modelling of wet air oxidation in a deep well reactor …

MODELLING OF WET AIR OXIDATION IN A DEEP WELL REACTOR FOR BIOMASS TREATMENT

TÂNIA CATARINA PINTO MOURA DISSERTAÇÃO DE MESTRADO APRESENTADA À FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO EM CHEMICAL ENGINEERING

M 2021

CLASSIFIED DOCUMENT. USE ONLY FOR EVALUATION PURPOSES (delete if not applicable)

Modelling of Wet Air Oxidation in a deep well reactor for biomass treatment

Master in Chemical Engineering


Master dissertation

of

Tânia Catarina Pinto Moura

Developed within the course of dissertation

held in

DMT Environmental Technology

Supervisor at FEUP: Prof. Ana Mafalda Ribeiro

Coordinator at DMT-ET: Eng. Jort Langerak

October 2021


Acknowledgment

I would like to thank DMT Environmental Technology for accepting me as an intern. Further, I

would like to thank biomass conversion group, Jort, Nadia, Mark, Yujun and Yuniki, for all

teamwork learning. Nadia, thank you for your help and your affection. I would like to thank

Gerrit for making sure that we were good accommodated in the Flecke.

I would like to thank Professor Ana Mafalda Ribeiro, for your time, dedication and

affection.

For the girls who were with me in The Netherlands, thank you for your company and

joy, Alexandra, Carina, Francisca, Mariana and Melanie.

My journey would not be the same without friends by my side, Raquel Claro Sousa,

Beatriz Carvalho and João ‘Bandeira’ Costa, thank you all for your support and your

friendship.

Finally, I would like to thank my family for the love and support, especially my

mother.


Abstract

Anaerobic digestion is a waste-to-energy technology that can be used towards a circular

economy. Biogas, a renewable energy, and digestate, a solid residue, are the products of AD.

Biogas yield can be enhanced by the applications of pre-treatments and post-treatment of

digestate.

Wet air oxidation (WAO) is a hydrothermal technology in which compounds are oxidize

in the liquid phase at high temperatures and high pressures. WAO is usually used as post-

treatment of AD, reducing chemical oxygen demand to form carbon dioxide. Since

intermediates products are produced in WAO process, namely acetic acid, it became

interesting to analyze application of WAO as post-treatment of the digestate and produce

more biogas from it. This way, WAO would produce acetic acid and this would be used by

methanogenic bacteria to produce biogas.

Hence, a deep well reactor buried in the ground with WAO process was modeled in

Aspen Plus V12. In this work, it was considered a first-order reactions in relation to the

concentration of substrate (glucose or acetic acid).

Firstly, the process flow diagram to model a plug flow reactor within concentric tubes

was chosen with particular emphasis on heat transfer throughout the reactor. In a simple

way, down flow and up flow streams are simulated as two blocks of reactor.

Moreover, heat transfer is influenced by the dimensions of the reactor. High length

and high diameters increase the heat exchange.

It was obtained a maximum production of acetic acid for a length of 700 m and a

diameter of 0.20.

In conclusion, WAO can be applied as a pre-treatment of biomass for production of an

intermediary product of AD, acetic acid. Furthermore, this process is energetically auto-

sufficient and the safety concerns related to high operational conditions are minimized by the

implementation of this process in a reactor buried in the ground.

Keywords (theme): Wet air oxidation; anaerobic digestion; acetic acid


Resumo

A digestão anaeróbia (DA) é uma tecnologia “waste-to-energy” que incentiva a uma economia

circular. Biogás, uma energia renovável, e um resíduo sólido, designado digestate, são os

productos obtidos da DA.

A oxidação por via húmida é uma tecnologia termal na qual os compostos são oxidados

numa fase líquida a temperaturas e pressões elevadas. Normalmente, esta tecnologia é usada

como pós-tratamento da DA, reduzindo a carga orgânica para formar dióxido de carbono.

Tendo em conta que produtos intermediários são produzidos na oxidação por via húmida, é

interessante analisar a sua aplicação como pós-tratamento do resíduo sólido obtido da DA

para produção de biogás a partir deste. Desta forma, pode-se produzir ácido acético que pode

ser usado na DA para produção de biogás através de bactérias metanogénicas.

Assim, foi modelado a oxidação por via húmida num reator vertical inserido no solo no

Aspen Plus V12. Neste trabalho, é considerado reações de primeira ordem em relação ao

substrato (glucose e ácido acético).

Em primeiro lugar, o diagrama de fluxo de processo para modelar um reator tipo

pistão em tubos concêntricos foi escolhido com a particular atenção na troca de calor

realizada ao longo do reator. De modo simples, as correntes de descida e de subida do reator

são simuladas em separado por blocos de reator.

Além disso, a transferência de calor é influenciada pelas dimensões do reator. O

aumento do comprimento e o aumento do diâmetro aumentam a troca de calor realizada.

Foi obtida uma produção máxima de ácido acético para o comprimento de reator de

700 m e diâmetro de 0.20 m.

Em conclusão, a oxidação por via húmida pode ser aplicada como pré-tratamento para

biomassa de forma a produzir um intermediário da DA, ácido acético. Além disso, é um

processo energeticamente auto-suficiente e as questões acerca da segurança relativas às altas

condições de operação são minimizadas pela inserção do reator dentro do solo.

Palavras-chave:: Oxidação por via húmida; digestão anaeróbia; ácido

acético


Declaration

I hereby declare, under word of honour, that this work is original and that all non-original

contributions is indicated and due reference is given to the author and source

20/09/2021


i

Index

1 Introduction ........................................................................................... 1

1.1 Framing and presentation of the work .................................................... 1

1.2 Presentation of DMT Environmental Technology ........................................ 2

1.3 Contribution of the author to the work ................................................... 2

1.4 Organization of the dissertation ............................................................ 2

2 Context and State of the Art ...................................................................... 4

2.1 Waste-to-energy technologies ............................................................... 4

2.2 Anaerobic digestion ........................................................................... 5

2.2.1 Livestock manure ...................................................................................... 5

2.2.2 Municipal solid waste .................................................................................. 6

2.2.3 Products ................................................................................................. 6

2.2.4 Biochemistry ............................................................................................ 7

2.3 Pre- and post-treatment ...................................................................... 7

2.4 Hydrothermal technologies .................................................................. 8

2.5 Wet Air Oxidation .............................................................................. 9

3 Methods: Computer Application Aspen Plus .................................................. 15

3.1 Process flow diagram ........................................................................ 15

3.2 Property thermodynamic model .......................................................... 18

3.3 Initial conditions ............................................................................. 19

4 Results and discussion ............................................................................ 21

4.1 Model assumptions and simplifications .................................................. 21

4.2 Process flow diagram ........................................................................ 21

4.3 Dimensions of the reactor .................................................................. 24

4.3.1 Length ................................................................................................. 24

4.3.2 Diameter .............................................................................................. 26

4.4 Composition and reaction kinetics ....................................................... 28

4.5 Air flowrate ................................................................................... 31


ii

4.6 Composition ................................................................................... 35

5 Conclusion ........................................................................................... 41

6 Assessment of the work done ................................................................... 43

6.1 Objectives Achieved ......................................................................... 43

6.2 Limitations and future ...................................................................... 43

6.3 Final Assessment ............................................................................. 43

7 References .......................................................................................... 45

Annex A - Manure treatment technologies ......................................................... 49

Annex B - MSW generation and management operations ........................................ 51

Annex C - Cow manure composition ................................................................. 53

Annex D - Mass transfer of oxygen ................................................................... 55

Annex E - WAO mechanism ............................................................................ 57

Annex F - Pressure correlation........................................................................ 58

Appendix A - Air flowrate .............................................................................. 60

Appendix B - Mass and energy balances ............................................................. 61

Appendix C - House of quality ......................................................................... 62


iii

List of Figures

Figure 1: Application of anaerobic digestion plant in a circular economy . .................................. 1

Figure 2: General process chain of anaerobic digestion. ........................................................ 2

Figure 3: Waste-to-energy technologies applied to municipal solid waste divided in different groups . 4

Figure 4: Livestock population in Europe between 2009 and 2013 . ........................................... 5

Figure 5: Overview of the metabolic pathway involved in AD process . ....................................... 7

Figure 6: Different configurations of pre-treatment or post-treatment with A: (a) pre-treatment

configuration; (b) post-treatment configuration with recirculation; (c) post-treatment in an inter-

stage configuration . .................................................................................................. 8

Figure 7: Typical configuration of (a) thermal hydrolysis and (b) wet air oxidation with AD process [6].

........................................................................................................................... 9

Figure 8: Sketch map of WAO reaction process. ................................................................ 10

Figure 9: Reactions involved in WAO considering glucose and acetic acid as initial component and

intermediate component, respectively. .......................................................................... 10

Figure 10: Diagram representing a deep well reactor with three concentric tubes: an inlet tube (1)-air

flow; a middle tube (2)-process downflow and an outlet tube (4)-process up-flow. ..................... 13

Figure 11: Process block diagram used as a base for process flow diagram in . ............................ 15

Figure 12: Process flow diagram in Aspen Plus with an heat exchanger and a reactor. .................. 15

Figure 13: Process flow diagram of a deep well reactor via wet air oxidation taking in account the

location of the injection of air . .................................................................................. 16

Figure 14: Oxygen solubility in water (a) at 100 bar for different temperatures and (b) at 90°C for

different pressures. ................................................................................................. 18

Figure 15: Temperature profile through the reactor for models A, B and C with different number of

blocks of reactors. ................................................................................................... 22

Figure 16: Evolution of pressure through the reactor for models A, B and C with different number of

blocks of reactor. .................................................................................................... 23

Figure 17: Evolution of vapor molar fraction of the up-flow stream for models A, B and C with

different number of blocks of reactor. ........................................................................... 23

Figure 18: Evolution of temperature for different lengths of the deep well reactor. .................... 24

Figure 19: Pressure variation for different length of deep well reactor. ................................... 25

Figure 20: Vapor molar variation for different lengths of deep well reactor. ............................. 26

Figure 21: Temperature profile for different diameters of a deep well reactor. ......................... 27


iv

Figure 22: Pressure variation for different diameters of deep well reactor. .............................. 27

Figure 23: Molar vapor fraction profiles for different diameters of deep well reactor. ................. 28

Figure 24: Variation of composition in a deep well reactor. .................................................. 29

Figure 25: Molar composition of acetic acid and carbon dioxide for different lengths of deep well

reactor. ................................................................................................................ 29

Figure 26: Reaction rates observed for the three reactions at different lengths of the deep well

reactor. ................................................................................................................ 30

Figure 27: Temperature profiles for different air flowrates. ................................................ 31

Figure 28: Variation of pressure for different air flowrates. ................................................. 32

Figure 29: Molar vapor fraction profiles for different air flow rates........................................ 33

Figure 30: Final composition of glucose, acetic acid and carbon dioxide for different air flowrates. . 34

Figure 31: Reaction rates of different reactions for various air flow rates. ............................... 34

Figure 32: Temperature evolution for different compositions of the process stream. ................... 36

Figure 33: Pressure profiles for 1000 m of length and 0.20 of diameter for different compositions of

the process stream. ................................................................................................. 36

Figure 34: Molar vapor fraction profiles for 1000 m of length and 0.20 of diameter for different

compositions of the process stream. .............................................................................. 37

Figure 35: Evolution of composition for case 2.................................................................. 38

Figure 36: Evolution of composition for case 3.................................................................. 38

Figure 37: Reaction rates of the three cases with different compositions of the process stream. ..... 39


v

List of Tables

Table 1: Kinetic parameters values for the WAO reactions . ................................................. 11

Table 2: Operational conditions for simulation of a deep well reactor with WAO. ....................... 17

Table 3: Process flow diagrams applied. ......................................................................... 17

Table 4: Initial conditions made for simulation of WAO in a deep well reactor. .......................... 20

Table 5: Conditions of cases with different compositions of process stream. ............................. 35


vii

Notation and Glossary

𝐴 Area m2

𝑐𝑝 Calorific capacity J·kg-1·K-1

𝑑 Diameter m 𝐸 Activation energy kJ·mol-1

𝐹 Flowrate kg·h-1

𝐻 Enthalpy J·kg-1

𝑘 Pre-exponential s-1

𝐿 Length m

𝑀 Molecular weight g·mol-1

𝑚 Exponent rate -

𝑛 Exponent rate - 𝑃 Pressure MPa

𝑄 Heat W 𝑟 Reaction rate kmol·m-3·s-1

𝑇 Temperature K Δ𝑇 Temperature variation K

𝑡 Time s 𝑈 Heat transfer coefficient W·K-1·m-2

𝑥 Molar fraction mol·mol-1

𝑥′ Mass fraction kg·kg-1

Greek Letters

𝜌 density kg·m-3

Indexes

𝑐 Critical 𝑐𝑖 Cold stream, inlet

𝑐𝑜 Cold stream, outlet 𝑓 flow

ℎ𝑖 Hot stream, inlet ℎ𝑜 Hot stream, outlet

𝑙𝑚 Logarithmic mean 𝑟 Relative

List of Acronyms

AD Anaerobic digestion COD Chemical oxygen demand DS Dry solids ET Environmental Technology EU European Union GHG Greenhouse gas MSW Municipal solid waste OECD Organization for Economic Cooperation and Development RDF Refuse derived fuel THP Thermal hydrolysis process TOC Total organic carbon WAO Wet air oxidation WtE Waste-to-energy


viii

Modelling of Wet Air Oxidation in a Deep Well Reactor for Biomass Treatment

Introduction 1

1 Introduction

1.1 Framing and presentation of the work

Bioenergy is a renewable energy that uses biomass to produce energy. Biomass can be sewage

sludge, manure, municipal solid waste, agriculture, forest residues, energy crops and others

[1,2]. The major concerns of bioenergy are biomass availability, sustainability issues and

competition between the alternative uses of biomass (for instance, competition for feed and

food). Hence, the use of waste streams may contribute for an improvement of bioenergy

production. Moreover, the use of waste for production of energy contributes for a circular

economy that, in turn, is a European Union’s plan for reduction of waste generation and

reduction of the use of resources [2,3].

Among waste-to-energy (WtE) technologies, anaerobic digestion (AD) has been

explored for bioenergy production from waste stream containing organic compounds,

contributing for a circular economy (Figure 1) [3]. Anaerobic digestion (AD) is a bioenergy

technology in which biogas and digestate are produced from organic matter by

microorganisms in the absence of oxygen [4].

Figure 1: Application of anaerobic digestion plant in a circular economy [5].

The anaerobic digestion process can be divided generally, as illustrated in Figure 2, in

different steps: pre-treatment, digester and post-treatment. Wet air oxidation (WAO) is a

hydrothermal technology used usually as a post-treatment in order to reduce chemical oxygen

demand (COD) of the digestate [6].


Introduction 2

Figure 2: General process chain of anaerobic digestion.

In this report, it will be study if WAO can be applied as pre-treatment and as post-

treatment of digestate that would be feed to another digestate to enhance biogas yield.

1.2 Presentation of DMT Environmental Technology

DMT Environmental Technology (ET) was founded in 1987, in the Netherlands, by Rob Dirkse.

DMT’s logan “Value Your Waste” represents the purpose of DMT. DMT-ET offer services and

products that aim to contribute to a better circular economy [7]. DMT Environmental

Technology provides TurboTec®, product that is based on thermal hydrolysis process (THP), as

a treatment for anaerobic digestion plants. It allows to enhance the biogas yield, enhance the

quality of the digestate for agricultural applications and reduce the sludge volumes from

biomass [8].

1.3 Contribution of the author to the work

Process flow diagram, property thermodynamic model and kinetic data were founded in the

literature. My work was to apply these information for a situation more approximated for the

feedstock within the scope of this work and study the effect of different parameters. My side

work was an analysis of current management of manure and municipal solid waste.

1.4 Organization of the dissertation

This report is divided into five main sections. In Section 1, it is present the framework of this

report. In Section2, it presents manure and municipal solid waste feedstocks and a review of

AD. Moreover, it presents how WAO can have a role in AD process. In Section 3, it is present

the methodology used in this report, namely process flow diagram and initial conditions for

WAO simulation. In Section 4, results are divided into sub-sections. It is analyzed the effects

of different parameters on the WAO products. In Section 5, main conclusions are summarized.


Context and State of Art 4

2 Context and State of the Art

2.1 Waste-to-energy technologies

“Waste-to-energy process can play a role in the transition to a circular economy provided that

the EU waste hierarchy is used as a guiding principle and that choices made do not prevent

higher levels of prevention, reuse and recycling” [3].

WtE technologies can be divided into three groups based on the conversion process:

thermochemical, physicochemical and biochemical [3]. Thermochemical conversions are

combustion, gasification, pyrolysis, torrefaction, refuse derived fuel (RDF), liquefaction, and

carbonization. Physicochemical conversion technology is transesterification. Finally,

anaerobic digestion and fermentation are technologies of biochemical conversion [3,9].

Figure 3: Waste-to-energy technologies applied to municipal solid waste divided in different

groups [3].



2.2 Anaerobic digestion

Anaerobic digestion (AD) is a technology used worldwide to produce bioenergy and a treated

organic waste, named digestate. In 2016, Europe has 17,662 AD plants and agricultural

substrates, sewage sludge and landfill waste were the main feedstocks used [10].

2.2.1 Livestock manure

Manure is a mixture of animal excreta, bedding, washing water and other material generated

by manure management [12]. Generally, manure contains nitrogen, phosphorus, potassium,

organic matter and other components [13].

Annual livestock manure production is about 1,400 million tonnes in Europe [11].

Figure 4 represents average population of livestock in thousands of heads in Europe between

2009 and 2013 [14].

Figure 4: Livestock population in Europe between 2009 and 2013 [14].

For centuries, manure has been applied as soil conditioner/fertilizer for the

enhancement of the land quality. However, improper management of manure and its overuse

cause negative consequences, such as emissions of greenhouse gas (GHG) and eutrophication

[11]. As a matter of fact, the pollution cost caused by ammonia and GHG emissions into the

atmospheres and the nitrogen present in the rivers in Europe is about 12,800 million €/year

[13].

Regulations have been established to control manure management towards a

minimization of environmental impacts. EU Nitrate Directive (maximum application rate 170

kg-N/ha/year) and EU Water Framework Directive (quality of surface water) are some

examples of EU legislation [15].



All treatments applied in manure management are in Annex A. The selection of a

technology or combination of technologies depends upon the geographical location, policies,

incentives provided, market of an end product and nutrients balance of the farm. The most

relevant treatments applied to the manure are composting, solid-liquid separation and

anaerobic digestion [11,15].

2.2.2 Municipal solid waste

According to European Statistical Office (Eurostat) and the Organisation for Economic Co-

operation and Development (OECD), municipal solid waste (MSW) is defined as “mixed waste

and separately collected waste from households including: paper and cardboard, glass metals,

plastics, bio-waste, wood, textiles, waste electrical and electronic equipment, waste

batteries and accumulators; bulky waste, including white goods, mattresses, furniture;

garden waste, including leaves, grass clipping” or as “mixed waste and separately collected

waste from other sources that is comparable to household waste in nature, composition and

quantity”. Bio-waste, in turn, is defined as “biodegradable garden and park waste, food and

kitchen waste from households, restaurants, caterers and retail premises, comparable waste

from food processing plants and other waste with similar biodegradability properties that is

comparable in nature, composition and quantity” [2].

MSW generated in 2019 was 224.5 million tonnes in the EU [16]. Majority of MSW

generated is biowaste (Annex B). Furthermore, MSW composition varies from country to

country, over the year, as well as MSW generation that is also correlated with economical

status, popularization and industrialization growth [2, 17].

Municipal waste treatments are recycling, composting/digestion, landfilling and

incineration with or without energy recovery. Recycling (including anaerobic digestion) is the

most applied treatment, followed by incineration, landfilling and composting (includes

fermentation) [2].

2.2.3 Products

Products obtained from AD process are biogas and a digestate, or organic waste. Usually,

approximately 85% of the feedstock volume results in digestate. Digestate, in turn, consists of

10 to 20 wt% of solid and 80 to 90 wt% of liquid [10].

Digestate consists of undigested material and microbial biomass. On the other hand,

biogas is mainly constituted by methane (50 – 75%) and carbon dioxide (25 – 50%), but other

components can be found in biogas in minor quantities, such as nitrogen, hydrogen, ammonia

and hydrogen sulphide. Biogas calorific value is around 6.0 – 6.5 kWh/m3, but this value

depends on the percentage of methane [10].



Biogas is applied for heat and electricity generation, also named combined heat and

power (CHP). Further, it can be upgraded to biomethane, that, in turn, can be used as a

transportation fuel and an alternative to natural gas [18]. The total biogas production

worldwide was 91,819 GWh, in 2019. In Europe, Germany is the main country in biogas

production [14].

Digestate can be used as a fertilizer, used for production of carbon-based materials

(for example, biochar and nanomaterials), used as a feedstock of another digester to recover

residual methane, used for nutrient recovery (nitrogen and phosphorus), among other

applications [10].

2.2.4 Biochemistry

AD process consists of a breakdown of organic compounds into methane and carbon dioxide,

final products of a four consecutive stages named hydrolysis, acidogenesis, acetogenesis and

methanogenesis.

Firstly, organic polymers – carbohydrates, lipids and proteins – are hydrolysed to

soluble oligomers and monomers by the action of extracellular enzymes of fermentative

bacteria. Secondly, products of the previous step are transformed into short-chain fatty

acids, i.e., lower than 6 carbons), acetate, alcohols, hydrogen and carbon dioxide –

acidogenesis. Thirdly, acetogenic bacteria oxidize short-chain fatty acids with more carbons

than acetate and alcohols, producing acetate, formate, hydrogen and carbon dioxide.

Fourthly and finally, the previously referred compounds are converted into methane and

carbon dioxide by methanogenic bacteria, which are strictly anaerobic [19].

Figure 5: Overview of the metabolic pathway involved in AD process [19].

2.3 Pre- and post-treatment

Either hydrolysis or methanogenesis may be a rate-limiting stage of AD, depending on the

substrate. When substrate has a more complex structure, hydrolysis is the limiting step,

whilst when substrate is easily broken down, methanogenesis becomes the rate-limiting stage

[20].



Hence, pre-treatments are applied to prepare substrates for the microorganism and,

as consequence, increase biogas yield. On the other hand, post-treatment can be applied to

digestate before its disposal, for instance, to fulfil legal requirements. Furthermore, post-

treatment can be applied to explore potential biogas production from digestate,

characterized by complex composition, increasing hence hydrolysis step. Figure 6 represents

different configurations that be found of AD process [21,22].

Figure 6: Different configurations of pre-treatment or post-treatment with A: (a) pre-

treatment configuration; (b) post-treatment configuration with recirculation; (c) post-

treatment in an inter-stage configuration [21].

Treatments applied may be chemical, biological, physical or a combination of them.

Chemical treatments involve the addition of chemical compounds, such as an alkaline or acid.

Biological treatments involve the addition of microorganisms or enzymes. Finally, physical

treatments can be divided into mechanical treatment and thermal treatment. Both aim to

break cells by physical forces or by elevated temperatures, respectively [20].

2.4 Hydrothermal technologies

The hydrothermal technologies are one type of technologies in which reactions happen in the

aqueous solvent at elevated temperatures and pressures. The hydrothermal technologies can

be divided into oxidative and non-oxidative hydrothermal technologies. With these

technologies it is possible to enhance AD process, to degrade and to remove organic

compounds, to reduce waste mass and volume and to recover valuable compounds [6].



Water presence is essential because it act as a solvent as well as, at high

temperatures and high pressure, water has a high reactivity and, consequently, breaks

chemical bonds in complex molecules to convert them into simpler compounds [6].

Thermal hydrolysis (TH) and WAO are both hydrothermal technologies with some

differences. TH is a non-oxidative hydrothermal technology, whilst WAO is an oxidative

hydrothermal technology. In addition to an oxidizing agent, chemicals and catalysts can be

involved in hydrothermal technologies. Besides, it is necessary to input energy in TH process,

whilst WAO is auto-thermal due to the exothermic reactions. Finally, another difference

between TH and WAO is that TH is used usually as pre-treatment of AD, while WAO is used as

AD post-treatment as illustrated in Figure 7 [6].

Figure 7: Typical configuration of (a) thermal hydrolysis and (b) wet air oxidation with AD

process [6].

2.5 Wet Air Oxidation

Wet oxidation or wet air oxidation (WAO) is a process in which compounds, either suspended

or dissolved, are oxidize in liquid phase at high temperatures (400 – 573 K) and high pressures

(0.5 – 20 MPa) with an oxidizing agent, oxygen that is present in air [23].

WAO is a technique used in wastewater process treatment, as an alternative to

incineration and biological and chemical treatments, to reduce organic and inorganic content

present in order to have the requirements needed to be discharged.



Zimmerman developed WAO process and its first industrial applications. First

applications of WAO were production of artificial vanilla flavouring and destruction of paper-

mill sludge and biological sludge. Nowadays, WAO is used for treatment of industrial wastes

(caustic solution), treatment of powdered activated carbon, production of useful products,

production of biofuel from microalgae and synthesis of methyl methacrylate [25].

By WAO, organic carbon compounds are converted to carbon dioxide and water,

organic nitrogen compounds to ammonia and nitrous compounds, sulphur compounds to

sulfuric acid or sulphates, phosphorous compounds to phosphates and chlorine compounds to

hydrochloric acid [24].

𝐶𝑚𝐻𝑛𝑂𝑘𝐶𝑙𝑤𝑁𝑥𝑆𝑦𝑃𝑧 + (𝑚 + 0.25(𝑛 − 3𝑥) − 0.5𝑘 + 2(𝑦 + 𝑧))𝑂2

→ 𝑚𝐶𝑂2 + 0.5(𝑛 − 3𝑥)𝐻2𝑂 + 𝑥𝑁𝐻3 + 𝑤𝐶𝑙− + 𝑦𝑆𝑂42− + 𝑧𝑃𝑂4

3− + ℎ𝑒𝑎𝑡 (2.1)

Reaction mechanism of WAO is a free radical mechanism, and overall process can be

found in Annex E.

Simplifying, WAO reaction can be understood as two pathways as illustrated in Figure

8. A direct pathway occurs when initial and relatively unstable compounds, indicated as A, is

oxidized directly to its final products – carbon dioxide and water, represented as C. Besides a

direct pathway, refractory intermediate products are also formed. Usually, acetic acid is

representative of intermediates compounds [26].

Figure 8: Sketch map of WAO reaction process.

In this report, glucose is considered as representative of group A and acetic acid

representing group B (Figure 9).

Figure 9: Reactions involved in WAO considering glucose and acetic acid as initial component

and intermediate component, respectively.



A global rate equation for each compound represented in Figure 9 can be expressed as

Eq. (15), assuming no volume change.

−𝑑[𝐴]

𝑑𝑡= 𝑘𝑜𝑒𝑥𝑝 (−

𝐸

𝑅𝑇) [𝐴]𝑚[𝑂2]𝑛 (2.2)

where 𝑘𝑜 is the frequency or pre-exponential factor, 𝐸 is the activation energy, 𝑅 is

ideal gas constant (8.3145 J/(mol·K)), 𝑇 is the temperature, 𝑚 and 𝑛 are the reaction order

with respect of component A and oxygen, respectively.

Global rate of WAO depends on the final product formation rate as well as the

formation and destruction rates of stable intermediates. Therefore, kinetic data was found in

the literature for glucose oxidation to carbon dioxide and acetic acid. This data, represented

in Table 1, considered first-order reactions with respect to glucose, not taking into account

the concentration of oxygen [27].

Table 1: Kinetic parameters values for the WAO reactions [27].

# Reaction 𝒌𝒐 (s-1) 𝑬

(kJ/mol)

1 C6H12O6 + 6O2 → 6H2O + 6CO2 71.52 28.4

2 C6H12O6 + 2O2 → 2CH3COOH + 2CO2 + 2H2O 0.811 12.3

3 CH3COOH + 2O2 → 2H2O + 2CO2 1211.97 54.4

Hence, for each reaction, the global reaction rate for glucose oxidation can be

expressed similarly to Eq. (2.2) with 𝑛 equal to zero. Since glucose reacts with oxygen in two

different reactions, reaction #1 and #2, Eq. (2.3) is a sum of two terms, each one

corresponding to each reaction.

−𝑑[𝐶6𝐻12𝑂6]

𝑑𝑡= 𝑘1

0 ∙ 𝑒−𝐸1 𝑅𝑇⁄ ∙ [𝐶6𝐻12𝑂6] + 𝑘20 ∙ 𝑒−𝐸2 𝑅𝑇⁄ ∙ [𝐶6𝐻12𝑂6] (2.3)

A similar equation is used to express the variation of acetic acid, Eq. (2.4). In this

case, acetic acid is formed from glucose and reacts to form carbon dioxide and water.

−𝑑[𝐶𝐻3𝐶𝑂𝑂𝐻]

𝑑𝑡= 𝑘3

0 ∙ 𝑒−𝐸3 𝑅𝑇⁄ ∙ [𝐶𝐻3𝐶𝑂𝑂𝐻] − 𝑘20 ∙ 𝑒−𝐸2 𝑅𝑇⁄ ∙ [𝐶6𝐻12𝑂6] (2.4)

Considering concentration of each compound, glucose and acetic acid, at time 0 s,

corresponding to [𝐶6𝐻12𝑂6]0 and [𝐶𝐻3𝐶𝑂𝑂𝐻]0, it is possible to obtain the following equations:

[𝐶6𝐻12𝑂6] = [𝐶6𝐻12𝑂6]0 ∙ 𝑒−(𝑘1+𝑘2)∙𝑡 (2.5)



[𝐶𝐻3𝐶𝑂𝑂𝐻] = [𝐶𝐻3𝐶𝑂𝑂𝐻]0 ∙ 𝑒−𝑘3𝑡 +𝑘2 ∙ [𝐶6𝐻12𝑂6]0

𝑘1 + 𝑘2 − 𝑘3[𝑒−𝑘3𝑡 − 𝑒−(𝑘1+𝑘2)∙𝑡] (2.6)

The sum of glucose (A) and acetic acid (B) may represent overall organic matter, such

as , for instance, chemical oxygen demand (COD) or total organic carbon (TOC).

The mass transfer of oxygen is also an important factor for overall process yield. Since

oxygen concentration is not considered in kinetic, this is not considered (Annex D).

WAO process can be found applied to two different types of reactors: plug flow

reactor or bubble column. In this report, it is studied a vertical plug flow reactor buried in

the ground, i.e., a deep well reactor, with plug flow reactor, with concentric tubes. This

configuration allows to pre-heat inlet stream with heat transfer of outlet stream and safety

concerns related to the high temperature and high pressure are minimized. On the other

hand, problems of this configuration are the sedimentation of solids at the bottom of the

reactor and problems of scaling have been reported [23,24].

A deep well reactor buried in the ground works as a plug flow reactor with concentric

tubes as illustrating in Figure 10, where 1 represents the inlet of air flow (intern tube) and 2

the inlet of the process stream (middle tube); 3 is the reaction zone of the reactor where

both streams – air stream and the process flow, containing the oxidizable compounds – meet

and, then the combustion reaction occurs, being 4 the outlet stream (outside tube)

containing the products. Process stream, in this report, is a general name adapted for a

stream to be treated.



Figure 10: Diagram representing a deep well reactor with three concentric tubes: an inlet

tube (1)-air flow; a middle tube (2)-process downflow and an outlet tube (4)-process up-

flow.

Process stream has two types of flow: first it has a down flow and then it has an up-

flow. This configuration allows that the up-flow steam with a higher temperature exchanges

heat with down-flow stream that has a lower temperature. In fact, the reactions that occur

at the bottom of the reactor are combustion reactions which release energy (exothermic

reactions) and, consequently, increase the temperature of the stream. Hence, this process

has as advantage feature the fact of being self-sufficient energetically, since the heat of

reaction is used to pre-heat the stream.

Analyzing heat transfer through the reactor, a double-pipe heat exchanger approach is

used to study how the dimensions of the reactor can affect the efficiency of heat exchanger.

Since it occurs a heat transfer between a down-flow stream and an up-flow stream, equations

for double-pipe type heat exchanger must be considered between them. Three equations are

important. One is the relation between the heat transferred between the fluids and the

overall heat transfer coefficient 𝑈, as follows:

𝑄 = 𝑈𝐴(∆𝑇)𝑙𝑚 (2.7)

where 𝑄 is the heat transferred, 𝑈 is the overall heat transfer coefficient, 𝐴 is the

area of contact between the two fluids and, finally, (∆𝑇)𝑙𝑚 is the log mean temperature

difference. This last term, “logarithmic mean” temperature, can be expressed as for counter-

current flow as in Eq.(2.8).



(∆𝑇)𝑙𝑚 =(𝑇ℎ𝑖 − 𝑇𝑐𝑜) − (𝑇ℎ𝑜 − 𝑇𝑐𝑖)

𝑙𝑛 (𝑇ℎ𝑖 − 𝑇𝑐𝑜𝑇ℎ𝑜 − 𝑇𝑐𝑖

) (2.8)

where 𝑇ℎ𝑖 is the inlet hot fluid temperature, 𝑇ℎ𝑜 is the outlet hot fluid temperature, 𝑇𝑐𝑖 is the

inlet cold fluid temperature and 𝑇𝑐𝑜 is the outlet cold fluid temperature.

To complete the analysis of Eq.(2.7), the contact between the two thermal fluids can be

expressed as a function of inner surface, 𝐴𝑖 , where 𝑟𝑖 is the radius of the inner surface and 𝐿

is the length of the tube.

𝐴𝑖𝑛 = 2𝜋𝑟𝑖𝑛𝐿 (2.9)

Besides Eq. (2.7, transfer of heat between two fluids can be expressed as the heat leaving the

hot fluid and, on the other hand, the heat gained by the cold fluid, considering that all

transferred occurs between the two fluids and therefore no heat is lost for the surrounding

environment. According to Eqs. (2.10) and (2.11), heat transferred can be expressed as

function of mass flowrate (�̇�ℎ and �̇�𝑐) and the calorific capacities of the streams (𝑐𝑝ℎ and

𝑐𝑝𝑐).

𝑄 = �̇�ℎ𝑐𝑝ℎ(𝑇ℎ𝑖 − 𝑇ℎ𝑜) (2.10)

𝑄 = �̇�𝑐𝑐𝑝𝑐(𝑇𝑐𝑜 − 𝑇𝑐𝑖) (2.11)


Methods: Computer Application Aspen Plus 15

3 Methods: Computer Application Aspen Plus

In this report, a deep well reaction via wet air oxidation was modelled in Aspen Plus V12.

Aspen Plus is an informatic tool used for model steady-state processes in chemical

engineering.

3.1 Process flow diagram

A previous study represented a deep well reactor, as illustrated in Figure 11, where a deep

well reactor is simulated as sum of heat exchanger and a reactor.

Figure 11: Process block diagram used as a base for process flow diagram in [27].

Figure 12: Process flow diagram in Aspen Plus with an heat exchanger and a reactor.

This model is based on the fact that the deep well reactor can be divided into two

separate operations: a heat exchanger and a reactor. Firstly, heat exchanger between the

cold stream before enter the reactor occurs and then reaction takes place in reactor with the

presence of the oxidising agent. Finally, outlet stream with higher temperature due to the

exothermic reactions and enter the heat exchanger. Although this approach represents simply

a deep well reactor with WAO reactions in terms of the processes that occur, it misses the



local heat transfer through the reactor. Therefore, another approach rises to overcome this

disadvantage.

A second method is based also on a heat exchanger and a reactor, but in this case, the

heat transfer occurs in reactor itself (Figure 13). Hence, deep well reactor can be divided in

different fractions in order to better simulate a local heat transfer between those fractions.

Figure 13 illustrates the case of a deep well reactor divided in 4 stages, at left, it is

represented the down flow stream and at right the up-flow stream. For instance, in a case of

a reactor length of 1000 m, each reactor represented at left is 250 m length, similar to the

reactor on the right side.

Figure 13: Process flow diagram of a deep well reactor via wet air oxidation taking in

account the location of the injection of air [27].

In this work, simulations were made based on this second approach. It is important to

note that in this work all heat exchange is between the inlet stream and outlet stream and,

hence, no cooling water or other type of stream had been considered. For this case, another

approach should be analysed.

Table 2 represents the initial conditions for the reactor and for heat transfer, while

Table 3 represents the PFDs used on this report. It is assumed that the reactor is made of

steel and, hence, the value of U is the value for steel.



Table 2: Operational conditions for simulation of a deep well reactor with WAO.

Category Operational condition

Reactor 𝐿: 1000 m

𝑑: 0.20 m

𝑈: 25 W/m2·K

Table 3: Process flow diagrams applied.

Model Process flow diagram

Model A

Model B



Model C

3.2 Property thermodynamic model

Predictive Soave-Reddlich-Kwong (PSRK) method was used in literature to model a similar

process – Gravity Pressure Vessel via Wet Air Oxidation - in Aspen Plus, since this model is

able to estimate the solubility of oxygen in water at high temperatures and at high pressures

more similar to the experimental data as is possible to see in Figure 14. Hence, PSRK was

chosen as a property thermodynamical model to simulate deep well reactor via WAO.

Figure 14: Oxygen solubility in water (a) at 100 bar for different temperatures and (b) at

90°C for different pressures.



The PSRK equation of state is an extension of the Redlich-Kwong-Soave (SRK) equation

of state and it is suitable for high pressure and high temperature conditions. PSRK model use

the UNIFAC model and mixing rules are the predictive Holderbaum rules [27].

Following equations are the equations of PSRK method, where 𝑝 is the pressure, 𝑅 is

the constant universal of gas, 𝑉𝑚 is the molar volume, 𝑇𝑐 critical temperature, 𝑃𝑐 critical

pressure and 𝑇𝑟 relative temperature.

𝑝 =𝑅𝑇

(𝑉𝑚 − 𝑏)−

𝑎(𝑇)

𝑉𝑚(𝑉𝑚 + 𝑏)

(3.1)

𝑎𝑖 = 0.42748𝑅2𝑇𝑐

2

𝑃𝑐𝛼(𝑇)

(3.2)

𝑏𝑖 = 0.08664𝑅𝑇𝑐

𝑃𝑐

(3.3)

𝛼(𝑇) = [1 + 𝑐1(1 + 𝑇𝑟0.5) + 𝑐2(1 − 𝑇𝑟

0.5)2 + 𝑐3(1 − 𝑇𝑟0.5)3]2 (3.4)

3.3 Initial conditions

Composition of the process stream is based on the composition of the cow manure that is

illustrated in Annex B.

Flowrate of the process stream is about 14600 tonDS/year (DS: dry solids) and,

considering a moisture content of 85% and 8000 h of working hours per year, about 12.2 ton

per hour is the operational flowrate of the process stream.

Furthermore, relation between glucose and acetic acid is based on the composition in

Annex x. It is considered for an approximation that mass fraction of glucose is double of mass

fraction of the acetic acid. In terms of molar fractions,

For complete oxidation of glucose, stoichiometric oxygen is 6 mol of oxygen for 1 mol

of glucose (Table 1). Hence, stoichiometric oxygen is approximately 1.07 kg of oxygen for 1 kg

of oxygen. Taking in account that only 10% of the total mass flowrate is glucose and air

stream has about 21% of oxygen, an air flowrate of 6216 kg/h is necessary to completely

oxidize the glucose. Table 4 represents the initial operating conditions for modelling of a

deep well reactor via wet air oxidation of a cow manure stream.



Table 4: Initial conditions made for simulation of WAO in a deep well reactor.

Category Operational condition

Process stream

𝐹 (kg/h) 12,200

𝑇 (K) 293.15

𝑃 (MPa) 0.5

𝑥′𝑤𝑎𝑡𝑒𝑟 0.85

𝑥′𝑔𝑙𝑢𝑐𝑜𝑠𝑒 0.10

𝑥′𝑎𝑐𝑒𝑡𝑖𝑐 𝑎𝑐𝑖𝑑 0.05

Air stream

𝐹 (kg/h) 6216

𝑇 (K) 473.15

𝑃 (MPa) 15

𝑥′𝑜𝑥𝑦𝑔𝑒𝑛 0.21

𝑥′𝑛𝑖𝑡𝑟𝑜𝑔𝑒𝑛 0.79


Results and discussion 21

4 Results and discussion

In this section, it is summarized the results in terms of temperature, pressure, molar vapor

fraction and composition with the following parameters, namely PFD, reactor dimensions, air

flowrate and composition.

4.1 Model assumptions and simplifications

Assumptions made on this report are the following: Beggs-Brill correlation for pressure

variation of the process stream and no heat lost to the surrounding environment.

Furthermore, it is important to note that all simulations were made based on the

temperature of thermal fluid, minimizing the temperature difference between blocks of

reactor by an interactive process. Therefore, process simulating is based on temperature

evolution of the thermal fluid in the block “RPlug”. Finally, using block “RPlug”, pressure

drop correlation is used for process stream, but it is not calculated for thermal fluid.

4.2 Process flow diagram

In this section, it was studied different models, Model A, B and C, illustrated in Table 3. The

main results analyzed in this report are: temperature, pressure and molar vapor fraction

profiles. These parameters are important for this section, since the goal is to compare the

effect of the number of reactors has in the simulation result.

Hence, Figure 15 presents the evolution of temperature and it is possible to verify

that, due to the process simulation, for the same operation and initial conditions,

temperature profiles are similar independently of the number of reactors. Hence,

temperature profile is not a good option for comparing models A, B and C.

Dimensionless reactor length, x-axis, is the distance of the process stream from its

input until its output. The graphic between position 0.0 and 0.5 represents down flow stream;

at position 0.5, it occurs the mixture of the process stream and air stream and, at this

position, reactions occur. From 0.5 to 1.0, up flow stream is represented in the graphic.



Figure 15: Temperature profile through the reactor for models A, B and C with different

number of blocks of reactors.

Secondly, pressure profile for different models is represented in Figure 16. It is

verified a pressure variation in ladder for Model B and Model C. For Model C, this shape is

more notable, indicating that with higher number of reactors, pressure profile approximates

better real and continuous result. However, due to the complexity of the interactive process,

in the next sections, model A was used to simulate.

Zones in which no pressure variation occurs are the zones where the process stream is

thermal fluid in the block “RPlug” in Aspen Plus V12. Therefore, higher number of blocks

reduce these zones which is a limitation of this model to get a continuous variation of

pressure.

290

340

390

440

490

540

590

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

T(K

)

Dimensionless reactor length

Model A Model B Model C



Figure 16: Evolution of pressure through the reactor for models A, B and C with different

number of blocks of reactor.

Furthermore, the outlet pressure is higher than the inlet pressure. In Figure 17, the

vapor molar fraction profile is represented.

Figure 17: Evolution of vapor molar fraction of the up-flow stream for models A, B and C

with different number of blocks of reactor.

It is possible to verify that high values for the vapor molar fraction, around 0.9, are

achieved. Hence, the fact that the outlet pressure is higher than the inlet pressure can be

explained by the principles of the hydrostatic pressure, i.e., that pressure variation depends

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

P(M

Pa)



0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.4 0.5 0.6 0.7 0.8 0.9 1.0

Mola

r vapor

fracti

on





upon the density of the fluid and the density of the gases is lower than the density of the

liquids.

4.3 Dimensions of the reactor

In this section, it will be analyzed the effect of the dimensions of the reactor. The reactor is

a double-pipe with concentric tubes and hence the dimensions to be considered are the

length and the diameter of the reactor.

4.3.1 Length

The length of the reactor has an effect on the heat transfer between the down-flow stream

and up-flow stream. Figure 18 represents temperature profiles for different lengths: 500 m,

600 m, 700 m, 800 m, 900 m, 1000 m, 1100 m, 1200 m, 1300 m, 1400 m and finally 1500 m.

Figure 18: Evolution of temperature for different lengths of the deep well reactor.

The temperature profiles obtained are similar to the profile obtained in Figure 15. In

both figures, it is observed an increase in temperature sharper than the temperature

decreasing of the up-flow stream. From Eqs. (2.10) and (2.11), product of mass flowrate and

heat capacity is higher for up flow stream than for down flow stream.

Furthermore, a decrease of temperature occurs at position 0.5, where the mixture of

the liquid stream and air happens. This decrease can be explained by the mixture of liquid

phase and gas phase and because of the dissolution of oxygen in water is an endothermic

reaction. In Section 4.5, the air flowrate is changed to study this feature.

290

340

390

440

490

540

590

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

T (

K)


500 m 600 m 700 m 800 m 900 m 1000 m

1100 m 1200 m 1300 m 1400 m 1500 m



Finally, for higher length of reactor, higher temperatures are achieved. From Eq.

(2.9), the heat transfer area increases and, as a consequence, the temperature achieved is

higher.

Figure 19 represents the variation of pressure for different reactor lengths. The final

pressure increases with the length of the reactor. Similarly to the observations made in

Section 4.2, the pressure at the bottom of the reactor, position 0.50 in x axis, is higher and,

hence, the pressure of the outlet stream is also higher.

Figure 19: Pressure variation for different length of deep well reactor.

Finally, the vapor molar fraction profile is illustrated in Figure 16. It is verified that

for higher lengths of deep well reactor, the vapor molar fraction becomes higher.

0.0

2.0

4.0

6.0

8.0

10.0

12.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

P (

MPa)


500 m 600 m 700 m 800 m 900 m 1000 m

1100 m 1200 m 1300 m 1400 m 1500 m



Figure 20: Vapor molar variation for different lengths of deep well reactor.

4.3.2 Diameter

The diameter is also a dimension of the deep well reactor that can vary, and it has an impact

on the process heat transfer and it is evaluated in this section.

Firstly, the temperature profile for the different lengths of the reactor varies sharply

on the down flow stream, while for the up flow stream it does not change significantly. For

the down flow stream, higher diameters, results in higher temperature. Similarly to length of

the reactor, according to the Eq. (2.9), the heat transfer is enhanced with high diameters,

but, on the other hand, the heat transfer is limited for high diameters, since the surface area

diminishes per stream volume.

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Vapor

mola

r fr

acti

on


500 m 600 m 700 m 800 m 900 m 1000 m

1100 m 1200 m 1300 m 1400 m 1500 m



Figure 21: Temperature profile for different diameters of a deep well reactor.

Figure 22 represents the pressure variation for different diameters. It is verified a

decrease in pressure for an increase of diameter.

Figure 22: Pressure variation for different diameters of deep well reactor.

Finally, the molar vapor fraction increases with the length of the reactor as illustrated

in Figure 23.

290

340

390

440

490

540

590

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

T(K

)


0.15 m 0.20 m 0.25 m 0.30 m 0.35 m 0.40 m 0.45 m 0.50 m

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

P(M

Pa)


0.15 m 0.20 m 0.25 m 0.3 m 0.35 m 0.40 m 0.45 m 0.50 m



Figure 23: Molar vapor fraction profiles for different diameters of deep well reactor.

4.4 Composition and reaction kinetics

In this section, an analysis of composition and kinetic reaction is done to better understand

how parameters affect final composition.

Figure 24 represents the composition profile for a reactor of 1000 m in length and a

diameter of 0.20 m. It is observed that glucose is completely oxidized as it was expected.

However, acetic acid was also oxidized to carbon dioxide since oxygen did not react

completely with glucose. Hence, oxygen did not react totally with glucose despite the fact

that a stochiometric amount of oxygen was used.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Vapor

mola

r fr

acti

on


0.15 m 0.20 m 0.25 m 0.30 m 0.35 m 0.40 m 0.45 m 0.50 m



Figure 24: Variation of composition in a deep well reactor.

Figure 25 shows the outlet molar fraction of acetic acid and carbon dioxide. It is

observed that a maximum of acetic acid is present at 700 m of length of reactor and a

maximum of carbon dioxide at length of 1200 m.

Figure 25: Molar composition of acetic acid and carbon dioxide for different lengths of deep

well reactor.

0

0.01

0.02

0.03

0.04

0.05

0.06

0.500 0.502 0.504 0.506 0.508 0.510

xi


Glucose Acetic acid Carbon dioxide Oxygen

11.93

11.94

11.95

11.96

11.97

11.98

11.99

12.00

12.01

48.41

48.42

48.43

48.44

48.45

48.46

48.47

500 600 700 800 900 1000 1100 1200 1300 1400 1500

xCH

3CO

OH

(x 1

03)

xCO

2(x

10

3)

Length of reactor (m)

Carbon dioxide Acetic acid



Moreover, Figure 26 represents the variation of rate of equation for three equations in

Table 1. Global reaction rate of reaction 3 (oxidation of acetic acid to carbon dioxide) is

lower than the reaction rate of reaction 1 (oxidation of glucose to carbon dioxide) and 2

(oxidation of glucose to acetic acid).

Moreover, it is verified that, between 500 m and 600 m of the reactor length, reaction

rate of reaction 1 is lower than the reaction rate of reaction 2, meaning that acetic acid

formation from glucose occurs preferably over total oxidation of glucose. For reactors length

higher than 600 m, reaction rate of reaction 1 is higher than the reaction rate of reaction 2.

Therefore, acetic acid formation decreases from this point. All reaction rates increase with

the length of the reactor and higher length of the reactor leads to higher temperatures

(Figure 18). Hence, reaction rates increase with temperature. Different slopes observed are

related to the different activation energies of the different reactions.

Figure 26: Reaction rates observed for the three reactions at different lengths of the deep

well reactor.

0.00

0.05

0.10

0.15

0.20

0.25

0.30

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

500 600 700 800 900 1000 1100 1200 1300 1400 1500

r 3(k

mol/

(m3·s

)

r 1,

r 2(k

mol/

(m3·s

)

Length of the reactor (m)

Reaction 1 Reaction 2 Reaction 3



4.5 Air flowrate

In this section, air flowrate variation is studied to analyse its effect. These simulations were

made with a reactor length of 1000 m and diameter of 0.2 m.

Therefore, three different flowrates were simulated, such as 1243 kg/h, that

corresponds to 1/5 of the stoichiometric air flowrate. Additionally, air flowrate of 4920 kg/h

corresponds to the minimal flowrate to complete oxidize glucose. Moreover, the maximum

flowrate corresponds to the one for which acetic acid reacts through all length of the reactor.

Figure 27 represents the evolution of temperature for different air flowrates. It is

observed that for the lowest flowrate, temperatures are lower. Moreover, at position 0.50,

temperature drop is not so accented as it is observed for higher flowrates. Therefore, it is

confirmed that this feature is related to gas stream. Lower air flowrate means lower oxygen

content, therefore less oxygen is dissolved.

Furthermore, slope of up flow stream for the lowest air flow rate is sharper than the

others and, according to Eq. (2.10), it depends upon the mass flowrate. The flowrate at up-

flow stream is higher than the flowrate of the down-flow stream, since air is mixed at

position 0.50.

Finally, temperature profiles for 4920 kg/h, 6216 kg/h and 7730 kg/h of air flowrates

are similar to each other.

Figure 27: Temperature profiles for different air flowrates.

290

340

390

440

490

540

590

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

T (

K)

Dimensionless length reactor

1243 kg/h 4920 kg/h 6216 kg/h 7730 kg/h



Figure 28 illustrates variation of pressure for the different air flowrates. It is observed

highest pressure values for the lowest air flowrate and lowest final pressure value is also for

the lowest air flowrate.

Figure 28: Variation of pressure for different air flowrates.

Figure 29 illustrates variation of molar vapor fraction. It is observed that for higher

fractions of molar vapor fraction corresponds to higher air flowrate. By relating this analysis

with pressure variation, it is possible to verify that the lowest flow rate, molar vapor fraction

is widely lower than the others flow rate and, consequently, pressure drop at up flow reactor

is higher.

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

P(M

Pa)


1243 kg/h 4920 kg/h 6216 kg/h 7730 kg/h



Figure 29: Molar vapor fraction profiles for different air flow rates.

Figure 30 represents variation of the final composition, molar fractions of glucose,

acetic acid and carbon dioxide. Oxygen molar fraction is zero is all cases. It is observed that

for the lowest air flowrate, glucose is not completely oxidized. Moreover, acetic acid lows at

air flow rates higher than 4920 kg/h. This air flowrate is the value for which glucose is

oxidized without affecting acetic acid content for a reactor of 1000 m length and 0.20 m

diameter. Finally, acetic acid does not react completely for the length of 1000 m.

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Vapor

mola

r fr

acti

on


1243 kg/h 4920 kg/h 6216 kg/h 7730 kg/h



Figure 30: Final composition of glucose, acetic acid and carbon dioxide for different air

flowrates.

Finally, Figure 31 illustrates reaction rates for reactions in Table 1. Reaction rate of

reaction 1 increases from 1243 kg/h until 4920 kg/h and then decreases for higher air flow

rates. Regarding reaction 2, reaction rate increases with increased air flow rate until 4920

kg/h. From this point, reaction rate stabilizes.

For reaction 3, reaction rate equals to zero up to flowrate of 4920 kg/h, then

increases up to 6216 kg/h. From this point, reaction rate stabilizes.

Figure 31: Reaction rates of different reactions for various air flow rates.

0

0.01

0.02

0.03

0.04

0.05

0.06

1000 2000 3000 4000 5000 6000 7000 8000

Mola

r co

mposi

tion

Air flow rate (kg/h)

Glucose Acetic acid Carbon dioxide

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

r 1,

r 2,r

3(k

mol/

(m3·s

)

Air flow rate (kg/h)




4.6 Composition

In this section, composition of glucose and acetic acid of the process stream varied to analyse

the effects. Table 5 represents the composition considered for each case. Other operational

conditions are represented in Table 2 and Table 4. The first case corresponds to the previous

conditions, and in the second case the content of acetic acid was eliminated. Finally, in third

case, glucose content was reduced.

Air flow rate was adjusted for case 3, since glucose composition changes. Air flowrate

calculated and used for model is 3108 kg/h.

Table 5: Conditions of cases with different compositions of process stream.

Case 𝒙′𝒈𝒍𝒖𝒄𝒐𝒔𝒆 𝒙′𝒂𝒄𝒆𝒕𝒊𝒄 𝒂𝒄𝒊𝒅 𝒙′𝒘𝒂𝒕𝒆𝒓

1 0.10 0.05 0.85

2 0.10 0.00 0.90

3 0.05 0.00 0.95

Figure 32 represents temperature evolution and it is possible to analyse that for case 3

temperature profile is lower than the case 1 and 2. Moreover, temperature profile for case 1

and case 2 are similar. Therefore, heat release on oxidation of the glucose is higher than the

oxidation of acetic acid and, hence, oxidation of glucose contributes in majority for the heat

of the reaction generated.



Figure 32: Temperature evolution for different compositions of the process stream.

Figure 33 represents pressure variation for different compositions of process stream. It

is possible to verify that for case 3 pressure drop is higher than the other cases for up flow

stream.

Figure 33: Pressure profiles for 1000 m of length and 0.20 of diameter for different

compositions of the process stream.

290

340

390

440

490

540

590

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

T(K

)


Case 1 Case 2 Case 3

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

P(M

Pa)





Molar vapor fraction results are represented in Figure 34. Since lower energy is released in

the case 3, with the lowest content of glucose, vapor molar fraction profile is lower than the

others. Hence, pressure drop is higher for case 3.

Figure 34: Molar vapor fraction profiles for 1000 m of length and 0.20 of diameter for

different compositions of the process stream.

Moreover, analysis of composition for cases 2 and 3 were made. Figure 35 and Figure

36 illustrate variation of glucose, acetic acid, carbon dioxide and oxygen for cases 2 and 3,

respectively. It is possible to verify that carbon dioxide production is higher when glucose is

higher. For higher content of acetic acid, higher residence time is needed to oxidize it

completely.

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Vapor

mola

r fr

acti

on





Figure 35: Evolution of composition for case 2.

Figure 36: Evolution of composition for case 3.

Erro! A origem da referência não foi encontrada. represents reaction rates for the

three present reactions. Reactions rates are not affected by acetic acid. Finally, when

glucose composition reduces, all three reaction rates reduce.

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.50 0.52 0.54 0.56 0.58 0.60 0.62 0.64 0.66 0.68

Mola

r com

posi

tion


Glucose Carbon dioxide Acetic acid Oxygen

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.5 0.502 0.504 0.506 0.508 0.51

Mola

r com

posi

tion


Glucose Acetic acid Carbon dioxide Oxygen



Figure 37: Reaction rates of the three cases with different compositions of the process

stream.

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

1 2 3

r 3(k

mo

l/(m

3·s

))

r 1, r

2(k

mo

l/(m

3·s

))

Case #



Conclusion 41

5 Conclusion

WAO is a hydrothermal technology in which compounds, organic and inorganic, are oxidized

to carbon dioxide and water, by oxygen, present in air, at the liquid phase. In this work it was

modelled a non-catalytic WAO process in a deep well reactor, considering that the process

stream composition is based on cow manure.

Vapor molar fraction depends on the composition of the process stream, because the

composition defines the heat generated in the reactor and, consequently, temperature of the

stream. For a same pressure, for higher temperature, higher will be the vapor molar fraction.

Besides composition, air flowrate also influences vapor molar fraction, but a change this

parameter may affect the yield of the product acetic acid. The length and the diameter of

the reactor also contributes for molar vapor fraction. In other words, for higher length and

diameter of the length, higher vapor molar fraction is achieved. This is due to the fact that

these parameters influence the heat transfer.

In fact, heat transfer can be increased with higher length and also with higher

diameter. It was verified that the increased is more notable for the length than for the

diameter, since there is a limited heat transfer for higher diameters due to the ratio surface

area/volume decrease.

Furthermore, it was observed that even though a stoichiometric amount of oxygen for

glucose has been used, some oxygen still remains after all glucose is oxidized. This is due to

the fact that the reaction kinetic did not consider oxygen concentration, such as for glucose.

Hence, reaction rate depends only the glucose concentration. Consequently, the remaining

oxygen oxidizes the acetic acid to form carbon dioxide. In fact, for lower lengths of the

reactor, the formation of acetic acid from glucose oxidation is more favorable than the

complete oxidation of glucose to carbon dioxide. However, for higher temperatures, the

opposite occurs, due to the impact of the different activation energies, besides both reaction

rates increase with the temperature.

Hence, it was verified a higher amount of acetic acid for the length of 700 m. On the

other hand, carbon dioxide maximum production is observed for a length of 1200 m.

Further, process flow diagram with different number of reactors, representing down

flow stream and up flow stream, were developed and tested. It is possible to conclude that

the higher number of reactors leads to a more real and continuous results.


Conclusion 42

Moreover, when air flowrate is lower, lower temperature profile is achieved. In

addition, it is possible to verify that the decrease on the temperature at position 0.50 may be

caused by the mix of the air and by the dissolution of oxygen in water being an endothermic

reaction. Moreover, with low air flow rates, glucose is not completely oxidized, and acetic

acid composition is higher. On the other hand, for high air flow rates acetic acid is oxidized as

well as glucose and carbon dioxide production are higher.

Further, glucose is more relevant than acetic acid for reaction rates of the reactions.

In conclusion, WAO process has potential to be applied as pre-treatment as long as other

considerations, such as formation of inhibitors and other important factors that need to be

considered are taken in account in an overall process analysis.


Conclusion 43

6 Assessment of the work done

6.1 Objectives Achieved

In this work, the main goal was to model a wet air oxidation in a deep well reactor and, to

concretize it, it was necessary to search for model in Aspen Plus and find all the information

that is necessary to model. This goal was fulfilled, and the effect of some parameters were

also studied. Other goals are: a review on manure and municipal solid waste current

management, an understanding of the AD process and how wet air oxidation can be framed,

brief knowledge on the WtE technologies and a realization of house of quality comparing

different processes.

6.2 Limitations and future

The availability of studies with this type of process is limited and, hence, the information, for

instance, of reaction kinetic is also limited. Therefore, a more understanding of the reaction

kinetic and more data would improve the study of this process. Furthermore, since the

simulations were made based on an interactive process, are time-consuming processes.

Therefore, for future, it is to simulate with more reactors.

6.3 Final Assessment

WAO process applied in a deep well reactor is an alternative to thermal hydrolysis process.

Thermal hydrolysis, when applied to AD process, acts similarly to the hydrolysis stage. When

WAO process is applied, theoretically, AD process is reduced to the methanogenesis stage.

Nonetheless, it is reported that high concentrations of acetic acid (VFA) can inhibit AD

process (mainly with food waste). Therefore, it is important to understand that whether

methanogenic bacteria are affected by high levels of VFA, that, indirectly, decreases pH of

the medium. Besides, methanogenic bacteria are strictly anaerobic and, hence, it is

important to notice the presence of oxygen in the liquid stream. One solution is to withdraw

from the system acetic acid and other valuable compounds and use it for another markets.

Finally, by applying this process in a deep well reactor reduces safety concerns, however

there are some limitations regarding the sedimentation at the bottom of the reactor and the

flow regime, and the capital cost that according to the literature is one reason why this

technology is not widely used.


References 45

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References 47

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8947(99)00022-4.

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Wet Oxidation Technology Based on Organic Wastewater Treatment.

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Annex A – Manure treatment technologies 49

Annex A - Manure treatment technologies

Manure treatment technologies can be divided into different categories: solid/liquid

separation, anaerobic treatments, treatments of solid fraction, treatments of liquid fraction

and air cleaning. Table A 1 represents identified manure treatment technologies that can

stand alone or combined [1,2].

Table A 1: Identified manure treatment technologies.

[1] Foged, Henning Lyngsø, Xavier Flotats, August Bonmati Blasi, Jordi Palatsi, Albert Magri

and Karl Martin Schelde. 2011. Inventory of manure processing activities in Europe. Technical

Report No. I concerning “Manure Processing Activities in Europe” to the European

Commission, Directorate-General Environment. 138 pp.

[2] Flotats, Xavier, Henning Lyngsø Foged, August Bonmati Blasi, Jordi Palatsi, Albert Magri

and Karl Martin Schelde. 2011. Manure processing technologies. Technical Report No. II

concerning “Manure Processing Activities in Europe” to the European Commission,

Directorate-General Environment. 184 pp.


Annex B – MSW generation and composition 51

Annex B - MSW generation and management

operations

Figure A 1 represents different composition of MSW generated between EU Member States,

whilst Figure A 2 illustrates evolution of the management operations applied between 1995

and 2015 [1].

Figure A 1: Waste generation by type between EU Member States.

Figure A 2: Waste management operations evolution from 1995 to 2015 in EU.

[1] Scarlat, N., Fahl, F., & François, J. (2019). Status and Opportunities for Energy Recovery

from Municipal Solid Waste in Europe. Waste and Biomass Valorization, 10(9), 2425–2444.

https://doi.org/10.1007/s12649-018-0297-7

https://doi.org/10.1007/s12649-018-0297-7


Annex C – Cow manure composition 53

Annex C - Cow manure composition

Cow manure composition is represented in Figure A 3. It is considered that glucose is

representative of soluble carbohydrate. Hence, values of mass fraction considered are an

approximation taking in account that slurry is, at average, 85% moisture and a ratio between

soluble carbohydrate and VFA to calculate mass fractions of these compounds.

Figure A 3: Composition of cow manure and pig slurry in a 1 kg basis.

[1] Varma, V. S., Parajuli, R., Scott, E., Canter, T., Lim, T. T., Popp, J., & Thoma, G. (2021).

Dairy and swine manure management – Challenges and perspectives for sustainable treatment

technology. Science of the Total Environment, 778, 146319.

https://doi.org/10.1016/j.scitotenv.2021.146319


Annex D –Mass transfer of oxygen 55

Annex D - Mass transfer of oxygen

Another parameter that influences rate of reaction that occur in WAO process is the mass

transfer of oxygen. Considering that the gas side mass transfer resistance is negligible, mass

transfer of oxygen from the gas to the liquid phase depends upon the overall volumetric gas-

liquid mass transfer coefficient or oxygen solubility in the liquid phase (𝑘𝐿 ∙ 𝑎),

𝑟𝑚 = 𝑘𝐿 ∙ 𝑎 ∙ (𝐶𝑂2

∗ − 𝐶𝑂2,𝐿) D 1

where 𝑟𝑚 is the oxygen mass transfer rate, 𝑘𝐿 is the liquid side mass transfer

coefficient, 𝑎 is the gas-liquid interfacial area, 𝐶𝑂2

∗ is the saturated oxygen concentration and

𝐶𝑂2,𝐿 the oxygen concentration in the liquid phase.

Saturated oxygen concentration, 𝐶𝑂2

∗ , rises with both increased temperature and

oxygen partial pressure in the operating range typical for wet air oxidation.

The overall mass transfer coefficient (𝑘𝐿 ∙ 𝑎-) is influenced by operating parameters,

namely reactor geometry, gas flowrate, temperature, pressure and liquid properties, and

their effect on the system characteristics such as gas hold-up, flow regime, bubble diameter,

interfacial are and the mass transfer coefficient [1].

[1] Kolaczkowski, S. T., P. Plucinski, F. J. Beltran, F. J. Rivas, and D. B. McLurgh. 1999. “Wet

Air Oxidation: A Review of Process Technologies and Aspects in Reactor Design.” Chemical

Engineering Journal 73 (2): 143–60. https://doi.org/10.1016/S1385-8947(99)00022-4.

https://doi.org/10.1016/S1385-8947(99)00022-4


Annex E – WAO mechanism 57

Annex E - WAO mechanism

WAO mechanism is a free radical reaction, in which oxygen reacts with the weakest C-H bond

of the oxidized organic compound. This mechanism can be divided in three stages: initiation,

propagation and termination. During initiation, radicals are formed (E1 to E2). Then, in

propagation stage, formed radicals react with other molecules to form more radicals (E3 to

E4) and, finally, in termination step, two radicals react to form a non-radical molecule (E 5 to

E 7) [1, 2].

𝑅𝐻 + 𝑂2 → 𝑅 • +𝐻𝑂𝑂 • (E 1)

2𝑅𝐻 + 𝑂2 → 2𝑅 • +𝐻2𝑂2 (E 2)

𝑅 • +𝑂2 → 𝑅𝑂𝑂 • (E 3)

𝑅𝑂𝑂 • +𝑅𝐻 → 𝑅𝑂𝑂𝐻 + 𝑅 • (E 4)

𝑅 • +𝑅 •→ 𝑅 − 𝑅 (E 5)

𝑅𝑂𝑂 • +𝑅 •→ 𝑅𝑂𝑂𝑅 (E 6)

𝑅𝑂𝑂 • +𝑅𝑂𝑂 •→ 𝑅𝑂𝐻 + 𝑅1𝐶𝑂𝑅2 + 𝑂2 (E 7)

[1] Li, L., Chen, P., & Gloyna, E. F. (1991). Generalized Kinetic Model for Wet Oxidation of

Organic Compounds. 37(11), 1687–1697.

[2] Zhang, Y. (2020). Wet Oxidation Technology Based on Organic Wastewater Treatment Wet

Oxidation Technology Based on Organic Wastewater Treatment.

https://doi.org/10.1088/1742-6596/1549/2/022040


Annex F – Pressure correlation 58

Annex F - Pressure correlation

Beggs-Bill correlation was used to estimate pressure variation. This method is suitable for all

reactor inclinations, including downhill. Pressure gradient is a function of pressure gradient

due to friction, hydrostatic pressure and pressure loss due to acceleration, 𝑒𝑘.

𝑑𝑝

𝑑𝑧= [(

𝑑𝑝

𝑑𝑧)

𝑓𝑟𝑖𝑐.+ (

𝑑𝑝

𝑑𝑧)

ℎ𝑦𝑑𝑟𝑜.] ∙ (1 − 𝑒𝑘) F 1

Hydrostatic pressure is a function of acceleration gravity (9.8 m2/s) and density, 𝜌, and the

column, ℎ:

(∆𝑝)ℎ = 𝜌 ∙ 𝑔 ∙ ℎ F 2

[1] Tech, A.. Aspen Plus: Unit Operation Models. Available at :

https://courses.ucsd.edu/jtalbot/ceng122/aspen/asp_unitops.pdf (last access on 17th

September 2021)

[2] CheGuide.. Beggs & Brill Method. https://cheguide.com/beggs_brill.html (last access on

17th September 2021)

https://courses.ucsd.edu/jtalbot/ceng122/aspen/asp_unitops.pdf

https://cheguide.com/beggs_brill.html


Appendix A – Air flowrate 60

Appendix A - Air flowrate

Glucose oxidation reaction is represented in Eq. (B1), in which 1 mole of glucose reacts with 6

mole of oxygen.

C6H12O6 + 6O2 → 6H2O + 6CO2 A 1

Converting these numbers to mass reference and taking molecular weights of each

component, it is possible to calculate ratio between glucose and oxygen in mass reference:

𝑀(C6H12O6)= 180 g/mol

𝑀(O2) = 32 g/mol

One mole of glucose corresponds to 180 g and 6 mole of oxygen correspond to 192 g (6

x 32). Therefore, for 1 kg of glucose is necessary 192 kg of oxygen. Initial mass fraction of

glucose in the process stream is 0.10 and hence, quantity of glucose is:

Glucose in process stream = 12200 (kg h⁄ ) × 0.1 = 1220 kg/h

Hence, quantity of oxygen needed is:

O2 = 1220 × 1.07 = 1305.4 kg/h

Since oxygen mass fraction present in air stream is 0.21, air flowrate necessary to

have stoichiometric oxygen is:

𝐹𝑎𝑖𝑟 =1305.4

0.21≈ 6216 kg/h


Appendix B – Mass and energy balances 61

Appendix B - Mass and energy balances

Mass and energy balance of simulation with conditions established in Table A 2 and Table A 3

were analyzed for model A. Table A 4 represents main results. A balance is calculated simply

calculating the difference between outlet stream (P-out) and inlet streams (P-in and Air). The

differences may be due to the high content of gas at up flow stream.

Table A 2: Mass balance.

𝑭𝒊𝒏𝒍𝒆𝒕 (kg·h-1) 𝑭𝒐𝒖𝒕𝒍𝒆𝒕 (kg·h-1) Difference (kg·h-1)

18416 18416.2 0.2

The same approach can be same for energy balance, Table

Table A 3: Energy balance.

𝑯𝒇,𝒊𝒏𝒍𝒆𝒕 (MW) 𝑯𝒇,𝒐𝒖𝒕𝒍𝒆𝒕 (MW) Difference (MW)

-49.25 -49.33 0.08

Table A 4: Results of the simulation of reactor with 1000 m of length and 0.20 m of

diameter.

Property Stream

P-inlet S2 S3 Air S4 S5 P-out

𝑻 (K) 293.15 449.85 504.85 473.15 466.77 529.97 511.15

𝑷 (MPa) 0.5 7.70 7.70 15 7.70 7.17 7.17

𝑭 (kg·h-1) 12200 12200 12200 6216 18416 18416.2 18416.2

Molar vapor fraction 0 0 0 1 0.347 0.821 0.539

𝑯(MJ/kg) -14.62 -13.98 -13.74 0.18 -9.04 -9.20 -9.643

𝑯𝒇(𝑴𝑾) -49.56 -47.39 -46.57 0.31 -46,26 -47.08 -49.33

𝒙′𝒈𝒍𝒖𝒄𝒐𝒔𝒆 0.1 0.1 0.1 - 0.066 - -

𝒙′𝒂𝒄𝒆𝒕𝒊𝒄 𝒂𝒄𝒊𝒅 0.05 0.05 0.05 - 0.033 0.033 0.033

𝒙′𝒄𝒂𝒓𝒃𝒐𝒏 𝒅𝒊𝒐𝒙𝒊𝒅𝒆 - - - - - 0.097 0.097

𝒙′𝒐𝒙𝒚𝒈𝒆𝒏 - - - 0.21 0.071 - -

𝒙′𝒘𝒂𝒕𝒆𝒓 0.85 0.85 0.85 - 0.563 0.603 0.603

𝒙′𝒏𝒊𝒕𝒓𝒐𝒈𝒆𝒏 - - - 0.79 0.267 0.267 0.267


Appendix C – House of quality 62

Appendix C - House of quality

House of quality were made for each feedstock to compare WtE technologies. Figure x and x

are the results. In both, anaerobic digestion with thermal hydrolysis is within the three best

options.

Figure A 4: House of quality for manure.

Figure A 5: House of quality for MSW.

modelling of wet air oxidation in a deep well reactor …

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