................................................................... 5 

2.4.2 Inventory analysis ................................................................................................................... 5 

2.4.3 Impact assessment ................................................................................................................... 6 

2.4.4 Interpretation of results.......................................................................................................... 6 

2.5 Prospective life cycle analysis ..................................................................................................... 6 

3 LIFE CYCLE ASSESSMENT ............................................................................................................ 7 

3.1 Goal and scope .................................................................................................................................. 7 

3.1.1 Functional unit ......................................................................................................................... 7 

3.1.2 System boundaries .................................................................................................................. 7 

3.1.3 Indicators and impact categories studied.......................................................................... 8 

3.1.4 Data requirements ................................................................................................................... 9 

3.1.5 Sensitivity analysis ................................................................................................................. 9 

3.1.6 Assumptions and limitations ................................................................................................ 9 

3.2 Life cycle inventory analysis ..................................................................................................... 10 

3.2.1 Flowchart for system ........................................................................................................... 10 

3.2.2 Description of activities ..................................................................................................... 11 

3.3 Energy data ..................................................................................................................................... 14 

4 RESULTS AND DISCUSSION....................................................................................................... 15 

4.1 Results for dissolving pulp from wheat straw ...................................................................... 15 

4.1.1 Climate change impact ....................................................................................................... 18 

4.1.2 Sensitivity Analysis – steam from biomass .................................................................. 20 

4.1.3 Sensitivity Analysis – recycling water ........................................................................... 21 

4.1.4 Sensitivity Analysis – steam from biomass and recycling of water ...................... 22 

4.1.5 Sensitivity analysis – no burden on wheat straw ........................................................ 23 

4.2 Comparison of dissolving pulp from wheat straw with wood ......................................... 26 

5 CONCLUSION ..................................................................................................................................... 29 

6 REFERENCES ...................................................................................................................................... 31 

Appendix A: Description of Impact Categories ........................................................................................ I 



Appendix B: Life Cycle Analysis of Benchmark – Dissolving Pulp from wood ......................... III 

Appendix C: Life Cycle Inventory Assessment of dissolving pulp from wheat straw ................. X 

Appendix D: Process settings for dissolving pulp to wheat straw in GaBi .................................. XII 

Appendix E: Additional LCA results of dissolving pulp from wheat straw ............................... XIV 

 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



 

List of Tables  

Table 3.1: List of environmental impacts studied and their assessment methodology .............. 8 

Table 3. 2: Energy indicators studied and their assessment methodology ................................. 9 

Table 3.3: Emissions from Recovery Boiler ............................................................................ 14 

Table 3. 4: Energy Demand per ton of dissolving pulp for different steps .............................. 14 

 

Table 4.1:  Impact Assessment results per tonne dissolving pulp for the different indicators 

studied (base case) .................................................................................................................... 15 

Table 4.2: Impact Assessment results for one tonne of dissolving pulp, steam from biomass 

compared to base case .............................................................................................................. 20 

Table 4.3: Impact Assessment results for one tonne of dissolving pulp, recycling water 

compared to the base case ........................................................................................................ 21 

Table 4. 4: Impact Assessment results for one tonne of dissolving pulp, steam from biomass 

and recycling water compared to base case ............................................................................. 22 

Table 4. 5: Impact Assessment results for one tonne of dissolving pulp with no environmental 

burden on wheat straw compared to base case ......................................................................... 23 

Table 4.6: Impact Assessment results for one tonne of dissolving pulp from wheat straw 

compared to the benchmark case. ADP – Abiotic Depletion Potential, non fossil resource. 

POF – Photochemical Oxidant Formation. EP – Eutrophication Potential. PERT – Primary 

energy renewable resources. PENRT – Primary Energy non renewable resources. AP – 

Acidification Potential.     CC – Climate Change. ODP – Ozone Depletion Potential. ........... 26 

  

Table B. 1: Process settings in GaBi for benchmark ................................................................ IV 

Table B. 2: Process Settings in GaBi for raw material transport for benchmark ..................... IV 

Table B. 3: Process Settings in GaBi for transport of chemicals for benchmark ..................... IV 

Table B. 4: Life Cycle Inventory data for benchmark case...................................................... VI 

Table B. 5: Average results of environmental indicators studied for benchmark case 

(unallocated). ......................................................................................................................... VIII 

Table B.6: Prices for products from Domsjö Fabriker, adapted from (González-García et al., 

2011) ......................................................................................................................................... IX 

Table B. 7: Mass and economic allocation factors for dissolving pulp, lignin, and ethanol.... IX 

 

Table C. 1: Life cycle inventory data for dissolving pulp from wheat straw ............................ X 

 

Table D. 1: Process settings in GaBi for the different flows, dissolving pulp from wheat straw

 ................................................................................................................................................ XII 

Table D. 2: Process settings for transport of wheat straw in GaBi ........................................ XII 

Table D. 3: Process setting for transport of chemicals in GaBi ............................................. XII 

 

Table E. 1: Impact assessment results of individual processes in dissolving pulp from wheat 

straw (base case) .................................................................................................................... XIV 

Table E. 2: Impact assessment results for individual processes when considering steam from 

biomass ................................................................................................................................... XV 

Table E. 3: Impact assessment result for all processes when considering no environmental 

burden on wheat straw ........................................................................................................... XVI 

 

 



List of Figures  

Figure 1. 1: Different Steps in a Life Cycle Assessment (Baumann & Tillman, 2004) ............ 5 

 

Figure 2.1: Graph showing the Collingridge Dilemma, where as knowledge of a technology 

increases, the design freedom decreases. Taken from (Arvidsson et al., 2018). ........................ 6 

 

Figure 3.1: Flowchart showing the different processes involved in producing dissolving pulp 

from wheat straw ...................................................................................................................... 11 

 

Figure 4. 1: Relative contribution of the different processes to indicators studied for the base 

case. ADP – Abiotic Depletion Potential, non fossil resource. POF – Photochemical Oxidant 

Formation. EP – Eutrophication Potential. PERT – Primary energy renewable resources. 

PENRT – Primary Energy non renewable resources. AP – Acidification Potential.     CC – 

Climate Change. ODP – Ozone Depletion Potential. ............................................................... 16 

Figure 4.2: Contribution of different processes to the climate change impact indicator (base 

Case) ......................................................................................................................................... 18 

Figure 4.3: Contribution of different processes to the different impacts with no burden 

associated with wheat straw ..................................................................................................... 24 

Figure 4. 4: Contribution of different processes to the impacts for the benchmark ................. 27 

 

Figure B.1: LCA model for the benchmark in GaBi for the year 2019 .................................... V 

 

Figure D.1: LCA model for dissolving pulp from wheat straw in GaBi ............................... XIII 
 

 
 
 
  



 

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1 INTRODUCTION 

 

In 2015 the United Nations member states adopted the 2030 Agenda for sustainable 

development which proposed 17 goas towards sustainable development referred to as the 

Sustainable Development Goals (SDGs). Goal 13, ‘Take urgent action to combat climate 

change and its impacts’ points out the need to reduce greenhouse gas emissions to limit global 

warming in order to ensure sustainable development (United Nations, n.d.). 

 

The textile industry is known to emit huge greenhouse gas emissions. The European 

Parliamentary Research Service (EPRS, 2019) reported that 1715 million tons of carbon di 

oxide was emitted in the year 2015 by the textile industry. The industry also has other 

sustainability challenges such as huge water consumption and large use of finite resources 

(Sandin et al., 2019). It was one of the first industries to be affected by the industrial revolution, 

where continuous improvement in technology resulted in mass production of clothing (Shishoo, 

2012). The economic policies of the last few decades have made the textile industry globally 

interconnected with cheap labour in Asian countries while also increasing resources used in 

production. The fast fashion industry of the late 90s have influenced the industry to transition 

to one of very high turnover and mass consumption which are highly unsustainable (Scheffer, 

2012). In fact, Roos (2016) reports that the production of textile fabrics is around 100 million 

tonnes annually, which is expected to increase as the global population is set to be 8 billion by 

2030 (OECD-FAO, 2022). This rise in demand will only worsen sustainability issues unless 

steps are taken to address them.  

 

There are different measures that can be taken to address sustainability issues within the textile 

industry. For instance, improving recycling rates, increasing lifetime of clothes, and raising 

awareness amongst users to name a few. But it has been found that raw material production in 

the textile industry contribute to environmental impacts, particularly the use of cotton and 

synthetic fibres, the two largest fabrics used in in the industry (EPRS, 2019).   Cotton consumes 

tremendous amounts of water, land, and fertilizers (EPRS, 2019) whereas 

synthetic fibres although cost effective, are derived from fossil fuels, which negatively impact 

climate change. Hence there is a great opportunity to study alternative raw materials that could 

possibly have lower climate and environmental impacts.  

 

The challenges with cotton and synthetic fibre, has resulted in an increase in the share of wood-

based fibres in the textile industry as these are seen as renewable (Kallio, 2021). The most 

common use is to convert wood to dissolving pulp which can be further used to produce textile 

fibres. However, an increase in demand for wood-based textile production, puts a constrain on 

forests as it caters to other sectors as well (Kallio, 2021).  

 

Sweden has plenty of forest land available due to its geography (Formas, 2012) but as reported 

by Material Economics (2020), the demand for wood-based biomass is set to grow significantly 

in Sweden and there will reach a situation where demand exceeds supply of wood. This calls 



 

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for better resource management and other strategies which are not in the scope of this report 

but underpins the need to shift from wood as starting material in bio-based products.  

 

Agricultural residue is seen as an alternative to wood to produce dissolving pulp and a study 

conducted by Jahan et al., (2021) shows different non-wood materials like wheat straw, rice 

straw and bamboo among others that can be used to produce dissolving pulp, often achieving 

yields close to 50%. 

 

The issues and challenges in the textile industry and resource constrains with forests, set the 

context of this master thesis. The CircuCel project between TreeToTextile, Chalmers and IVL 

is tasked with studying such agricultural residues for producing dissolving pulp and in the 

previous year promising results were seen with wheat straw and oat husk to produce dissolving 

pulp at a lab scale. The results of this study would help TreeToTextile in understanding the 

different environmental impacts of raw material choices in producing dissolving pulp, as this 

is later used as their starting material to produce textile related fibres (TreeToTextile, 2023).  

 

1.1 Aim  

 

The aim of this master thesis is to assess the potential environmental impacts of scaling up lab 

trials to an industrial process to produce dissolving pulp from wheat straw via the soda cooking 

process. The impacts will be studied using a life cycle assessment methodology. The aim also 

includes comparing the environmental impacts with a benchmark case of dissolving pulp from 

wood.   

 

 

 

 

 

 

 

 

 

 

 

 

 

 



 

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2 BACKGROUND   

 

2.1 Dissolving pulp  

 

All plant biomass contain cellulose as a major component in its cell wall and it is the most 

largely available organic material on earth (Rowell, 2012). It also contains other carbohydrate 

structures such as hemicellulose and lignin (Ek et. al., 2009). Due to its high degree of 

polymerization, cellulose has unique properties which make it highly valuable in the chemical 

industry, however it needs to be separated out from the other carbohydrates present (Ek et. al., 

2009). Dissolving pulp is pulp that has high cellulose content (95%) produced after subjecting 

plant biomass to chemical pulping processes that break down lignocellulosic content. The pulp 

produced can then be used to derive other material such as rayon and viscose, which are 

important to the textile industry (Beirmann,1996).  

 

2.2 Chemical pulping processes 
 

In order to separate and produce high cellulose content in dissolving pulp, various chemical 

processes exist. Some of the most common methods used today are the soda pulping process, 

the kraft pulping process, and the sulphite pulping process (Beirmann,1996).  

 

• Soda cooking process – In the soda cooking process the biomass is cooked with sodium 

hydroxide and then bleached to produce dissolving pulp. It was one of the first methods 

in the pulping industry and is mainly used when using straw based biomass as raw 

material (Beirmann,1996). 

 

• Kraft pulping process – The Kraft pulping process differs from the soda cooking process 

in that sodium hydroxide and sodium sulphite chemicals are both used to cook biomass 

at around 180°C to give stronger pulp. The advantage is its usefulness in cooking most 

wood species. However, pulps produced from this step are harder to bleach, have low 

yield and the presence of harmful sulphur residue. It is often preceded by an acid pre-

hydrolysis step in which the plant biomass is subjected to sulphuric acid to liberate cell 

fibres and dissolve hemicellulose content. This makes it easier to extract cellulose in the 

cooking step (Beirmann,1996). 

 

• Sulphite pulping process – In this process, biomass is treated with sulphurous acid along 

with its alkali salts to separate lignin by forming lignosulfonates. This process is 

common in Swedish pulp mills and is suitable for most wood species. Pulps produced 

by this process are bright and easily bleached compared to the ones from the kraft 

process, however they are not as strong  (Beirmann,1996). 

 

 

 

 



 

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2.3 Dissolving pulp from wheat straw via soda pulping process (lab scale)   

 

This section further explains how dissolving pulp can be produced from wheat straw via the 

soda cooking process. The soda cooking process as mentioned in the previous section is useful 

for straw based raw materials. 

The lab-based processes are described below (Sjöstedt, 2022).   

 

1. Acid pre-hydrolysis  

Acid pre-hydrolysis is conducted with sulphuric acid (0.1% concentration) at elevated 

temperature (160 °C) to open up the cell structures in the lignocellulosic biomass. This 

ensures that the lignin is accessible for further processing with sodium hydroxide. The 

sulphuric acid hydrolyses hemicellulose because of their short-chained structures to their 

respective monomers which can be recovered for further processing if required.   

 

2. Soda cooking  

As mentioned earlier, in the soda cooking process the biomass is treated with sodium 

hydroxide (6% concentration) at a temperature of 170°C. This ensures delignification takes 

place and high-grade cellulose is obtained. The by-product of this step is black liquor which 

mostly is used to recover energy and chemicals in industrial processes.  

 

3. Bleaching 

In this step all unwanted impurities are removed to give the pulp its desired purity. Within 

the pulping industry chlorine bleaching was mostly used but due to its high impacts on the 

environment, industries switched to chlorine dioxide bleaching. Using absolutely no traces 

of chlorine is the best option and, in this study, bleaching via hydrogen peroxide step was 

studied. There is also the need to use chelating compounds like Ethylenediaminetetraacetic 

acid (EDTA) to inhibit transition metals that can affect the yield of the bleaching process.  

 

The conclusions from lab trials were that for the case of wheat straw harsher bleaching steps 

are required to meet the desired quality for dissolving grade pulp. This was later improved 

at lab experiments with a two-step bleaching process using hydrogen peroxide of 3% and 

5% concentration, respectively.  

 

 

 

 

 

 

 

 

 

 

 



 

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2.4 Life Cycle assessment framework  
 

A Life Cycle Assessment (LCA) is useful to understand the environmental impacts occurring 

along the Life cycle of a product, from when the materials are extracted to its production and 

disposal at the end of life. LCA can help in understanding why one product is better than the 

other, while also looking at more global level impacts rather than site specific. In the process 

industry, LCA is usually conducted with a cradle to gate approach. This is because in process 

industries, the main application of LCA is to look at what are some environmentally better 

design or process options. LCA in the process industry has also helped in process improvements 

ultimately leading to better environmental performance (Baumann & Tillman, 2004). There are 

four main steps in an LCA namely - goal and scope definition, inventory analysis, impact 

assessment, and interpretation of results which are often iterative in nature.  

 

 
Figure 1. 1: Different Steps in a Life Cycle Assessment (Baumann & Tillman, 2004) 

    

2.4.1 Goal and scope 

 

In the goal and scope definition the reason for carrying out the study is specified and along with 

it all other contextual information about the product or process is studied. It is necessary that 

specific goals are set for the LCA study and not a vague description. The goal and scope step 

also include information on the type of LCA to be conducted and the environmental impacts 

that will be considered (Baumann & Tillman, 2004).   

An important part is to define the functional unit of the system under study. A functional unit 

is a unit with which all other flows in the system are related to and all impacts will be quantified 

in relation to the functional unit. The choice of functional unit must be representative of the 

function of the system. In the goal and scope step other aspects like time horizon, geographical 

scope, data requirements and system boundaries must be specified (Baumann & Tillman, 2004).  

 

2.4.2 Inventory analysis 

In this step all environmentally relevant flows are collected and built up as per the different 

processes present in the system. This includes energy flows, material flows emissions and 

others entering and leaving the system boundary which must reflect the goal and scope defined. 

Once all relevant data is collected, they must be normalised in relation to the functional unit. 



 

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The inventory analysis step is often considered as the most time-consuming step in an LCA 

study (Baumann & Tillman, 2004). 

 

2.4.3 Impact assessment  

In this step all the flows quantified in the inventory analysis are related to its environmental 

impacts. This also means that a lot of environmental loads will be classified and aggregated to 

represent the studied impacts and convey relevant information. This is done by multiplying the 

environmental load with a characterisation factor. These will significantly depend on the impact 

assessment method used in the study (Baumann & Tillman, 2004). 

 

2.4.4 Interpretation of results  

 

In this step the results of the impact assessment and inventory data are refined and presented to 

best reflect the goal and scope definition. This might include showing different graphs and 

diagrams that answer the specific questions in the goal and scope definition. It must also convey 

results that are relevant for the intended audience. It is often common that sensitivity analysis 

and scenario analysis are conducted to conclude the findings of the LCA study (Baumann & 

Tillman, 2004). 

 

2.5 Prospective life cycle analysis  

 

According to Arvidsson et al. (2018) , a prospective LCA is an LCA conducted to provide 

environmental guidance in early development of a process or technology where potential 

environmental impacts can be detected. This allows for more freedom in changes or alterations 

that would be difficult to implement later once the technology matures. However, at early stages 

of development, knowledge of how a technology will behave or impact the environment is 

limited although high degree of freedom exists. This conflict in freedom of change versus 

knowledge at maturity is referred to as a Collingridge dilemma ( Figure 2.1, Arvidsson et al., 

2018). 

 
Figure 2.1: Graph showing the Collingridge Dilemma, where as knowledge of a technology increases, the design freedom 
decreases. Taken from (Arvidsson et al., 2018). 

 



 

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3 LIFE CYCLE ASSESSMENT  

 

In this section the LCA of dissolving pulp production from wheat straw is described. The LCA 

for the benchmark case (dissolving pulp from wood) can be found in Appendix B. 

 

3.1 Goal and scope 

 

The goal of this LCA is to investigate the environmental impact of producing dissolving pulp 

from wheat straw. The process has been scaled up from laboratory to industrial scale using 

ASPEN PLUS. The modelling in ASPEN PLUS is not part of this master thesis and more details 

can be found in a separate master thesis (Linnea, 2023). The results will also be compared to a 

benchmark (dissolving pulp). Information and data present in the environmental reports of 

Domsjö Fabriker plant in Sweden will serve as a benchmark, representing a generic model for 

dissolving pulp produced from wood.  

 

More specifically the LCA will try to answer the following questions –  

1. What processes or steps contribute to the environmental impacts?  

2. Are there any measures or changes in the process that can lower the environmental 

impact?  

3. How does the environmental performance of the dissolving pulp from wheat straw 

compare against dissolving pulp from wood (benchmark). 

The scope of this study is a cradle – gate prospective attributional LCA study in which the 

processing of all chemicals required and other materials including their transport to the industry 

up to the point where dissolving pulp leaves the gate of the industry is considered. The 

cultivation of wheat will also be considered within the scope of this study since wheat straw 

residue is generated from this step. The use phase along with its transportation is not considered, 

as these impacts will be independent of the process route through which dissolving pulp is 

produced.  

 

3.1.1 Functional unit  

 

The functional unit was considered as 1 tonne of dissolving pulp (93% dry) produced from 

the entire process. This is appropriate as the function of the system under study is to produce 

dissolving pulp and therefore quantifying impacts in terms of amount produced is logical. 

However, a note must be made regarding the quality of the pulp produced. From the results 

obtained through lab trials the purity of dissolving pulp needs to be slightly improved before it 

can be considered as a good grade of material for further use. This qualitative difference with 

respect to the LCA of dissolving pulp from wood based raw materials is not captured in the 

functional unit. In this study the reference flow is the same as the functional unit.  

 

3.1.2 System boundaries  

 
As mentioned, the system boundary of the LCA is a cradle to gate study. The background 

system has been identified as the production and transport of raw materials which in this case 

is wheat straw along with all the required chemicals. The foreground system includes the entire 

industrial process along with the wastewater treatment plant and energy recovery unit in which 



 

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the black liquor produced from the soda cooking step is sent to recover energy and part of the 

sodium hydroxide used.  

  

Geographical boundaries – The plant will be assumed to be set up in Sweden, Skåne county 

(Nymölla) as TreeToTextile already has an existing pilot plant for converting dissolved pulp 

into cellulose fibre. The area is also close to other industrial clusters which may have potential 

symbiosis opportunities later. It was assumed that wheat straw is sourced from within the Skåne 

county while chemicals required, span the entire European union region. The electricity mix 

from Sweden is considered.  

 

Time horizon – Since this is a prospective study, the time period for the operation of this plant 

was assumed to be approximately 5 years from now with an operational life of 10-12 years. 

  

Other boundaries – Capital goods and personnel are beyond the scope of this study and will 

be excluded from the system. The construction impacts will also not be considered and can be 

part of a separate study. This is justified because inclusion of these would have no significant 

difference to the impacts of the product and would make sense to consider only at a more 

realistic stage of the implementation of the plant and not early on when looking at different 

process options.  

 

3.1.3 Indicators and impact categories studied 

 

A list of impact categories and indicators with their assessment methods are given in Table 

3.1and Table 3. 2 below. Wherever possible the Environmental Footprint 3.0 assessment 

method was chosen to calculate impacts for the respective categories. The reason being that the 

European commission recommends this method as common practice for LCA impacts of goods 

and services (EU Commission, 2021). In all other cases the indicators proposed in the 

Environmental Product Declaration (EPD) international system were chosen.  

 
Table 3.1: List of environmental impacts studied and their assessment methodology 

Impact Category Unit Method  

Climate Change (CC) kg CO2 eq. Environmental Footprint 3.0 

Abiotic Depletion Potential, non-

fossil resources (ADP)  

kg Sb eq. EN15804+A1 

Eutrophication Potential (EP) kg Phosphate 

eq. 

CML 2001 

Photochemical oxidation 

formation (POF) 

kg NMVOC 

eq. 

ReCiPe 1.05 Midpoint (H) 

Acidification Potential (AP) mole H+ eq. Environmental Footprint 3.0 

Ozone Depletion Potential (ODP) kg CFC -11 

eq.  

Environmental Footprint 3.0 

Water deprivation   m3 world eq.  Environmental Footprint 3.0 

 

 

 

 

 

 

 



 

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Table 3. 2: Energy indicators studied and their assessment methodology 

Indicator Unit Method  

Total use of renewable 

primary energy (PERT) 

MJ EN15804+A1 

Total use of non-renewable 

primary energy (PENRT) 

MJ EN15804+A1 

 

The importance of climate change impact is clear and more so since the textile industry is 

known to emit large amounts of greenhouse gases. The cultivation of wheat implies the use of 

fertilizers and fuel which makes it relevant to study acidification and eutrophication potential. 

The industrial process will use a tremendous amount of energy and hence the energy indicators 

total use of renewable and non-renewable primary energy were chosen. The use of different 

chemicals implies different resources used and hence abiotic depletion potential was also 

studied.  

A detailed description of the different indicators used can be found in Appendix A. 

 

3.1.4 Data requirements  

 

Data required for this study will mainly be obtained from the process simulation and modelling 

of lab data in ASPEN PLUS. The simulation work is done in parallel by another master thesis 

student and hence a complete dataset was hard to gather. However, all the major material flows 

into the different processes were obtained and used in the LCA modelling. Wherever data was 

a challenge, estimations and assumptions from literature were performed and experts at IVL 

were consulted. The data for background processes, like wheat cultivation and other chemicals, 

were taken as regionalized averages representative of what is common in Europe. The 

background processes were selected from the GaBi database provided and the data hierarchy 

procedure at IVL.  

 

3.1.5 Sensitivity analysis  

 
Based on the results obtained from the impact assessment, sensitivity analysis will also be 

conducted. Focus is given on climate change impact and how sensitive the results are to 

different scenarios. Steam required for the processes can either come from natural gas or 

biomass. The base case assumes steam to come from natural gas and a sensitivity analysis based 

on steam from biomass will be studied. The system has a huge water demand and the base case 

does not include any recycling of water within the system. A sensitivity analysis based on 

recycling water will also be studied. Finally, a sensitivity analysis based on allocating no burden 

on the wheat straw will also be studied.  

 

3.1.6 Assumptions and limitations  

 

• Wheat straw was assumed to be supplied from Skåne county and that there is enough 

supply of it although Gunnarsson et al, (2020) shows that in order to maintain soil 

fertility for the Skåne region it is best to let the wheat straw remain in the fields.  

• Wheat straw supply was assumed to be only from four of the biggest wheat farms from 

Skåne (Casimir & Lund, 2020). 

• The data set used for wheat cultivation is obtained from Ecoinvent 3.8 which is data 

representative for wheat cultivation in Switzerland. This was chosen because of few 



 

10 | P a g e  
 

wheat straw based LCA literature following the same manner  (Borrion et al., 2012) , 

(Janssen et al., 2014).  

• The Ecoinvent data-set for wheat cultivation allocates 95% of the burden to wheat and 

5 % to wheat straw (Ecoinvent 3.8, accessed May 15th, 2023). 

• When comparing the yield reported for wheat cultivation in Sweden by Nilsson & 

Bernesson (2009)  with the Ecoinvent dataset used, these were found to be similar and 

assumed to not make a difference.  

• It was assumed that all chemicals were bought and transported to the factory in 

concentrated form and that dilution occurs on site. 

• The plant was assumed to be operational for 8400 hours in a year to account for 

maintenance and shutdown activities. 

• Operational issues with different processes were not considered to affect the production 

of dissolving pulp. 

• Steam required was assumed to be produced from natural gas.  

• Biogenic carbon was not included in emission calculations. This is because the uptake 

and emissions of biogenic carbon are considered to be net zero over a long period of 

time.  

 

3.2 Life cycle inventory analysis  

 

This section describes more on how the data for the system were gathered and estimated. A 

detailed inventory table for each system is given in Table C. 1. It consists of raw data received 

from the process simulation in ASPEN PLUS and normalised to the functional unit of 1 tonne 

dissolving pulp. The modelling of the system was carried out in the software GaBi. A list of 

datasets used in the software can be found in Table D. 1. 

 

3.2.1 Flowchart for system 

 

The flowchart to produce dissolving pulp from wheat straw is shown below in Figure 3.1. The 

dashed lines indicate the system boundary and as mentioned the use phase does not fall within 

the system boundary. The entire emissions for the system are indicated as an arrow leaving the 

system boundary. The background system consists of the production of chemicals and wheat 

cultivation, while the foreground system includes all operations that treat the wheat straw to 

convert it into dissolving pulp.  

 



 

11 | P a g e  
 

 
Figure 3.1: Flowchart showing the different processes involved in producing dissolving pulp from wheat straw 

3.2.2 Description of activities  

 

This section briefly describes the different activities modelled. 

 

3.2.2.1 Wheat straw cultivation 

The wheat straw required for this system is assumed to come from Skåne county and the 

required amount of raw material needed for 1 tonne dissolving pulp was calculated to be 

approximately 2.5 tons. The moisture content for the wheat straw was 11% as this is what was 

used in lab trials. To model the background system in GaBi, the wheat cultivation process, 

Wheat production, Swiss integrated production, intensive from the Ecoinvent database 3.8 was 

used. The moisture content for this process is 15% in straw and a help process was created to 

get the moisture content down to desired 11% for the study.  

3.2.2.2 Transport of wheat straw  

 

The wheat straw needed to be transported to the plant at Nymölla was assumed to take place 

only by trucks. In order to calculate the distance, the four biggest wheat farms in Skåne county 

were found out as per Casimir & Lund (2020). The distance was then calculated as 120 kms, 

which is the average distance from these farms to Nymölla using google maps. The transport 

specifications can be found in Table D. 2. 

 

3.2.2.3 Transport of all other chemicals  

 

All chemicals transported to the plant are assumed to be from a distance of 1500kms. This 

distance is considered since it accounts for the farthest regions in the EU. Transport 

specifications can be found in Table D. 3. 

  

 

 

 



 

12 | P a g e  
 

3.2.2.4 Acid pre-hydrolysis  

 

In this process, wheat straw is mixed with hydrochloric acid solution (0.125%) in a digester at 

160°C and pressure 7 bar. This causes mainly hemicellulose to dissolve in the acid solution. 

Waste liquor is generated in this step which is sent to the waste water treatment plant.  

 

3.2.2.5 Soda cooking  

 

The treated wheat straw is then mixed with sodium hydroxide solution (7.4%) 170° C and 8 bar 

pressure. It is usually carried out in batch reactors. This step separates most of the lignin which 

is found in the black liquor. The pulp produced is sent further for bleaching. The black liquor 

is sent to an energy recovery unit where it is burned to recover energy that meets most of the 

demand in the plant. The smelt that remains consists of sodium salts which are further processed 

to recover sodium hydroxide. 

 

3.2.2.6 Washing number-1 

 

Before the pulp is sent for bleaching it is subjected to counter current washing in order to 

remove chemicals and other dissolved content especially lignin. Usually, a set of 3-4 washers 

are used. The wastewater from this step is sent to wastewater treatment plant and the washed 

pulp is sent further for bleaching.  

 

 

3.2.2.7 Two step hydrogen peroxide bleaching  

 

The washed pulp is now sent for bleaching. A bleaching step is used so that the pulp can be 

brought to its desired brightness as there is still some lignin present in the pulp. The pulp in this 

system is bleached with a hydrogen peroxide of 0.62% solution and 0.37% solution along with 

the complexing agent ethylenediaminetetraacetic acid (EDTA). EDTA is used so that metals 

present in the pulp do not form ions with hydrogen peroxide and inhibit bleaching. The reaction 

is usually carried out in atmospheric pressure and at 80-110°C temperature (Ulefors, 2022). 

 

3.2.2.8 Washing number-2  

 

A washing step similar to the previous washing step is done once again to get rid of impurities, 

and the waste stream is sent to the wastewater treatment plant. The washed pulp is finally sent 

for drying.  

 

3.2.2.9 Drying  

 

The washed pulp is dried to about 7% moisture content. The drying operation consumes a lot 

of energy part of which was supplied by the energy recovered from burning black liquor and 

the rest by steam from natural gas. The waste stream from the drying step is sent to the 

wastewater treatment plant.  

 

In order to calculate the energy requirements for drying, the mass of water needed to be 

removed was taken as the water flow that came out of the dryer (Table C. 1). It was assumed 

that a mechanical press removes 50% of the water before it enters the dryer (Sundin, 2011). 

The energy required to evaporate the remaining water at 100°C was calculated with equation 



 

13 | P a g e  
 

(1) assuming a latent heat of vaporisation of 2257.92 kJ/kg steam (Engineering toolbox, 2003).  

The energy required was calculated as 5.4 GJ/ tonne of dissolving pulp.  

 

3.2.2.10 Energy and chemical recovery  

 

In this step the black liquor from the soda cooking process is further processed. Initially, the 

black liquor is sent to a series of evaporators to concentrate it further. This allows for efficient 

burning and production of energy. After that it is sent to a recovery boiler where it is burned 

with air to generate energy (Beirmann,1996). The energy recovered is used to supply the energy 

demands for the evaporators as well as for the drying process. After burning, the smelt that 

remains consist of sodium salts which is then sent to a causticizing plant where it is mixed with 

calcium oxide to get sodium hydroxide which is recycled back to the soda cooking step 

(Beirmann,1996). The recovery efficiency of sodium hydroxide was assumed to be 97% of 

sodium salts entering the boiler based on literature (Tran and Vakkilainnen, n.d.). The 

chemicals needed for the causticizing plant were not considered in the model due to time 

constrains.  

 

3.2.2.10.1  Chemical recovery data 

 

In order to recover chemicals from black liquor, a mass balance of sodium hydroxide (NaOH) 

used within the system was calculated. It was found that approximately 28% of initial NaOH 

used is lost. From the sodium hydroxide present in black liquor 97% of it is recovered based on 

the assumption mentioned above. It was found that 70% of NaOH initially used could be 

recovered and only the lost amount of NaOH needs to be accounted for in the LCA model.  

 

3.2.2.10.2  Energy recovered from black liquor 

 

The energy recovered from burning black liquor in the recovery boiler was calculated by 

assuming a steam potential of 3.5 kg steam/kg black liquor solids (Valmet, 2017). Steam 

produced was assumed to be medium pressure (MP) steam at 180°C. The latent heat of 

vaporisation at this temperature was assumed to be 2013.56 kJ/kg steam (Engineering toolbox, 

2003). 

The total energy recovered can then be calculated using equation 1 – 

𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑡𝑜𝑡𝑎𝑙 𝑚𝑎𝑠𝑠 𝑜𝑓 𝑠𝑡𝑒𝑎𝑚 ∗ 𝐿𝑎𝑡𝑒𝑛𝑡 ℎ𝑒𝑎𝑡 𝑜𝑓 𝑣𝑎𝑝𝑜𝑟𝑖𝑠𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑠𝑡𝑒𝑎𝑚           (1) 

                       

For this process it was calculated to be around 8.4GJ/ tonne dissolving pulp. 

 

3.2.2.10.3 Energy demand - evaporators  

 
The evaporators increase the concentration of black liquor to the recovery boiler and they use 

a significant amount of energy as well. The pressure at which evaporators operate was assumed 

as 4 bar with a demand of 2.5-ton steam/ tonne dissolving pulp (Orr, 2009). At 4 bar pressure 

the latent heat of vaporisation of steam was taken as 2132.95 kJ/kg (Engineering toolbox, 2003). 

Using equation (1) energy required for the evaporators were calculated as 4.3 GJ/tonne 

dissolving pulp.  

 

 

 



 

14 | P a g e  
 

3.2.2.10.4  Emissions from recovery boiler  

 
The emissions from recovery boiler were calculated as per the information given in European 

Commission’s Best Available Technique (BAT) guidelines for the paper and pulp industry 

(Suhr et al., 2015). The main emissions are to air and the quantities are shown in Table 3.3 

below. 

 
Table 3.3: Emissions from Recovery Boiler 

Pollutant Amount (kg/tonne DP) 

Sulphur di oxide 0.002-0.65 

Total reduced Sulphur 0.0007-0.4 

Nitrogen oxides 0.73-2.0 

Particulates 0.02-1.6 

 

The average values of the given ranges were entered in the energy and chemical recovery 

process. It is also important to note that biogenic carbon di oxide is released as well. But this is 

considered not to contribute to any environmental impact. To calculate the amount of biogenic 

carbon, it was assumed that 31% of the solid biomass in the black liquor consists of carbon 

(Suhr et al., 2015). Assuming that all carbon gets converted to carbon di oxide, 760 kg CO2 / 

tonne of dissolving pulp is released.  

 

3.2.2.11 Wastewater treatment plant  

 

All the waste streams from the process were sent to a wastewater treatment plant. The modelling 

of this step was assumed by adding a process that treats wastewater from municipal waste 

representative for an average EU plant. This is because no industrial level wastewater treatment 

processes were found in GaBi and to model a treatment plant from scratch is out of scope due 

to time constraints. 

 

3.3 Energy data  

 

The energy required for the different process steps are given below in Table 3. 4. These values 

were calculated based on data provided by Ulefors (2022). It was assumed that the energy 

requirements for each step would not differ much from oat husk or wheat straw as raw material. 

Data from the simulation of the process should be used but since it is time consuming and to 

avoid unnecessary wait time to proceed with LCA, calculations from the previous year was 

used.  
Table 3. 4: Energy Demand per ton of dissolving pulp for different steps 

Process Type Demand per tonne DP (MJ) 

Prehydrolysis  MP Steam  6.1 

Soda Cooking  MP Steam  3.8 

Bleaching  MP Steam  0.2 

Pumps Electricity  0.01 

 
 
 



 

15 | P a g e  
 

4 RESULTS AND DISCUSSION 

 

This section presents the results of the LCA and discusses the different observations. Firstly, 

the results for dissolving pulp from wheat straw along with individual contributions are 

presented in section 4.1 while also taking a closer look into the climate change impact category. 

Based on the observations, sensitivity analysis was conducted for different scenarios and their 

results are presented in sections 4.1.2 to section  4.1.5. Finally, the results of wheat straw pulp 

are compared with the results of the benchmark pulp from wood in section 4.2.  

 

4.1 Results for dissolving pulp from wheat straw  
 

The results for the indicators mentioned in Table 3.1 are presented below in Table 4.1, all based 

on producing 1 tonne dissolving pulp. The results are for the base case in which all the energy 

demands are by steam from natural gas. Contribution of all the processes to the different impact 

categories and indicators are shown below in Figure 4. 1.  

 
Table 4.1:  Impact assessment and inventory results per tonne dissolving pulp for the different indicators studied (base 
case) 

Impact Category Units Total Amount 

Abiotic Depletion Potential, non -fossil resources kg Sb eq. 0.0014 

Eutrophication Potential  kg Phosphate eq. 2.5 

Photochemical Oxidant Formation Potential  kg NMVOC eq. 2.6 

Total use of Renewable Primary Energy  MJ 8600 

Total use of Non-Renewable Primary energy  MJ 1300 

Acidification Potential  moles H+ eq. 5.0 

Climate Change  kg CO2 eq. 780 

Ozone Depletion Potential kg CFC-11 eq. 1.4 E-05 

Water Deprivation  m3 world eq. 35 

 

 

 

 



 

16 | P a g e  
 

 
Figure 4. 1: Relative contribution of the different processes to indicators studied for the base case. ADP – Abiotic 

Depletion Potential, non fossil resource. POF – Photochemical Oxidant Formation. EP – Eutrophication Potential. PERT – 

Primary energy renewable resources. PENRT – Primary Energy non renewable resources. AP – Acidification Potential.     

CC – Climate Change. ODP – Ozone Depletion Potential. 

 

 

 

 

 

 

 

 

 

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

ADP EP POF PERT PENRT AP CC OD Water
deprivation

Impact Assessment Results (Base Case)

Wheat Straw Cultivation Wheat Straw Transport Transport Chemicals

HCl Production NaOH Production Energy,Recovery Boiler

H2O2 Production EDTA Production Process Water

Waste Water Treatment Plant Natural Gas Steam Prodn Electricity



 

17 | P a g e  
 

From the graph above, a few interesting observations can be made. Wheat cultivation dominates 

highest contribution to 6 out of the 9 indicators studied, while also significantly contributing to 

the rest. The production of chemicals such as sodium hydroxide and EDTA have significant 

contributions to energy use, abiotic depletion potential, acidification potential and ozone 

depletion potential. Recovery boiler operations have highest contribution to photo chemical 

oxidant formation potential, while also significantly contributing to acidification potential. 

Transport activities have insignificant contributions to the overall impacts studied. Water 

deprivation is completely dominated with the use of process water in operations, however, the 

wastewater treatment plant releases cleaned water back to water bodies and hence has a negative 

value.  

 

The reason for wheat cultivation’s large impact is mainly due to the use of fertilizers and 

chemicals that are used as pesticides during its cultivation. The high contribution towards ADP 

is because of the impacts arising from the use of ammonium nitrate, inorganic fertilizers, and 

phosphorus fertilizers (Ecoinvent 3.8, accessed 15th May, 2023). The same can be said for its 

contribution to EP, it is also due to the release of nitrogen, ammonia and phosphates into fresh 

water. The release of ammonia emissions to air is what contributes to AP while organic 

compounds most probably emitted from the use of pesticides contribute to ODP. The use of 

energy is also high. This is because around 2MJ of energy from biomass are used per kg of 

wheat straw produced, along with some crude oil and natural gas (Ecoinvent 3.8, accessed 15th 

May, 2023).   

 

The production of sodium hydroxide has significant contributions to photo chemical oxidant 

formation potential and acidification potential is due to the emissions of nitrogen, sulphur 

dioxides and ammonia during production. Production of sodium hydroxide also consumes a 

significant amount of renewable energy. This is due to the high energy required for the 

electrolysis of brine, which produces sodium hydroxide. Similarly, the use of different 

chemicals in EDTA production such as formaldehyde and sodium cyanide explain the 

significant contribution to abiotic depletion potential (Ecoinvent 3.8, accessed May 15th, 2023). 

A closer look into the impacts found that the reason for high contribution of the EDTA 

production towards ozone depletion potential is due to the release of halogenated compounds 

to air.   

 

The contribution by the energy recovery process to POF and AP are also due to the release of 

nitrogen dioxide and sulphur dioxide to air. The burning of black liquor usually consists of 

lignin and some amount of sulphur is present in lignin. Burning with air implies the release of 

some nitrogen dioxides as well.  

 

Process water used contributes the highest to water deprivation and it is because of the high-

water demand of the processes. Most of the chemicals are highly diluted as per data provided 

from the simulation results. Process water contributes to other impacts as well and this because 

the process modelled includes the purification of water by an ion exchanger. This could explain 

the contributions to photo chemical oxidant formation potential and acidification potential 

while the use of energy in the ion exchange process explains the use of renewable energy.  



 

18 | P a g e  
 

4.1.1 Climate change impact  

 

Since climate change is of high relevance a closer look into the individual contributions is 

shown below in Figure 4.2. From Table 4.1 above the total climate impact for producing 1 tonne 

of dissolving pulp from wheat straw is 760 kg CO2 eq. Sodium hydroxide and hydrogen 

peroxide production contribute mostly to climate change impact. The production of these 

chemicals has significant emissions of greenhouse gases to air. These along with the use of 

process water, wheat cultivation and steam from natural gas contribute to 80% of the climate 

change impact. 

 

 
Figure 4.2: Contribution of different processes to the climate change impact indicator (base Case) 

From the graph above, sodium hydroxide and hydrogen peroxide production contribute mostly 

to climate change impact. The production of these chemicals has significant emissions of 

greenhouse gases to air. These along with the use of process water, wheat cultivation and steam 

from natural gas contribute to 80% of the climate change impact.  

 

Taking a closer look into sodium hydroxide production, it is most likely that the electricity use 

is what contributes to huge carbon emissions and thus to climate change impact. The data set 

used in the model is a European average and hence average electricity use in Europe is 

considered. The share of fossil fuels in the European grid mix is about 42% (Eurostat,2023). A 

higher share of renewables in the grid mix could lower the climate change impact of sodium 

hydroxide production. It should also be pointed out that the climate change impact presented in 

Figure 4.2 are after 70% of the sodium hydroxide has been recovered within the production 

process and actions could be taken to minimize the loss of chemicals.  

0,00

50,00

100,00

150,00

200,00

250,00

CCk
g 

C
O

2
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q
. p

er
 t

o
n

n
e 

d
is

so
lv

in
g 

p
u

lp

Climate change impact

Wheat Straw Cultivation Wheat Straw Transport Transport Chemicals

HCl Production NaOH Production Energy,Recovery Boiler

H2O2 Production EDTA Production Process Water

Waste Water Treatment Plant Natural Gas Steam Prodn Electricity



 

19 | P a g e  
 

When further studying different production methods for sodium hydroxide, there is evidence 

for a more sustainable way of producing sodium hydroxide via the oxygen depleting cathode 

(ODC) method as cited by (Garcia-Herrero et al., 2017). In the future it could be expected that 

such a process might be implemented throughout and so further reduce impact on the studied 

system.  

 

Hydrogen peroxide is widely produced via the anthraquinone process which requires hydrogen 

as a key compound. The production of hydrogen in the data set used, is modelled via steam 

cracking which most likely uses steam produced from natural gas. Steam produced from 

biomass could lower climate change impact. An important factor to consider then is deciding 

on where to source these chemicals from. The high use of electricity and energy demands for 

these chemicals imply that the energy mixes of different geographies can affect the 

environmental performances of the foreground system as well.  

 

Additionally, the wheat cultivation process contributes to 35% of the climate change impact 

and this arises from the release of dinitrogen oxides, the use of fertilizers and other farming 

operations (Ecoinvent 3.8, accessed May 15th, 2023).  

 

The process water data-set used in this study undergoes a purification step as mentioned before 

and this is likely why it contributes to the climate change impact. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



 

20 | P a g e  
 

4.1.2 Sensitivity Analysis – steam from biomass 

 

Most impact arises from the processes in the background system and not much can be done to 

change it directly from the perspective of the plant. However, sensitivity analysis could be used 

to study how different choices affect the environmental performance of the system. In this 

sensitivity analysis the effects of changing steam production from natural gas to biomass was 

studied and the results are shown below in Table 4.2.   

 
Table 4.2: Impact Assessment results for one tonne of dissolving pulp, steam from biomass compared to base case 

Impact Category  Units Base case (steam 

from natural 

gas) 

Biomass scenario 

(steam from 

biomass) 

% Change  

Abiotic Depletion Potential, non -fossil 

resources  

kg Sb eq. 0.0014 0.0014 

 

 

0 

Eutrophication Potential  

 

kg Phosphate eq. 2.5 2.6 +4 

Photochemical Oxidant Formation 

Potential 

 

kg NMVOC eq. 2.6 2.7 

 

+4 

Total use of Renewable Primary Energy  MJ 8600 10,200 +20 

Total use of Non-Renewable Primary 

energy  

MJ 1300 1300 0 

Acidification Potential moles H+ eq. 4.5 4.6 +2 

Climate Change  kg CO2 eq. 780 694 -9 

Ozone Depletion Potential kg CFC-11 eq. 1.4E-05 1.4E-05 0 

Water Deprivation  m3 world eq. 35 35 0 

 

From the table above, it is observed that producing steam from biomass lowers climate impact 

by roughly 9%. However, it does cause other impact categories like eutrophication potential, 

photo chemical oxidant formation potential and acidification potential to increase slightly. One 

important aspect to mention is that - there are biogenic carbon dioxide emissions from burning 

biomass for steam. The emissions are however are not accounted for since the amount of carbon 

dioxide emissions are balanced with the uptake of carbon dioxide during the growth of the 

biomass via photosynthesis.  

 

 

 

 

 

 

 

 



 

21 | P a g e  
 

4.1.3 Sensitivity Analysis – recycling water  

 
Another sensitivity analysis studied was performed to investigate how recycling of the process 

water would affect the environmental performance of the system. From the data gathered, close 

to 97 tons of water per tonne of pulp is used in the system. It was assumed that 60% of water 

used can be recycled in pulping plants without loss in quality (Alexandersson,2003).With this 

assumption, the water demand reduces to 41 tons per tonne dissolved pulp. The results are 

shown in Table 4.3 below.  

 
Table 4.3: Impact Assessment results for one tonne of dissolving pulp, recycling water compared to the base case 

Impact Category  Units Base case (No 

recycling of 

water) 

Recycling Scenario 

(Recycling 60% of 

water) 

% Change  

Abiotic Depletion Potential, non -fossil 

resources  

kg Sb eq. 0.0014 0.0014 

 

 

0 

Eutrophication Potential  kg Phosphate eq. 2.55 2.53 -1 

Photochemical Oxidant Formation  Kg NMVOC eq. 2.63 2.57 

 

-2 

Total use of Renewable Primary Energy  MJ 8600 8300 -3 

Total use of Non-Renewable Primary 

energy  

MJ 1300 1300 0 

Acidification Potential  Moles H+ eq. 4.5 4.3 -3 

Climate Change  Kg CO2 eq. 780 739 -5 

Ozone Depletion Potential Kg CFC-11 eq. 1.4E-05 1.4E-05 0 

Water Deprivation  m3 world eq. 35 17 -51 

 

Recycling water within the plant shows some interesting results. Overall, it reduces the 

environmental performance in most indicators. The climate change impact is reduced by 5% 

from the base case whereas water deprivation is reduced by 51% which is the highest effect by 

far. This is logical as reducing water demand will significantly reduce its overall deprivation.   

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



 

22 | P a g e  
 

4.1.4 Sensitivity Analysis – steam from biomass and recycling of water  

 

From the perspective of climate change impact using steam from biomass and recycling water 

are both good and hence implementing both these cases together should give the maximum 

possible reduction in climate change impact. The overall changes in impact categories and 

indicators for implementing both steps simultaneously are shown in Table 4. 4 below. 

 
Table 4. 4: Impact Assessment results for one tonne of dissolving pulp, steam from biomass and recycling water compared 

to base case 

Impact Category  Units Base Case Biomass and 

recycling 60% 

water scenario 

% Change  

Abiotic Depletion Potential, non -fossil resources  kg Sb eq. 0.0014 0.0014 

 

 

0 

Eutrophication Potential kg Phosphate 

eq. 

2.55 2.58 1.8 

Photochemical Oxidant Formation Potential kg NMVOC eq. 2.63 2.70 

 

2.6 

Total use of Renewable Primary Energy  MJ 8612 9961 15.6 

Total use of Non-Renewable Primary energy  MJ 1295 1295 0 

Acidification Potential   moles H+ eq. 4.5 4.56 1.3 

Climate Change  kg CO2 eq. 780 650 -16.7 

Ozone Depletion Potential kg CFC-11 eq. 1.36E-05 1.36E-05 0 

Water Deprivation  m3 world eq. 35 17 -51 

 

It can be observed that implementing both scenarios reduce climate change impact by 

approximately 17% although it does cause other impacts to increase slightly. The energy use 

increases, but it can be argued that is the share of renewables that increases. Water 

deprivation too improves due to recycling which is advantageous.  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



 

23 | P a g e  
 

4.1.5 Sensitivity analysis – no burden on wheat straw  

 
Given that wheat cultivation dominates the contribution to most impacts, it was decided to see 

how the environmental performance is affected if no environmental burden is allocated to the 

raw material. It can be argued that since wheat is the main product during wheat cultivation, all 

environmental burden must be allocated to it and none to its by-products. This is a common 

method of allocation followed in LCA practice, known as the cut-off allocation method. The 

results of this sensitivity analysis are shown in Table 4. 5 below and relevant contributions to 

each indicator in Figure 4.3.  

 
Table 4. 5: Impact assessment results for one tonne of dissolving pulp with no environmental burden on wheat straw 
compared to base case 

Impact Category  Units Total Amount 

(Base Case) 

Total Amount (No 

Burden on Wheat 

Straw) 

% Change  

Abiotic Depletion Potential, 

non -fossil resources 

kg Sb eq. 0.0014 0.0003 

 

 

-70 

Eutrophication Potential  kg Phosphate eq. 2.55 0.87 -65 

Photochemical Oxidant 

Formation  

kg NMVOC eq. 2.63 2.2 

 

-16 

Total use of Renewable 

Primary Energy 

MJ 8612 2650 -20 

Total use of Non-Renewable 

Primary energy  

MJ 1295 385 -70 

Acidification Potential  moles H+ eq. 4.5 2.50 -55 

Climate Change   kg CO2 eq. 780 679 -13 

Ozone Depletion Potential kg CFC-11 eq. 1.36E-05 3.3E-06 -70 

Water Deprivation  m3 world eq. 35 20 -43 

 



 

24 | P a g e  
 

 
Figure 4.3: Contribution of different processes to the different impacts with no burden associated with wheat straw 

From Table 4. 5, the exclusion of wheat straw burden drastically affects the environmental 

performance of the system and it further strengthens the need to include all relevant background 

processes involved in the system to get a precise understanding of the environmental impacts. 

It is also important since wheat cultivation has a huge impact on the system, uncertainty in data 

must be reduced. The data-set used was for the cultivation practices in Switzerland which were 

assumed to be the same as in Sweden. It would be wise to further look at local wheat cultivation 

data in Sweden and study how environmental performances are affected. It also highlights the 

importance of choice in allocation method. The Ecoinvent data-set allocates 95% of the burden 

to wheat and 5% to wheat straw. There could be higher economic value for wheat straw in the 

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

ADP EP POF PERT PENRT AP CC OD Water
Deprivation

Impact Assessment Results (No burden on Wheat Straw) 

Transport of Wheat straw Transport of Chemicals
Prodn. HCl Prodn. of NaOH
Energy Recovered Prodn. Of H2O2
Prodn. Of EDTA Process Water



 

25 | P a g e  
 

future which might call for an economic allocation procedure which can also affects the 

environmental impact studied.  

 

Excluding wheat straw environmental burden sheds more light into the other processes. As can 

be seen in Figure 4.3 the production of sodium hydroxide and EDTA dominate the contribution 

to most indicators once again highlighting importance of considering where to source them 

from for the reasons mentioned in the section 4.1.4.   

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



 

26 | P a g e  
 

4.2 Comparison of dissolving pulp from wheat straw with wood  

 

As mentioned earlier dissolving pulp is commonly made from wood and hence it would make 

sense to compare the environmental performances of producing pulp from wheat straw to that 

of wood. This section presents the results of the dissolving pulp from wood (based on data from 

Domsjö Farbiker AB). This will be the benchmark case and more information on the modelling 

of the benchmark can be found in Appendix B. 

 

For the dissolving pulp from wood, the refinery produces other by-products such as ethanol and 

lignin. It was decided to allocate the environmental burden between dissolving pulp, ethanol, 

and lignin first by mass allocation and economic allocation methods, to get a range for which 

environmental impacts could vary. The results are shown in Table 4.6 below with results from 

the base case of producing dissolving pulp from wheat straw. All impacts values are for 1 tonne 

of dissolving pulp produced.  

  

 
Table 4.6: Impact Assessment results for one tonne of dissolving pulp from wheat straw compared to the benchmark case. 
ADP – Abiotic Depletion Potential, non fossil resource. POF – Photochemical Oxidant Formation. EP – Eutrophication 

Potential. PERT – Primary energy renewable resources. PENRT – Primary Energy non renewable resources. AP – 

Acidification Potential.     CC – Climate Change. ODP – Ozone Depletion Potential. 

Impact Category  DP from wood 

(mass Allocation) 

DP from wood 

(economic 

allocation) 

DP from wheat straw (base case) 

ADP, non -fossil resources (kg Sb eq.) 0.00033 0.00039 0.0014 

EP (kg Phosphate eq.) 1.7 2.1 2.55 

POF (kg NMVOC eq.) 3.7 3.9 2.63 

PERT (MJ) 71480 83560 8612 

PENRT (MJ) 10035 11731 1295.5 

AP (Mole H+ eq.)  5.2 6.1 4.5 

CC (kg CO2 eq.)  415 486 780 

ODP (kg CFC-11 eq.)  1.6E-05 1.8E-05 1.4E-05 

Water Deprivation (m3 world equiv.)  1.3 1.5 35 

 

The fields marked in red and green indicate if the base case performs better or worse when 

compared to the benchmark results. From the table above, pulp made from wheat straw has a 

better performance in total use of renewable and non-renewable energy, photochemical 

oxidation formation, acidification potential and ozone depletion. Whereas its climate change 

impact, water deprivation and abiotic depletion impacts are much larger than the base case. The 

eutrophication potential is only slightly higher in the base case when compared to the 

benchmark.  

 

Figure 4. 4 below shows the contribution of the different processes in the benchmark case to 

the different indicators. The results are irrespective of the allocation procedure used since the 

relative contributions are shown. The contributions to the benchmark indicators mainly arise 

from plant related operations, forestry operations and production of chemicals. 

 

 



 

27 | P a g e  
 

 
Figure 4. 4: Contribution of different processes to the impacts for the benchmark 

 

The reason as to why wheat straw-based pulp performs better than the benchmark in POF and 

AP is that most of the impact in the benchmark arises from emissions in the plant which are 

higher when compared to emissions in the recovery boiler for wheat straw-based pulp. The 

benchmark operations have significantly higher emissions of nitrogen oxide and sulphur oxide 

gases as can be seen when comparing Table 3.3 with Table B. 4 .  

 

A reason for this could also be because in the benchmark case, sulphurous acid is a main 

compound that is used for the cooking of wood chips and hence higher emissions of sulphur 

can be rightly expected, explaining the higher results. The data for emissions for the recovery 

boiler in the wheat straw case were estimated from literature, whereas for the benchmark local 

data has been used. The uncertainty in data could affect the results of these indicators.  

 

The share of non-renewable energy is higher for the benchmark as the use of electricity is high 

and is the largest contributor to the indicator in the benchmark. Along with electricity 

consumption, the chemicals produced too contribute to PENRT in the benchmark case. The use 

of sodium hydroxide and hydrogen peroxide is much higher in the benchmark case than 

compared to the wheat straw case. The wheat straw-based pulp uses lesser chemicals as they 

are extremely diluted as per data from simulation results. The electricity use in wheat straw-

based pulp has been estimated form literature as well and uncertainty could affect the results as 

well.  

Looking into renewable energy use, both benchmark and the wheat straw case have major 

shares of contribution in raw material cultivation operations, but the energy use in forestry is 

higher than that for wheat cultivation.  

 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

ADP POF EP PERT PENRT AP CC OD Water
Deprivation

Impact Assessment Results - Dissolving Pulp from wood 

Forest Raw Material Transport of Raw Material Transport Chemicals

Prodn. EDTA Prodn. H2O2 Prodn. Lime

Prodn. Magnesium Sulphate Prodn. Sodium hydroxide Prodn. Oxygen

Prodn. Sulphur Process Water Energy from HFO

Energy from Biomass Electricity Plant Ops.



 

28 | P a g e  
 

Similar trends in OD can be observed in the benchmark and wheat straw-based case. Highest 

share comes from the cultivation of raw materials. The reason for this is due to the influence of 

halogenated compounds. However, when examining the datasets used, there is no direct use of 

halogenated compounds in the processes modelled. This could mean that there are traces of 

halogenated compounds used further upstream in the processes studied.  

 

EP is higher in the wheat straw case as most emissions arise from cultivation of wheat as 

compared to emissions from the plant in the benchmark case.  

As discussed earlier, wheat cultivation uses fertilizers and other compounds that directly affect 

eutrophication potential.  

 

Water Deprivation is significantly lower in the benchmark case as there is a huge difference in 

the total water demand comparing both systems. A well-established plant in operation would 

have significant measures in place to efficiently use and re-circulate water within its operations. 

The data used for the wheat straw-based pulp case has estimated values of water and actual 

operations could use lesser amounts of water.  

 

Evaluating from a climate change impact perspective the benchmark performs much better. 

However, these are also results based on allocation and hence it will always have a lower value 

than the wheat straw-based pulp. It is interesting to note that the unallocated results of the 

benchmark case have a climate change impact value of 645 kg CO2 which is very close to the 

sensitivity analysis results for the wheat straw case in implementing recycling of water and 

using steam from biomass (see Table 4. 4). Another reason is also that wheat cultivation impacts 

are higher than wood and so the climate change impact is higher for wheat-based pulp.  

 
 
 
 
 
 
 
 
 
 
 
  



 

29 | P a g e  
 

5 CONCLUSION 

 

This thesis set out to study the potential environmental impacts of producing dissolving pulp 

from wheat straw as raw material, using life cycle assessment. 

Three research questions were defined in the goal and scope step of the assessment and the 

results from assessment conclude that: –  

 

• The cultivation of wheat has the highest impact across most indicators due to the use of 

chemicals and fertilizers during cultivation. The production of chemicals also has 

significant contributions to the environmental impacts.  

• In the foreground system, emissions from energy recovery and the high use of process 

water contribute to the different indicators studied.  

• From a climate change impact perspective, the highest impacts arise from production of 

sodium hydroxide and hydrogen peroxide. The importance of why and where to source 

these chemicals from were also highlighted.  

• Sensitivity analysis were conducted to see how impacts would change to varying the 

source of energy and recycling water used within the system. The results show that 

using biomass and recycling of water reduces climate change impact by 17% from the 

base case and water deprivation by 50%. However, other indicators perform slightly 

worse.  

• When comparing with the benchmark case of wood-based pulp, pulp from wheat straw 

uses significantly lesser energy and has lesser eutrophication and acidification impacts. 

However, from a climate change perspective wheat straw pulp has a higher climate 

change impact. Same is the case for water deprivation as well.  

 

There were a lot of significant assumptions that could affect the results and conclusions 

presented such as estimating emission and energy data from literature. The uncertainties for 

these have not been accounted for in this study and should be included in further research. The 

importance of wheat cultivation implies that primary data from cultivation activities in Sweden 

should give better insight into the impacts of producing dissolving pulp from wheat straw in 

Sweden. The benchmark case has production of by-products which too can be produced from 

wheat straw as raw material. Future research could also investigate simulation data for these 

and conducting LCA. The influence of background systems implies that future potential 

scenarios of how chemicals such as sodium hydroxide and hydrogen peroxide will be produced 

would help understand environmental impacts better.  

 

The data used for the LCA study were those of simulation results. In an actual industrial scale 

production, one would have accurate and better data which would give better results with less 

uncertainty. The high-water demand and dilution of chemicals would be much different in an 

actual plant thereby affecting the results of the LCA study. The energy recovered from black 

liquor should be able to meet steam demand and some electricity demand as seen in literature 

(González-García et al., 2011). The energy calculations for black liquor done in this study does 

not do so and this is a limitation that can affect environmental impacts. Moreover, the electricity 

used in a plant would be much larger than what was assumed thereby affecting results. It is also 

interesting to note that no by products were considered or modelled in this study. Most 

industries have by-products produced that are sold or used elsewhere. The environmental 

performance would also be affected in that case as the notorious issue of allocation would then 

have to be considered. The soda cooking method is only one process route that is studied. 

Further research should consider which process route is the best comparing kraft process and 

sulphite process. There is also research on other cooking methods that use organic solvents and 



 

30 | P a g e  
 

other alkaline compounds for pulping (Jahan et al., 2021). These could also be studied further 

in terms of their environmental impacts and performance. The process simulation is only at a 

preliminary stage and further optimization and improvements need to be studied which can also 

change the results presented here. One main issue in this system was the high use of water, 

which needs to be optimized. The recovery boiler too is a critical step in the entire process 

which needs further optimization. Operational issues such as build up of silica and its handling 

must be studied further.  

The results presented only tell where and how much environmental impacts are caused. 

Decisions on whether to produce dissolving pulp from wheat straw will depend of other 

economic factors and value judgements of different stakeholders involved. The need however 

is clear that if indeed a bioeconomy transition as forecasted occurs, then wood and forestry 

alone cannot meet these demands and hence other alternatives should be studied and further 

research still needs to be carried out.  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 



 

31 | P a g e  
 

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 Appendix A: Description of Impact Categories  
 
 

1. Abiotic Depletion Potential, non-fossil resources 

 

According to Van Oers et al. (2020) the abiotic depletion potential of resource is the ratio 

of annual production to the square of ultimate reserves, divided by the same for a reference 

element, which in most cases is antimony.  

 

2. Eutrophication Potential  

 

Eutrophication potential gives insight into how much nutrients released into the ecosystem 

can change its biological productivity. Most aquatic systems lack nutrients such as nitrogen 

and phosphorous. The release of these nutrients can cause micro-organisms to consume 

oxygen and lower levels of oxygen lead to loss of other species. Emissions of nitrogen 

oxides and phosphates contribute to this impact category mainly It is expressed usually in 

kg phosphate equivalent (Baumann & Tillman, 2004). 

 

3. Acidification Potential  

 

Acidification Potential shows what is the maximum possible acidification a substance can 

cause. It is measured as the ability of a substance to form H+ ions. Pollutants like sulphur 

dioxide, nitrogen oxides and ammonia have very high acidification potentials. These 

pollutants in the atmosphere can turn acidic and in turn affect soil and other water bodies 

when deposited by acid rain or fog for instance (Baumann & Tillman, 2004).  

 

4. Total use of renewable primary energy resources  

 

This indicator tells how much renewable energy is used within a system. The use of total 

primary energy resources according to the European standards EN15804 is a sum of 

renewable primary energy as carrier and renewable primary energy resources as material 

utilization (EPD International, n.d.).  

  

5. Total use of non – renewable primary energy resources 

 

This indicator tells how much non-renewable energy is used within a system. The use of 

total primary energy resources according to the European standards EN15804 is a sum of 

non-renewable primary energy as carrier and non-renewable primary energy resources as 

material utilization (EPD International, n.d.).   

  

6. Photochemical Oxidant Formation  

 

Pollutants like nitrogen oxides and hydrocarbons in the presence of sunlight form secondary 

pollutants known as photo oxidants.  These cause the formation of photochemical smog 

also knows as summer smog that can cause damage to human health and vegetation. Ozone 

is an important photo oxidant and the photochemical oxidant formation calculates how 

much ozone can be produced photo chemically by a substance (Baumann & Tillman, 2004). 



 

II | P a g e  
 

 

 

7. Climate Change, total  

 

This impact category studies the global warming potential of greenhouse gases. All green 

house gases have the ability to absorb infrared radiation and heat the atmosphere, known as 

radiative forcing. The global warming potential (GWP) of a substance is defined as the ratio 

of increase in infrared radiation by a substance to the increased infrared radiation of 1 kg of 

carbon dioxide. GWP is expressed in kg CO2 eq.  Apart from CO2 Gases such as methane, 

nitrogen oxides and Chlorofluorocarbons also contribute to global warming. The GWP can 

be calculated across different time horizons as different green house gases have varied life 

times in the atmosphere. The most common time span measured is GWP -100 years, which 

was also the basis for this study (Baumann & Tillman, 2004). 

 

8. Ozone Depletion 

 

Ozone Depletion potential is the change in stratospheric ozone in the steady-state due to 

emissions relative to that of CFC-11. The ozone layer is important as it prevents harmful 

ultraviolet radiation from the sun to enter the earth’s atmosphere. The presence of 

halogenated compounds due to emissions slowly start depleting the ozone layer, causing 

damage to human life and other animal species (Baumann & Tillman, 2004). 

 

9. Water Deprivation, Available Water Remaining (AWARE) method  

 

The water deprivation calculated by the AWARE method tells how much water is deprived 

in a region or ecosystem. It is calculated as the inverse of the difference between available 

water per area and the demand of water per area. The characterisation factor obtained can 

range from 0.1 -100. An important note in the results from GaBi software is that un 

regionalized flows have a world average characterization factor of 43, which is 

unrepresentative of Sweden. All such flows were multiplied with a Swedish 

Characterisation factor of 1.694 as per data provided by WULCA (2021).  

 

 

 

 

 

  



 

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Appendix B: Life Cycle Analysis of Benchmark 

– Dissolving Pulp from wood 
 

 

This section describes the LCA conducted for the benchmark. All data necessary were compiled 

from the environmental reports published by Domsjö Fabriker AB for the years 2019, 2020 and 

202 representative of a general pulping plant in Sweden (Fabriker, 2019, 2020, 2021). From the 

reports it was difficult to assess the electricity used in each of the years and data from  (Klugman 

et al., 2019)  was assumed to be the same throughout all the years.  

The functional unit was 1 tonne of dissolving pulp produced and the impact results can be easily 

compared to that of the pulp produced by wheat straw.  

 

Domsjö Fabriker Operations  

Domsjö Fabriker is a bio refinery located in Örnsköldsvik, Sweden which can produce up to 

255,000 tons of pulp. The refinery also produces by-products ethanol and lignin. Most of the 

cellulose is used for textile fibre production while lignin is exported. Ethanol is sold to SEKAB 

and is used in biofuels or to produce other chemicals. Raw material used in the refinery is spruce 

and pine wood. The process used to produce dissolving pulp is the sodium-based sulphite 

process where it is carried out in two stages to have minimum lignin in the pulp. The cooked 

pulp is then bleached in a two-stage bleaching process to produce dissolving pulp of 91% - 92% 

cellulose which is further dried and sent for storage. Meanwhile the black liquor produced from 

the cooking process and bleaching steps are ctollected evaporated and sent for production of 

ethanol. The collected process liquid also is used in two recovery boilers that produce high 

pressure steam which is used for meeting some of the electricity demand. The effluents from 

the boiler are sent for chemical recovery, thereby recycling sodium and sulphur. Part of the 

stream that is sent for ethanol production is diverted for lignin production as well where it is 

stored mostly as dry powder (Fabriker, 2021) 

 

Assumptions 

 

Assumptions made for modelling the system for the benchmark is given below –  

 

• No background processes existed for production of Sulphur Dioxide as raw material. 

The amount of Sulphur needed was calculated by stoichiometry and was added to total 

sulphur needed.  

• The density of softwood was taken as 420 kg/m3 fub (100% dry content)  

• Energy content for Heavy Fuel Oil was assumed to 40.4 MJ/kg and that of biomass 16 

MJ/kg.  

• Transport distance for raw m